INDIA DAILY
December 29, 2020 India 28-Dec 1-day 1-mo 3-mo Sensex 47,354 0.8 7.3 24.7 Nifty 13,873 0.9 7.0 23.6 Contents Global/Regional indices Special Reports Dow Jones 30,404 0.7 1.8 11.9 Nasdaq Composite 12,899 0.7 6.7 18.2 Initiating Coverage FTSE 6,502 0.1 1.7 11.3 SBI Cards and Payment Services: Swipe to earn Nikkei 27,163 1.2 1.9 15.4 Hang Seng 26,315 (0.3) (2.2) 13.1 Initiate coverage with ADD: an attractive long-term compounding story. KOSPI 2,812 0.1 6.8 20.8
A two-pronged play on payments and lending on small-ticket consumption Value traded – India items Cash (NSE+BSE) 510 724 443 13,86 Derivatives (NSE) 16,425 15,566 International experience shows credit card business quite favorably 8 Key risks: micro and macro risks that are typical of this nature of businesses Deri. open interest 5,010 3,897 3,360
Forex/money market
Change, basis points
28-Dec 1-day 1-mo 3-mo
Rs/US$ 73.5 (5) (54) (28)
10yr govt bond, % 6.2 (1) 4 (21)
Net investment (US$ mn)
24-Dec MTD CYTD
FIIs (68) 6,382 22,488 (2,626 MFs (157) (6,062) ) Top movers
Change, %
Best performers 28-Dec 1-day 1-mo 3-mo
TATA in Equity 633 1.7 9.6 71.0
SHTF in Equity 1,016 2.0 (5.1) 66.7
IIB in Equity 867 1.7 1.1 61.7
BAF in Equity 5,204 0.4 6.0 58.0
KMB in Equity 1,989 1.4 4.3 57.4
Worst performers
RIL in Equity 2,003 0.5 3.8 (10.8)
UPLL in Equity 453 0.9 8.5 (8.1)
BOS in Equity 12,841 1.2 0.2 (5.9)
BRIT in Equity 3,604 (0.4) (0.9) (3.6)
HMCL in Equity 3,083 0.3 (0.8) (2.9)
[email protected] Contact: +91 22 6218 6427
For Private Circulation Only. FOR IMPORTANT INFORMATION ABOUT KOTAK SECURITIES’ RATING SYSTEM AND OTHER DISCLOSURES. REFER TO THE END OF THIS MATERIAL. Company Report SBI Cards and Payment Services (SBICARD) ADD Banks December 28, 2020 INITIATING COVERAGE Sector view: Attractive Swipe to earn. We initiate coverage on SBI Cards (SBIC) with an ADD rating and Fair CMP (`): 840 Value of Rs900. We believe that the positives of (1) strong revenue growth led by rising and underpenetrated payments play, (2) highly profitable lending book and (3) benefit Fair Value (`): 900 of a strong parentage that can lower the origination risk are partly offset by expensive BSE-30: 47,354 valuations. We like the space as it is one of the few areas where we see strong growth prospects and we like SBIC given its strong market share.
Initiate coverage with ADD: an attractive long-term compounding story
We initiate coverage on SBI Cards (SBIC) with an ADD rating, valuing the company at a Fair Value of Rs900, which implies a valuation of 30X FY2023 EPS and ~8X PBR. This implies a 7% INSIDE upside from current levels. SBIC has delivered strong earnings growth of 40% CAGR for Superior growth FY2017-20 and we expect 30% CAGR for FY2020-24. With a reasonably long growth runway, we see valuation premium to remain high in the medium term which, in our view, metrics for SBI should result in lower risk to multiple de-rating and remain a solid compounder. Cards…….pg12
A two-pronged play on payments and lending on small-ticket consumption items Long growth runway...... pg27 There are two distinct characteristics that differentiate SBIC from other lending products – (1) rapid expansion in infrastructure for accepting digital payments (online and offline) that has led to better digital adoption trends leading to a solid play on low risk payment-related income Low card penetration and (2) ability to build a long-term lending relationship which is high yielding, granular, short in India…...pg43 term and yet, highly profitable. Low penetration of digital products implies that the growth trajectory is quite healthy.
International experience shows credit card business quite favorably
In this report, we discuss (1) trends on retail payment behavior across time periods and different geographies, (2) stakeholders’ perspectives on credit cards and (3) the earnings model of the M B Mahesh, CFA credit card business. On a risk-adjusted basis, we believe that this business is quite profitable on a through-the-cycle basis. Nischint Chawathe Key risks: micro and macro risks that are typical of this nature of businesses Abhijeet Sakhare There are several risks to our thesis: (1) SBIC is a standalone credit card company with limited access to data as compared to a traditional bank. (2) The business is cyclical and expensive with greater emphasis on analytics. (3) Earnings can be extremely volatile and different models in Ashlesh Sonje the credit card business can lead to wide variation among players in this segment. (4) Regulatory intermediation on inter-change fees can lead to lower adoption rates. (5) Intermediation of Dipanjan Ghosh credit- or payment-related function through alternate products can disrupt SBIC’s business model. (6) Relationship with SBI is crucial to build better returns.
Company data and valuation summary
Company data Stock data High Low Price performance 1M 3M 12M Rating: ADD 52-week range (Rs) 919 495 Absolute (%) 5.1 (0.2) NA Rel to BSE-30 (%) (2.7) (21.2) NA CMP (Rs) Price at close of: December 28, 2020 840 Capitalization Forecast / valuation 2021E 2022E 2023E Market cap (Rs bn) 790 EPS (Rs) 13.3 20.0 29.2 Promoter (%) 69 P/E (X) 63.1 41.9 28.8 Free float (%) 31 P/B (X) 12.2 9.6 7.3 Shares outstanding (# mn) 940 RoE (%) 21.1 25.6 28.8 [email protected] Contact: +91 22 6218 6427
Source: Company data, Kotak Institutional Equities estimates
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SBI Cards and Payment Services Banks
BUSINESS OVERVIEW: KEY FINANCIALS
Exhibit 1: SBI Cards: key financial metrics March fiscal year-ends, 2018-24E
Cost- Credit PAT EPS BVPS RoA RoE Cards Loans Spends NIM income costs (Rs bn) (Rs) (Rs) (%) (%) (# mn) (Rs bn) (Rs bn) (%) (%) (%) 2018 6.0 7.7 30 4.6 31.7 6.3 140 765 15.5 63.1 6.6 2019 8.6 10.3 43 4.8 29.1 8.3 179 1,033 14.4 60.4 6.4 2020 12.4 13.3 57 5.5 27.9 10.5 228 1,309 15.6 56.6 9.5 2021E 12.5 13.3 69 4.6 21.1 12.0 264 1,056 15.4 49.1 12.0 2022E 18.8 20.0 88 5.9 25.6 15.6 317 1,764 14.7 59.1 7.5 2023E 27.4 29.2 115 6.9 28.8 20.1 416 2,311 15.6 59.7 6.5 2024E 36.3 38.7 152 7.0 29.0 25.7 541 3,007 15.8 60.9 5.8
Source: Company
Exhibit 2: SBI Cards: financial summary March fiscal year-ends, 2018-24E (Rs mn)
2018 2019 2020 2021E 2022E 2023E 2024E Income statement NII 20,524 25,664 35,404 41,961 46,919 62,314 81,321 Other income 26,102 37,110 49,104 49,106 68,302 88,232 113,708 Total income 46,626 62,774 84,508 91,067 115,222 150,547 195,029 Operating expenses 29,406 37,947 47,809 44,748 68,124 89,886 118,686 PPOP 17,221 24,827 36,699 46,319 47,098 60,660 76,343 Impairment losses and bad debts 7,990 11,477 19,402 29,528 21,805 23,838 27,521 PBT 9,230 13,350 17,296 16,791 25,293 36,823 48,821 Taxes 3,195 4,701 4,848 4,299 6,475 9,427 12,498 PAT 6,036 8,649 12,448 12,493 18,818 27,396 36,323 EPS 8 10 13 13 20 29 39 Growth (%) 55 43 44 0 51 46 33 Balance sheet Assets Cash and bank balances 4,727 7,768 6,760 7,436 8,180 8,998 9,898 Net loans and advances 140,455 179,087 228,116 264,016 317,453 416,015 541,246 Fixed assets 1,754 2,164 3,346 3,802 4,961 6,385 8,143 Other assets 8,890 12,440 14,806 16,286 17,915 19,706 21,677 Total assets 155,826 201,459 253,028 291,540 348,509 451,104 580,963 Liabilities Borrowings 113,040 135,494 173,649 197,528 234,107 307,713 399,659 Other financial liabilities 6,449 9,577 6,713 8,055 8,861 9,747 10,722 Other liabilities 12,769 20,513 19,254 21,179 23,297 25,627 28,189 Total liabilities 132,258 165,584 199,616 226,762 266,265 343,087 438,570 Shareholders' equity Paid up capital 7,850 8,372 9,390 9,390 9,390 9,390 9,390 Reserves and surplus 15,719 27,506 44,023 55,389 72,854 98,628 133,004 Shareholders' equity 23,569 35,878 53,412 64,778 82,244 108,017 142,394 RoE decomposition (% of average assets) NII 15.5 14.4 15.6 15.4 14.7 15.6 15.8 Other income 19.8 20.8 21.6 18.0 21.3 22.1 22.0 Total income 35.3 35.1 37.2 33.4 36.0 37.7 37.8 Operating expenses 22.3 21.2 21.0 16.4 21.3 22.5 23.0 PPOP 13.0 13.9 16.1 17.0 14.7 15.2 14.8 Provisions 6.1 6.4 8.5 10.8 6.8 6.0 5.3 PBT 7.0 7.5 7.6 6.2 7.9 9.2 9.5 RoA 4.6 4.8 5.5 4.6 5.9 6.9 7.0 Average assets/average equity (X) 6.9 6.0 5.1 4.6 4.4 4.2 4.1 RoE 31.7 29.1 27.9 21.1 25.6 28.8 29.0
Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 3
Banks SBI Cards and Payment Services
VALUATIONS We initiate coverage on SBIC with an ADD rating and Fair Value of Rs900. At our FV, we are valuing the business at 30X FY2023 EPS. This implies an 8X PBR. Earnings, as compared to net-worth-based valuation, is our preferred way as there is a play on payments that is not driven by capital adequacy levels. A risky business but is a largely underpenetrated industry. Rapid adoption of the product in recent years is a key positive argument. SBIC is one of the largest issuers of cards, making it a solid franchise.
Initiate with ADD rating with Rs900 Fair Value We initiate coverage on SBI Cards with an ADD rating and value the company at Rs900 (see exhibit 1). This implies a value of 8X book and 30X March 2023E EPS for RoEs in the range of 25-30% in the short term without factoring in possible dilution of equity led by strong earnings growth. We value SBI Cards using a residual growth model assuming (1) cost of equity of 13.0% (similar to frontline banks given the quasi sovereign nature of the parent bank and related advantages in terms of availability and cost of capital), (2) medium-term earnings growth of ~30% CAGR, tapering to long-term growth of 7% and (3) long-term RoEs moving closer to 17-18% while medium-term RoEs would be strong at 25-30%.
Exhibit 3: We value SBI Cards at 8X book and 30X March 2023E EPS Residual growth model of SBI Cards, March fiscal year-ends, 2021-41 (Rs bn)
SBI Cards: Residual growth model Risk free rate (%) 8.0 Beta (X) 1.0 Risk premium (%) 5.0 Cost of equity (Re) (%) 13.0 Terminal growth rate (%) 7.0 Dividend payout from 2024E 20% 2021 2022 2023 2024 2025 2035 2036 2037 2038 2039 2040 2041 Terminal Year 0 0 1 2 3 13 14 15 16 17 18 19 20 EPS 13 20 29 39 51 372 416 462 508 554 598 640 685 % growth 0.4 50.6 45.6 32.6 33.0 13.0 12.0 11.0 10.0 9.0 8.0 7.0 7.0 BVPS 69 88 115 152 193 1,800 2,133 2,503 2,909 3,353 3,831 4,343 3,915 % growth 21 27 31 32 27 20 19 17 16 15 14 13 Re*BVPS 7 9 11 15 20 195 234 277 325 378 436 498 176 Residual income 6 11 18 24 32 176 182 185 183 176 163 142 2,936 % growth (23) 87 61 33 34 5 3 1 (1) (4) (8) (13) PV of residual income (Rs) 5.9 11.1 15.7 18.6 22.0 36.0 32.9 29.5 25.9 22.0 18.0 13.9 254.8
RoE (beginning equity) (%) 23.4 29.0 33.3 33.6 33.9 24.7 23.1 21.7 20.3 19.0 17.8 16 .7 17.5
Current BVPS (Rs) 115 PV of residual income (Rs) 798 Fair value (BVPS + PV of income) (Rs) 913 Target PBR - FY2022E 10.4 Target PBR - FY2023E 7.9 CMP (Rs) 835 Upside (%) 9.3
Source: Company, Kotak Institutional Equities estimates
Net-worth-based valuation model as compared to earnings-based valuation model We see two broad valuation frameworks for SBI Cards. The first is the more traditional residual growth model where we look at the excess earnings growth that the business is generating over its cost of equity. On the other hand, we see a strong argument to primarily look at the earnings-based business. The primary argument for choosing this approach is the play on payments that is not available in other lending-based businesses. A card provider offers two services: (1) payment and (2) loans. The play on payments is sufficiently large and does not consume capital. Hence, the growth of the business is not related to the business’ capital levels. While we see a strong merit to this argument, we do note that there is a strong lending-related business as well, especially for credit card companies like SBIC. Hence, we are currently using a residual growth model to value this business currently.
4 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Superior and profitable growth business drives a higher valuation multiple
We give a much higher-than-normal multiple for SBIC. We believe the following reasons drive this argument.
A largely underpenetrated segment with a fairly superior runway for growth. When we look at the lending landscape across the retail and corporate lending segments, we believe that the credit card business would probably have the fastest growth. Even MFI has a very large penetration, in our view gives more opportunity primarily through a higher ticket size. In credit cards, we see extremely low levels of penetration (<5% of population) followed by steady rise in average annual spends to be a major driver of growth for the entire industry. Within this space, we believe that the leaders would have a disproportionately large market opportunity. We see SBIC as a major player which is likely to take advantage of this space.
Play on payment and lending makes it different compared to its peers. While banks are essentially a play on the lending side led by a business model that gets differentiated through its funding franchise, SBIC offers a play on payments and lending. The payment side has negligible risks and the high share of revenues makes it different to other companies. The lending business gives the traditional play.
Credit card business is complex but highly profitable business. Our understanding of the payment space suggests that the credit card space is highly complex as there a need to continuously engage with their customer to keep them active while ensuring that the risks are within an acceptable framework. The risk reward of this business is reflected in the superior earnings profile. We see SBIC trading at superior multiples given its high RoEs as we have seen with other financial lenders in this space (see exhibit 4 and 5).
Niche play. While we would not place a higher weight to this argument compared to the ones mentioned above, we would note that SBIC is a niche play in the Indian financial landscape. Its highly profitable and strong growth implies that it is most likely to have a higher-than-normalized earnings multiple. Most cards businesses’ is within the bank and its earnings, even if it is similar or superior to SBIC, is not readily distributable to the shareholder. If anything, the bank would essentially cross-subsidize its profits from cards to areas where it needs to invest or build scale of relatively suboptimal profits.
Acquisition engine of a standalone credit card company is different. From our various studies we note that the standalone credit card companies have models that typically focus on riskier customer segment that the large banks have been reluctant to lend to. While there are exceptions to this argument, this was more visible during the 1980-2008 in a few geographies. Acquisition cost is quite prohibitive which results in building a preference to the riskier customer segments. SBIC differentiates itself in this argument where the acquisition engine is running on SBI’s platform. The tie-up not only reduces the cost of acquisition but the pool of customers that the bank has is quite superior as it is the largest bank. The only challenge is that the customer base is less profitable on a per card basis as we believe that they are likely to be transactors rather than revolvers. However, this would be offset partly through lower cost of acquisition, better activation and lower provisions.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 5
Banks SBI Cards and Payment Services
Exhibit 4: Relative valuation comparison RoE and FY2020-23E revenue CAGR, March fiscal year-ends (%)
25
EQUITAS 20 SBICARD AUBANK BAF UJJIVANS 15 BANDHAN
Axis HDFCB 10 DCB
23E Revenue CAGR (%) RBL ICICI - FB CUBK 5 KVB
FY2020 IIB
- 0 6 12 18 24 30 FY2022E RoE (%)
Source: Company, Kotak Institutional Equities estimates
Exhibit 5: Relative valuation comparison RoE vs PBR, March fiscal year-end, 2022E
10
SBICARD 8 BAF
6
AUBANK 4 HDFCB
FY2022E PBR (X) BANDHAN UJJIVANS CUBK 2 ICICI YES DCB EQUITAS IIB KVB FB 0 (5.0) - 5.0 10.0 15.0 20.0 25.0 30.0 FY2022E RoE (%)
Source: Company, Kotak Institutional Equities estimates
Exhibit 6: SBI Cards trades at a fairly rich multiples on book value basis Valuation comparable metrics, March fiscal year-ends, 2021-23E
EPS CAGR RoE (%) RoA (%) PE (X) Adj. BVPS (Rs) Ad. PBR (X) CMP FV Reco. FY2020-23E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E SBI Cards 840 900 ADD 30 21.1 25.6 28.8 4.6 5.9 6.9 63 42 29 69 88 115 12.2 9.6 7.3 AU 856 690 SELL 13 24.2 12.5 14.3 2.5 1.3 1.4 22 35 27 178 201 232 4.8 4.3 3.7 Axis Bank 618 625 BUY 110 10.9 12.3 13.9 1.0 1.1 1.2 18 14 12 310 342 382 2.0 1.8 1.6 Bandhan Bank 406 400 ADD 10 19.3 16.3 16.9 3.2 2.8 2.7 20 20 16 110 130 156 3.7 3.1 2.6 Bajaj Finance 5,204 3,000 REDUCE 25 12.8 20.4 21.5 2.6 4.4 4.7 71 39 30 603 723 875 8.6 7.2 6.0 City Union 182 170 REDUCE 23 9.1 11.6 13.5 1.0 1.3 1.5 27 19 15 69 76 90 2.6 2.4 2.0 DCB 119 150 BUY 15 8.8 10.0 13.0 0.7 0.9 1.1 13 10 7 105 112 127 1.1 1.1 0.9 Equitas Holdings 66 100 BUY 39 9.2 8.8 15.4 1.2 1.0 1.7 8 8 4 84 91 105 0.8 0.7 0.6 Federal Bank 67 80 BUY 15 9.4 9.5 13.2 0.8 0.8 1.1 10 9 6 73 78 86 0.9 0.9 0.8 HDFC Bank 1,413 1,475 ADD 12 15.9 15.5 16.0 1.8 1.8 1.8 27 24 21 348 390 440 4.1 3.6 3.2 ICICI Bank 520 600 BUY 35 12.3 12.3 12.5 1.4 1.6 1.5 22 19 17 199 217 239 2.1 1.9 1.7 IIB 867 900 ADD 6 5.5 11.2 12.5 0.6 1.3 1.4 33 14 12 494 550 616 1.8 1.6 1.4 KVB 46 65 BUY 47 5.6 7.4 10.0 0.5 0.7 0.9 10 7 5 73 78 85 0.6 0.6 0.5 Ujjivan SFB 40 40 ADD 19 10.1 8.9 14.1 1.7 1.5 2.3 22 23 13 18 20 23 2.2 2.0 1.7 YES 18 11 SELL NM (5.3) (2.2) 0.7 (0.6) (0.3) 0.1 (30) (59) 190 11 11 11 1.6 1.6 1.6
Source: Company, Kotak Institutional Equities estimates
6 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Strong visibility on medium-term growth; robust recovery post Covid
We believe the credit card growth story has just started unfolding with visibility of multi-year growth. Factors that will drive growth are (1) expansion of card base in the country (India has just ~30 mn credit card holders compared to ~300 mn people with bureau records) and (2) greater share of payment flows happening through electronic payments including credit cards. SBIC being #2 player in the market both in terms of cards outstanding and spends, is likely to be a key beneficiary of this trend.
SBIC has few key factors in its favor: (1) dedicated management focus being a pure-play company (albeit with associated risks), (2) credibility and trust coming from ‘SBI’ brand name which helps both in terms of brand recall as well as access to SBI’s customer base in smaller cities and (3) backing of SBI (~70% stake) which provides an implicit backstop in terms of cost and availability of debt and equity capital. As a result, we forecast 25% CAGR over FY2020-24E in terms of growth in card base and annual spends (see exhibit 7 and 8).
Exhibit 7: We expect card base to grow ~25% CAGR over Exhibit 8: We expect annual spends to grow ~25% CAGR over FY2020-24E FY2020-24E Cards outstanding and yoy growth, March fiscal year-ends, 2014-24E Annual spends and yoy growth, March fiscal year-ends, 2014-24E
(# mn) Cards outstanding (LHS) YoY (RHS) (%) (Rs bn) Spends (LHS) YoY (RHS) (%) 30 40 3,500 100
24 32 2,800 75
18 24 2,100 50
12 16 1,400 25
6 8 700 0
0 0 0 -25
2014 2015 2017 2018 2019 2016 2020
2014 2015 2016 2017 2018 2020 2019
2021E 2022E 2023E 2024E
2022E 2023E 2024E 2021E
Source: Company, Kotak Institutional Equities estimates Source: Company, Kotak Institutional Equities estimates
Revenues have a good mix of non-lending fees
One of the key aspects of the cards business that differentiates it from a traditional lending business is the strong contribution of non-lending income in the overall revenues. Fees and other non-interest income have contributed ~55% of total revenues over the past few years. However, FY2021E is likely to be an odd year with most fee streams impacted as the pandemic led to lower spend-driven interchange fees and lower instance-based and annual membership fees as well.
We expect overall revenues to grow ~23% over FY2020-24E (see exhibit 9), nearly equally across net interest income and non-interest income (see exhibit 10). In terms of receivables mix, FY2020 saw a skew towards higher-risk revolver book, followed by trend reversal in FY2021E. We expect the mix to normalize back to FY2019 levels by FY2022-23E (see exhibit 11).
KOTAK INSTITUTIONAL EQUITIES RESEARCH 7
Banks SBI Cards and Payment Services
Exhibit 9: Revenue growth to recover by 2022E Breakup of revenue, March fiscal year-ends, 2013-24 (Rs bn, %)
Net interest income Non-interest income Revenue growth yoy (RHS) 200 80
160 64
120 48
80 32
40 16
0 0
2015 2016 2017 2020 2013 2014 2018 2019
2021E 2022E 2024E 2023E
Source: Company, Kotak Institutional Equities estimates
Exhibit 10: Non-interest income to recover by FY2022E Exhibit 11: Share of revolver balances increased in 2020 Breakup of revenue, March fiscal year-ends, 2013-24 (%) Breakup of outstanding balances, March fiscal year-ends, 2017-24 (%)
Net interest income Non interest income Term Revolver Transactor 100 100 17 23 24 26 31 27 27 27 80 80 54 55 54 54 56 56 59 58 54 59 59 58 60 60 51 45 47 46 40 45 45 45 40 40
20 46 45 46 46 44 44 41 42 46 41 41 42 20 32 29 29 32 29 28 28 28
0 0
2017 2018 2019 2020
2013 2014 2015 2016 2018 2019 2020 2017
2022E 2023E 2021E 2024E
2021E 2023E 2024E 2022E
Source: Company, Kotak Institutional Equities estimates Source: Company, Kotak Institutional Equities estimates
Covid-led rise in stress loans and credit costs; expect normalization from FY2022E
We expect credit costs (gross) of 12% in FY2021E (see exhibit 12), followed by sharp moderation to 7.5% in FY2022E and 6.5% in FY2023E. Post start of Covid, SBIC witnessed large rise in moratorium book during the regulatory dispensation, rising to ~30% levels in April-May before falling to 6% in June. However, around 9% of receivable book has utilized RBI’s restructuring scheme with large share comprising self-employed segment, which has been acquired through the open market channel. Further, reported GNPL increased to 4.3% by 2QFY21 from 1.4% in 1QFY21 (higher 7.5% GNPL ex impact of extended standstill).
8 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 12: We expect credit costs to normalize by FY2022E back to FY2019 levels Credit costs (% of loans), March fiscal year-ends, 2013-24E (%)
13.0 12.0
10.4 9.5
7.5 7.8 7.2 6.6 6.5 5.8 5.2 4.7 4.6 4.1 3.9
2.6
0.0
2014 2016 2017 2019 2015 2018 2020
2021E 2022E 2024E 2023E
Source: Company, Kotak Institutional Equities estimates
Top-of-the-line RoEs within the lending universe
We expect SBIC to make 21% RoE in FY2021E, ramping up to 25-30% in FY2022-24E as it emerges from the one-off Covid impact (see exhibit 13). These return ratios are one of the highest across our coverage universe and represent the nature of the underlying business, which has a high share of fee income as well as high-yielding lending book. These RoEs compare with ~30% average RoE the company delivered over FY2018-20. We expect earnings growth trajectory to resume from FY2022E as credit costs normalize and revenue drivers continue to gain traction, especially spend-related fees (see exhibit 14). The key operating variables that we expect to drive financial performance are (1) strong card additions at ~25% CAGR over FY2021-23E to reach ~20 mn cards and (2) nearly flattish spend per card at Rs130,000 barring the blip in FY2021E due to Covid.
Exhibit 13: We expect RoEs to recover to ~30% by FY2023E Exhibit 14: We expect ~30% PAT CAGR over FY2021-23E RoA and RoE, March fiscal year-ends, 2013-24E (%) PAT and yoy growth, March fiscal year-ends, 2013-24E (%)
RoE RoA (RHS) PAT PAT growth yoy (RHS) 50 8.0 40 120
40 6.4 32 90
30 4.8 24 60
20 3.2 16 30
10 1.6 8 0
0 - 0 (30)
2013 2014 2015 2016 2018 2019 2020 2017
2013 2015 2016 2017 2018 2019 2020 2014
2021E 2022E 2023E 2024E
2022E 2023E 2024E 2021E
Source: Company, Kotak Institutional Equities estimates Source: Company, Kotak Institutional Equities estimates
KOTAK INSTITUTIONAL EQUITIES RESEARCH 9
Banks SBI Cards and Payment Services
Key risks: evolving industry landscape, regulations, dependence on SBI
SBI Cards is a single product company in a fast-evolving industry landscape
Unlike a bank, which offers a wide range of payment services, SBIC is a single-product company. While the company is well-equipped to manage the changes with the credit card landscape, any material behavioral change of consumers outside of credit cards could be a potential area of risk. We have seen evolution of new payment/credit substitutes for credit cards such as Buy Now Pay Later, which have gained some market share in select countries.
Interchange fees play a very critical role in revenues
SBIC generates substantial amount of revenue through interchange fees and business development incentives (~1.7% of spends). A key risk is that the bank is dependent on third-party networks like Visa, MasterCard and Rupay as they help in processing the payments made by their credit card customers. The contribution of this fee income is ~25% of the total revenues. Outside of the dependency on these networks, the risk of interchange fees being regulated is a key area of risk. While not on the anvil, we have seen MDR or interchange fees dropping quite consistently in select markets. A steady decline in MDR rates reduces the efficacy of the product.
The usage of the brand ‘SBI’ and its distribution
As of 3QFY21, SBI owns 69.5% in SBIC. SBIC has a non-exclusive and non-transferable right to use the logo and certain trademarks for its business operations. SBI can terminate the agreement for various specified factors which includes the bank’s stake in the company falling <26%.
SBIC will provide branch relationship executives at select branches of SBI. SBI provides referrals to the company generated through various channels as decided by SBI. SBIC pays a commission to SBI. The company pays a royalty of 2% or 0.2% of total income, whichever is higher.
Others
The payment landscape in India is showing a lot of promise on digital adoption. However, what remains unclear is the payment product that would get adopted and what would be the relative comfort to use credit cards over other channels.
The cost of running this business is quite high. SBIC needs to constantly build strong analytical insights to ensure that the risk is minimized when the economy moves in a different direction. Also, the cost of acquisition is quite high as there is a need to constantly engage with the customer. The utility of the card, for the customer, beyond points, a limited interest free period to pay the previous month’s payment and the lending option is not something that cannot be disrupted. Hence, it becomes critical for SBIC, which is a standalone credit card company to understand these trends and suitably develop models to protect its customer base.
10 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
SBI CARDS: A PURE-PLAY BUSINESS IN A PHASE OF RAPID GROWTH SBIC is the second-largest credit card issuer in India with 19% market share of the Indian credit card market in terms of the number of credit cards outstanding. The company is a subsidiary of SBI, India’s largest commercial bank, and has a strong track record of growth and profitability. SBIC offers a wide range of majorly SBI branded and co-branded credit cards to diverse customer segments and has been growing its credit card portfolio at a robust pace of >30%, higher than the industry average.
A strong growth in pure-play business on payment and lending
SBIC is the second-largest credit card issuer in India both in terms of number of credit cards (19% market share as of July 2020) and credit card spends (~20% market share in 4MFY21). The company offers an extensive credit card portfolio to individual cardholders and corporate clients, which includes lifestyle, rewards, travel and fuel, shopping, banking partnership cards and corporate cards covering all major cardholder segments.
SBIC started its operations in 1998, and is a subsidiary of SBI, India’s largest commercial bank in terms of deposits, advances and number of branches as of September 30, 2019. SBIC has grown faster than the Indian credit card market over the past few years. Over FY2018-20, SBIC’ number of credit cards outstanding grew at a CAGR of ~32% (compared to industry average of ~25%). In the same period SBIC’ credit card spends grew at a robust pace of ~45% CAGR (compared to a 26% CAGR for the overall credit card industry).
SBIC only operates in the issuing side of the credit card value chain, unlike most of the other players in the industry who also have a merchant acquisition business. SBI (parent bank) runs the merchant PoS business through another subsidiary SBI Payments.
Exhibit 15: SBI Cards has consistently gained market share in cards and industry spends Key metrics for SBI Cards, March fiscal year-ends, 2013-1HFY21
2013 2014 2015 2016 2017 2018 2019 2020 1HFY21 Cards (# mn) 2.6 2.9 3.2 3.6 4.6 6.3 8.3 10.5 11.0 YoY (%) 11 10 15 26 37 32 28 21 Market share (%) 14 15 15 15 15 17 18 18 19 Spends (Rs bn) 113 163 209 287 429 765 1,032 1,308 487 YoY (%) 44 28 38 49 78 35 27 18 Market share (%) 9 11 11 12 13 17 17 18 20 Spend per card (Rs/year) 46,479 59,602 70,209 84,327 105,470 141,654 143,926 136,835 182,122 YoY (%) 28 18 20 25 34 2 (5) 41 Spend per transaction (Rs) 2,183 2,503 2,702 2,651 2,819 3,633 3,713 3,373 3,374 YoY (%) 15 8 (2) 6 29 2 (9) (7)
Source: RBI, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 11
Banks SBI Cards and Payment Services
Exhibit 16: SBIC growth metrics have been better than industry over the past few years 7Y and 3Y CAGR of key metrics for SBIC and industry, March fiscal year-ends, 2013-20 (%)
Source: RBI, Kotak Institutional Equities
Broad set of offerings across segments
SBIC offers a diverse and extensive portfolio of credit cards catering to individual cardholders and corporate clients and is categorized into lifestyle, rewards, travel and fuel, shopping, banking partnership cards and corporate credit cards. The company offers four SBI-branded credit cards each catering to a varying set of cardholder needs. The product suite caters to customer segments across segments including ‘premium’, ‘affluent’, ‘mass affluent’, ‘mass’ and ‘new to credit’ categories. Products are differentiated by customized benefits, such as reward programs and discount programs that are tailored for each target demographic and thus offer a higher value proposition. Premium cards, which comprise credit cards that have annual fee of Rs1,499 and above constituted 14% of the total card base, down from 16% in FY2017.
Co-brand partnerships – an attractive way to scale the business model
The credit cards offered through co-brand partnerships bear SBIC branding along with the co-brand partner’s banding. Under a typical co-brand arrangement, the partner agrees to promote the product to its customers while the company underwriting the credit cards controls credit criteria, and issues credit cards to eligible customers. The co-brand partners also provide space in their retail outlets for SBIC to market its products. The rewards/benefits of the co-brand cards are jointly built with the co-brand partner. This exclusive specialized benefit is a valuable way to source customers interested in a specific spend category. SBIC has one of the widest ranges of co-brand partners in the industry spanning multiple sectors (see exhibit 18 and 19).
Credit card spends from the company’s co-branded credit cards represented ~19% of total credit card spends in FY2019 (24% in 1HFY20). Newly sourced co-brand accounts represented ~30% of total new cards sourced in FY2019 (36% in 1HFY20).
Corporate cards – meaningful spend contribution
The company also offers multiple corporate cards to corporate clients that can be tailored for specific end-uses and functionalities. The company’s ability to provide such customized product offerings across multiple cardholder segments has helped build a broad customer base. Corporate cards accounted for ~25% of the total spends, despite constituting less than 1% of the card base.
12 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 17: Wide range of credit card offerings Credit card product offerings of SBIC
Credit card category Annual fees Description Card variants Personal cards Lifestyle cards Rs1,499 to Rs4,999 Targets cardholder segments with similar lifestyle interests SBI Card ELITE, SBI Card ELITE Advantage, Doctor's SBI Card Offers range of benefits such as gift vouchers and SBI Card PRIME, OLA Money SBI Card, Apollo SBI Card, SBI Card Rewards Rs499 to Rs2,999 accelerated reward points accruals PRIME Advantage, Tata Platinum Card, Tata Titanium Card
SimplyCLICK SBI Card, SimplySAVE SBI Card, fbb SBI STYLEUP Offers shopping vouchers and bonus rewards on certain Card, Central SBI Select+ Card, Central SBI Select Card, SBI Card Shopping Rs499 to Rs2,999 shopping categories Unnati, SimplyCLICK Advantage SBI Card, SimplySAVE Advantage SBI Card, Shaurya SBI Card
Etihad Guest SBI Premier Card, Etihad Guest SBI Card, BPCL SBI Offers special travel-related benefits such as complimentary Travel and fuel Rs499 to Rs4,999 Card, Yatra SBI Card, Air India SBI Signature Card, Air India SBI airport lounge access and fuel surcharge waivers Platinum Card, Chennai Metro SBI Card, IRCTC SBI Platinum Card
Co-brand partner banks: Allahabad Bank, Karnataka Bank, South Banking partnerships Rs499 to Rs4,999 Cards offered to customers of co-brand partner banks Indian Bank, Federal Bank, Karur Vysya Bank, Oriental Bank of Commerce, Bank of Maharashtra
SBI Card ELITE Business, SBI Card PRIME, Business and SBI Card Business NA Tailored for the needs of our SME clients Vyapar Unnati Corporate cards Tailored for expense management solutions for corporate General corporate Rs0 to Rs499 SBI Signature Corporate Card; SBI Platinum Corporate Card clients with large employee base. Tailored for bulk buying and inventory purchasing from Central travel account Rs0 to Rs499 SBI Central Travel Account Card airlines, hotels and travel consolidators. Provides functionality to make multiple utility bill payments Utility Rs0 to Rs499 (telecommunications, electricity, water, gas, etc.) in a single SBI Corporate Utility Card transaction Provides payment solutions for B2B vendor payments driving Corporate purchase Rs0 to Rs499 savings through extended payment terms. End user is the SBI Corporate Purchase Card procurement or finance team of corporate client
Source: Company
Exhibit 18: SBI Cards offers a wide array of co-branded credit cards Core and co-branded cards offered by SBI Cards
Source: Company
KOTAK INSTITUTIONAL EQUITIES RESEARCH 13
Banks SBI Cards and Payment Services
Profiling the business
The company has a diversified customer acquisition network, multiple channels and platforms. New customers are sourced broadly through (1) open market, (2) bank (SBI) and (3) corporate distribution channels. SBIC is one of the most prolific acquirers of customers with presence in over 3,400 open market points across India, including bank branches, retail shops, malls, fuel stations, railway stations, airports, corporate parks and offices of co-brand partners. The distribution is spread across 148 locations across India via various channels – banca, co-brand partners, point of sale distribution, tele-calling centres and digital medium.
Customer profile: shift towards lower age, self-employed, new to credit
SBIC customer acquisition has been shifting towards adding more self-employed customer base with its share at 21% of customer sourced in 1QFY21 leading to its share rising to 15% by FY2020 compared to 10% in FY2017 (Exhibit 19). This trend is playing out along with the broad industry (including SBIC) trend of shift towards smaller cities beyond metros and towards younger age cohorts (Exhibit 21 and 23). Consequently, the share of new-to-credit customers has also increased to 24% of total customers sourced in FY2019 were from the new-to-credit customer segment compared to 17% in FY2017 (Exhibit 22).
Exhibit 19: Increasing share of self-employed customers Exhibit 20: Premium cards form ~14% of overall card base Customer mix, March fiscal year-ends, 2017-1QFY21 (%) Proportion of premium cards outstanding, March fiscal year-ends, 2017-1HFY20 (%) Salaried Govt/PSU Cat A Cat B Self-employed 100 20 10 11 13 15 21 22 80 16 33 25 26 60 12 90 89 87 17 40 22 20
8 16 16 15 14 20 37 30 33 4 - 2017 2018 2019 2020 New New sourcingsourcing (1Q'21) (2Q'21) - Notes: 2017 2018 2019 1HFY20 (1) CAT A & B companies comprise renowned and listed private Notes: companies and mid and small size unlisted private and public (1) Premium cards are defined as products with an annual fee greater companies. than Rs1,499.
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
The company has developed models that more accurately estimate risk for new-to-credit and new-to-card cardholders without a credit history and intends to leverage this capability for sourcing customers from this segment. The company also plans to tap into the super- premium segment targeting a high-net-worth clientele, to benefit from higher spends that this customer segment is expected to generate. The share of premium cards, defined as credit cards with an annual fee greater then Rs1,499 were at 14% of the total card base as of 1HFY20, compared to 16% in FY2017 (Exhibit 20).
14 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 21: Increasing share of self-employed customers Exhibit 22: Increasing share of sourcing from the new-to-credit Age-wise customer mix; inner circle is outstanding as of June 2020 segment and outer circle is for March-June 2020 quarter (%) Share of new-to-credit in total number of credit cards sourced, March fiscal year-ends, 2017-19 (%)
30
Under 30, >45, 25% 24% 24 >45, 22% Under 30, 30% 18
12 24 31-45, 22 48% 17
31-45, 6 50%
- 2017 2018 2019 Source: Company, Kotak Institutional Equities
Source: Company, Kotak Institutional Equities
Exhibit 23: Increasing share of sourcing from outside the top eight cities New accounts sourced by geography, March fiscal year-ends, 2017-1HY20 (%)
Top eight metropolitan areas Tier II metropolitan areas Tier III metropolitan areas Others 100 4 10 14 26 26 80 13 19 14 14 19 60 18 18
40 67 54 20 43 42
- 2017 2018 2019 1HFY20
Source: Company, Kotak Institutional Equities
Open market source far more expensive but has much lower churn as well
Sourcing through the SBI bank channel has expanded over the past 3-4 years achieved through a joint initiative to push the product to SBI’s customers. This has led to nearly 50-50 mix of new customer sourcing between SBI and open market channels (see exhibit 24). However, on an outstanding basis, SBI’s share has remained ~40% over the past three years (Exhibit 25). Back-of-the-envelope calculations suggest fairly high churn rate of ~30% among SBI’s customers compared to <10% for the open market channel (see exhibit 26). This could probably indicate low activity levels leading to a dormant card which is subsequently cancelled.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 15
Banks SBI Cards and Payment Services
Exhibit 24: Fresh sourcing nearly equally split between bank and Exhibit 25: Open market sourcing continues to dominate cards open market sourcing outstanding Sourcing mix of new accounts, March fiscal year-ends, 2017-1FY21 Sourcing mix of cards in force, March fiscal year-ends, 2017-1HFY21 (%) (%)
Open market Bank (SBI) Open market Bank 100 100
33 80 36 80 38 38 38 38 46 50 55 57
60 60
40 40 64 67 62 62 62 62 54 51 20 45 43 20
- - 2017 2018 2019 2020 1HFY21 2017 2018 2019 2020 1HFY21
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 26: Bank channel exhibits higher churn based on back-of-the-envelope calculations Calculation of churn in cards, March fiscal year-ends, 2017-1HFY21
2017 2018 2019 2020 1HFY21 Cards in force (# mn) 4.6 6.3 8.3 10.5 11.0 New accounts (# mn) 1.2 2.5 2.8 3.4 1.0 % of opening cards 34 55 45 41 19 Reduction (# mn) 0.3 0.8 0.8 1.1 0.5 Reduction (% of opening cards) Open market channel 17 1 6 2 Banking channel 20 32 26 22 Overall 8 18 13 14 10
Source: Company, Kotak Institutional Equities
Exhibit 27: Open market is likely to be far more expensive acquisition channel versus banca KIE estimates of sourcing cost/card, March fiscal year-ends, 2017-20 (Rs)
7,000
5,600
4,200
2,800
1,400
- 2017 2018 2019 2020 Notes: (1) Above calculations are based on KIE assumptions. We include sales promotion and fees & commission expenses to calculate per card costs. (2) Sales promotion costs includes costs for open market acquisition, branch relationship executive costs, retail cash-backs, etc. (3) Fees & commissions include costs for corporate card passback, co-brand payouts, banca commissions, etc.
Source: Company, Kotak Institutional Equities
16 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Payback period per card is probably getting extended
Card business typically carries high operating expenses compared to other retail segments. While SBIC’ scale provides clear benefits such as ability to incur high marketing costs, distribute portfolio geographically, large part of the cost growth is variable and linked to growth in business (cards/spends). This is largely a function of high marketing costs (spreads over the card base), acquisition cost (varies with cards added), rewards and payment network costs (both vary with spends).
In the below matrix (see exhibit 28 and 29), we show the amount of spends and annual fee required to recover the customer acquisition cost across the range of inputs. Key assumption here is SBIC earns interchange fees of 1.5% and makes 0.4% provisions for rewards on total spends. Given that (1) average spend per card (adjusting for corporate cards) in FY2019-20 was around Rs100,000 and (2) average annual fee per card is ~Rs600, SBIC is probably not making gross profit on the card in the first year. Calculations don’t account for cost of funding interest-free period credit line as well as revolve-related interest income in the first year. There are a few more factors at play: Card churn: Attrition is also a crucial consideration for payback and for SBIC it has been closer to ~15%. Incremental cardholder is spending less: In line with trends across the industry, mix of new-to-credit or new-to-card and non-metro locations has been rising. This probably implies lower spend per card in the initial years whereas acquisition cost is relatively more inelastic.
Exhibit 28: Average card needs high spends in the first year to recover the sourcing cost Spends and annual fees required in the first year to recover sourcing costs (Rs)
Annual fee per card (Rs) Sourcing cost per card (Rs) 0 500 1500 3000 2000 180,000 140,000 50,000 - 3000 270,000 230,000 140,000 - 4000 360,000 320,000 230,000 90,000 5000 450,000 410,000 320,000 180,000
Notes: (1) We assume 1.1% as net spend-based fee adjusting for reward-based expense.
Source: Company, Kotak Institutional Equities
Exhibit 29: Card probably breaks even by the end of second year Hypothetical profitability model for a non-revolving card
Assumptions Year-1 Year-2 Year-3 Year-4 Year-5 Number of cards 15% churn 1.00 0.85 0.72 0.61 0.52 Acquisition cost/card 3,000 (3,000) ― ― ― ― Annual fee/card 1,000 1,000 925 786 668 568 Annual spend 15% growth 100,000 115,000 132,250 152,088 174,901
Interchange fees (% of spends) 1.5% 1,500 1,596 1,560 1,525 1,490 Reward (% of spends) 0.4% (400) (426) (416) (407) (397) Interest-free period cost 7.0% (583) (621) (607) (593) (580)
First year operating profit (1,483) 1,475 1,323 1,193 1,081 Cumulative (1,483) (9) 1,315 2,508 3,590
Source: Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 17
Banks SBI Cards and Payment Services
Robust growth in credit card spends
As we discussed in the section outlining credit card economics, credit card revenues are broadly categorized into (1) fee-based and (2) interest-based. SBIC’ revenue profile is diversified across these two heads. SBI’s topline growth performance has been noteworthy with revenues compounding at ~40% CAGR over FY2013-20. Growth has been quite balanced between net interest income (37% CAGR), core fee income (39%) and other miscellaneous income (~45% CAGR). Core fee-based revenues comprising interchange fees, annual subscription fees and instance-based fees is close to ~50% of overall revenues (see exhibit 31).
There is reasonably high correlation between the income and income drivers. Spend-based fee, i.e. interchange income, grows in line with spends whereas interest income grows in line with growth in loan book. This probably reflects lack of meaningful pricing pressure either on interchange or the interest rates (see exhibit 32 and 33).
Exhibit 30: Revenues have grown by ~40% CAGR over FY2013-20 Exhibit 31: Net interest income is ~40% of overall income Revenues and yoy growth, March fiscal year-ends, 2013-20 Revenue mix, March fiscal year-ends, 2018-20 (%)
Subscription-based fees Spend-based fees (Rs mn) Revenues YoY (RHS) (%) Instance-based fees NII 90,000 80 Other income 100 9 10 11 72,000 64 80
54,000 48 44 41 42 60 36,000 32 40 15 16 15 18,000 16 20 25 26 24 - - 7 7 8
-
2013 2014 2015 2017 2018 2019 2020 2016 2018 2019 2020
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 32: Fee income growth has strong correlation with spends Exhibit 33: NII growth correlates with loan growth growth Net interest income and loans, March fiscal year-ends, 2013-20 Fee income and spends, March fiscal year-ends, 2013-20 (Rs mn) NII (LHS) Loans (RHS) (Rs bn) (Rs mn) Core fees (LHS) Spends (RHS) (Rs bn) 40,000 250 45,000 1,400
32,000 200 36,000 1,120
24,000 150 27,000 840
16,000 100 18,000 560
8,000 50 9,000 280
- -
- -
2014 2016 2017 2018 2019 2020 2015
2013
2014 2015 2016 2017 2018 2019 2020 2013 Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
18 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Strong growth in receivables portfolio
Receivables or loans outstanding on balance sheet comprise unpaid dues from transactions as well as revolving balance or conversion of spends to installment loans. There could be a small share of balance transfer from other companies as well. In line with the market share in spends, SBIC also has the second highest loans book among card issuers in India.
Over FY2013-20, spends growth of ~40% CAGR has outpaced ~30% growth in loans reflecting increased use of credit cards for transactions rather than borrowing. We have seen a consistent decline in loans/spends ratio to 17% in FY2020 from ~30% in FY2013 (see exhibit 34 and 35). This trend is similar to trends we see with other issuers in India as well as some of the other countries such as the US.
Exhibit 34: ~40/30% CAGR growth in spends/loans since FY2013 Exhibit 35: Declining loans/spends ratio over the years Spends in the year and loan outstanding at year-end, March fiscal Loans to spend ratio, March fiscal year-ends, 2013-20 (%) year-ends, 2013-20 (Rs bn) 35 Spends Loans 1,400 1,308 29 27 27 28 26 24 1,120 1,032
21 18 17 17 840 765
14 560 429 287 7 228 280 209 179 163 140 113 103 44 57 74 33 - - 2013 2014 2015 2016 2017 2018 2019 2020 2013 2014 2015 2016 2017 2018 2019 2020 Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 36 shows the mix of receivables between the three categories of portfolio. As of FY2020, ~40% of the receivable was revolving in nature with the rest of the book nearly equally split between transactions and term loans. Since corporate card spends generally don’t revolve, adjusting for corporate receivables would lead to lower ratio of transactors book for retail cards. The term loan book has much lower interest rates compared to revolver but also has lower credit losses. We analyze the book by also looking at the distribution residual tenor based on maturity tables. As of FY2020, 27% of loan book has <1 month tenor, similar to the share of transactor book. On the other end, 11% of the book has more than 1 year duration (see exhibit 37). We are not sure if this is based on behavioral pattern or contractual, but probably higher duration loans could indicate conversion of larger spends to longer duration loans.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 19
Banks SBI Cards and Payment Services
Exhibit 36: Strong growth in credit card receivables Exhibit 37: Share of loans with >12 months duration has risen Credit card receivables, March fiscal year-ends, 2017-2QFY21 (%) Mix of credit card receivables, March fiscal year-ends, 2017-1HFY20 (%)
Term loan Revolver Transactor <1 month 1-2 months 2-3 months 3-6 months Restructured Revolve+Transact 6-12 months 1-3 years >5 years 100 9 100 8 8 6 9 11 11 28 25 80 17 16 16 12 11 12 30 80 68 18 17 71 71 21 21 20 22 60 60 40 45 11 12 10 11 11 34 13 40 40 17 16 16 17 16 14
20 20 32 29 29 32 30 27 28 28 29 32 32 27
0 - 2015 2016 2017 2018 2019 2020 2017 2018 2019 2020 1QFY21 2QFY20
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
For the limited historical data we have on the break-up of core fee income, we don’t see material change in any of the underlying drivers (see exhibit 38). The company is attempting to increase the share of fee paying cards and share of premium cards that earn annual/renewal fees. Interchange rates are set by payment networks and blended rates depend on number of factors such as type of card, merchant, spend category, etc. Payment networks also reward issuers with ‘business development incentives’ designed to build payments volume and increase product acceptance – this about ~15% of the interchange fees.
Instance-based fees primarily consist of a wide range of fees including fees for late payment, reward redemption, cash withdrawal, over limit, etc. This fee has been steady at ~Rs1,300 per card over the past three years.
Exhibit 38: Underlying revenue drivers have been stable reflecting resilient pricing/rates Key revenue items and underlying drivers, March fiscal year-ends, 2018-20 (Rs mn)
2018 2019 2020 Subscription based fees 3,255 4,353 6,493 per card (Rs) 600 610 680 Spend based fees 11,738 16,431 20,407 % of spends 1.54 1.59 1.56 Instance-based fees 6,779 9,937 12,886 per card (Rs) 1,260 1,390 1,350 Net interest income 20,524 25,664 35,404 % of receivables 16.9 16.1 17.4
Source: Company, Kotak Institutional Equities
Business has low operating leverage
Credit card business has high operating costs, large share of which is variable in nature. The business has strong dependence on third-parties for parts of the business such as customer acquisition, payment processing, fraud control, collections, logistics, etc. As a result, large part of cost base moves in line with business growth, especially spends (see exhibit 40).
Largest cost heads are sales promotion and fees & commission expenses together contributing 45% of non-interest costs (see exhibit 39). It includes acquisition cost for sourcing new accounts, cost of sales/engagement efforts such as promotional and cashback expenses. Employee cost contribution is lower as the company uses a large outsourced workforce to source business, with off-roll employees at close to 39,600 compared to 3,960 employees who are on-roll.
20 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Rewards and transaction charges at ~20% of non-staff costs are also linked to level of spends. Rewards cost is a provision for future rewards redemption (actuarially determined) and are influenced by the volume of cards eligible for rewards, the percentage of customers using up the reward points and claiming the rewards, the nature of tie-ups with the partners for redemption of rewards, and the effective cost per reward point. Transaction charges are paid to payment network for their services and are linked to transaction volumes.
Exhibit 39: Large share of costs are variable in nature Exhibit 40: Strong correlation between non-staff costs and spends Operating cost breakup, March fiscal year-ends, 2016-20 (%) Non-staff costs and spends, March fiscal year-ends, 2013-20
Others Collection & recovery (Rs mn) Non-staff costs Spends (RHS) (Rs bn) Rewards Transaction charges Processing charges Sales promotion, fees, commission 50,000 1,400 Employee Finance costs 100 40,000 1,120
80 30,000 840
60 20,000 560 40 10,000 280 20 - -
-
2015 2016 2017 2018 2019 2020 2014 2016 2017 2018 2019 2020 2013
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Ind-AS helps report better cost ratios
Over the FY2013-20 period, SBIC’ expense growth has been ~35% CAGR, compared to ~40% for spends and overall revenues. With a high share of fees income in the revenues, cost-income is probably a better representation than cost-assets. Cost-spends is also a useful measure given the strong correlation. Cost-income has seen a consistent decline over FY2017-20, reducing the cost-income by ~10 ppt. On spend basis as well, we see a sharp fall from FY2018 onwards. This is partly explained by shift to Ind-AS from FY2017 (se exhibit 41 and 42).
Exhibit 41: Decline in cost ratios over the past few years Exhibit 42: Sharp fall in cost-spends from FY2018 onwards Cost-income and cost-assets, March fiscal year-ends, 2013-20 (%) Cost-spends ratio, March fiscal year-ends, 2013-20 (%)
Cost-income Cost-assets (RHS) 5.0 80 25 4.7 70 67 66 67 63 4.6 64 61 60 23 57 4.3 4.2 4.2 4.2 22 4.2 48 21 21 21 3.8 20 32 19 3.8 3.7 3.7 19 19 16 18 17 3.4
- 15 3.0 2013 2014 2015 2016 2017 2018 2019 2020 2013 2014 2015 2016 2017 2018 2019 2020
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 21
Banks SBI Cards and Payment Services
Costs deferred over longer duration even as customer attrition is up
Ind-AS allows amortizing customer acquisition costs (CAC) over the behavioral life of the customer. This helps smoothen the cost of customer acquisition – capitalized costs have been ~10-20% of total non-interest costs during FY2017-20. However, this provides meaningful support to the PBT (~35% of PBT). Further, CAC is increasingly deferred over longer duration periods as seen from lower share of CAC amortizing in less than 12 months. (Exhibit 26). With the onset of the pandemic the monetization of CAC is probably right- shifted further.
Exhibit 43: Acquisition costs are deferred up to around 4 years Exhibit 44: Unamortized costs are ~15% of net worth Card acquisition costs capitalized during the year, March fiscal year- Unamortized card acquisition costs and as % of net worth, March ends, 2017-20 (Rs mn) fiscal year-ends, 2017-20
Unamortized CAC - realized >12 months 6,500 (Rs mn) Unamortized CAC - realized <12 months (%) % of net worth (RHS) 8,000 20 5,200
6,400 16 3,900 16 16 4,800 14 12
2,600 12 3,200 8
1,300 1,600 4
- - - 2017 2018 2019 2020 2017 2018 2019 2020
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Asset quality: Covid-led rise in stress loans and credit costs
Credit costs during the year are a better representation of asset quality for credit cards than period-end impaired loans. With ~90% of the book having duration of less than 12 months, write-offs are generally higher for impaired loans. SBIC has a policy to write off loans more than 191 days overdue. Credit costs have risen from FY2018 onwards, possibly driven by shift to Ind-AS accounting (see exhibit 46 and 47).
Post start of Covid, SBIC witnessed large rise in moratorium book during the regulatory dispensation, rising to ~30% levels in April-May before falling to 6% in June. The company had introduced an internal scheme ‘easy payment plan’ for cardholders to regularize their accounts by paying minimum dues. The outstanding loans under this scheme are <1% of loans as it requires higher payment upfront. The other scheme is RBI’s restructuring scheme which allows repayment schedule to be deferred by up to 24 months. SBIC came out with one and two year repayment plans at 14% and 16%, respectively. Around 9% of receivable book has utilized this scheme with large share comprising self-employed segment, which has been acquired through open market channel. Further, reported GNPL increased to 4.3% by 2QFY21 (7.5% ex impact of extended standstill).
Credit costs (see exhibit 45) have spiked as the company made provisions on the additional NPLs (including pro forma NPLs adjusting for extended standstill) to the extent of ~65% and 10% provisions on restructured loans. Retail unsecured is the largest segment in terms of breakup of the loan book (98-99% of total) on which the overall ECL has increased in FY2020, especially for Stage-2 loans, in anticipation of potential stress due to Covid.
22 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 45: Credit costs have risen recently, driven by provisions for Covid Absolute credit costs (excluding recoveries on write-offs) and % of loans, March fiscal year-ends, 2013- 2QFY21
(Rs mn) Credit costs % of loans (RHS) (%) 22,000 15.0 14.6
17,600 12.0
8.5 13,200 8.2 9.0
6.1 6.4 8,800 6.0 4.4 4.3 3.5 3.8 3.7
4,400 3.0
- - 2013 2014 2015 2016 2017 2018 2019 2020 1QFY21 2QFY21
Source: Company, Kotak Institutional Equities
Exhibit 46: SBIC has increased ECL provisions on the Stage-2 loans Stage-wise loans and provisions, March fiscal year-ends, 2017-2QFY21
2017 2018 2019 2020 1QFY21 2QFY21 Gross loans (Rs mn) 103,052 145,698 185,263 241,406 233,300 239,780 Stage-1 93,666 130,330 166,990 190,634 Stage-2 6,977 11,243 13,743 45,929 Stage-3 2,409 4,125 4,529 4,844 3,150 10,287 Mix (% of total) Stage-1 90.9 89.5 90.1 79.0 Stage-2 6.8 7.7 7.4 19.0 Stage-3 2.3 2.8 2.4 2.0 1.4 4.3 Provisions (Rs mn) 3,223 5,243 6,176 13,290 13,998 20,621 Stage-1 1,314 1,965 2,600 6,531 Stage-2 274 501 564 3,504 Stage-3 1,636 2,777 3,011 3,255 Provisions (% of loans) 3.1 3.6 3.3 5.5 6.0 8.6 Stage-1 1.4 1.5 1.6 3.4 Stage-2 3.9 4.5 4.1 7.6 Stage-3 67.9 67.3 66.5 67.2
Source: Company, Kotak Institutional Equities
Exhibit 47: Retail (unsecured) comprising ~98% of loans has seen rise in stage-2 ECL Absolute credit costs (excluding recoveries on write-offs) and % of loans, March fiscal year-ends, 2013- 1QFY21
2019 2020 Stage 1 Stage 2 Stage 3 Stage 1 Stage 2 Stage 3 Corporate - secured 0.0 0.0 0.0 0.0 0.0 0.0 Corporate - unsecured 0.2 0.2 0.0 1.1 15.1 100.0 Retail - secured 0.3 0.6 7.9 0.3 2.4 6.9 Retail - unsecured 1.6 4.1 66.7 3.5 7.6 67.3
Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 23
Banks SBI Cards and Payment Services
FINANCIALS: A LONG RUNWAY ON GROWTH AND BETTER EARNINGS PROSPECTS We expect SBIC to deliver best-in-class growth on revenues backed by strong profitability metrics. We build higher provisions for Covid-related impact but see this as a cyclical episode, which allows the company to filter the weaker customers out of its customer base. We expect the company to deliver 20% RoE and on the back of ~50% earnings CAGR with strong growth in earnings led by lower provisions in the near term. We expect credit costs to move closer to pre-Covid levels by FY2023.
Return ratios to remain closer to the best-in-class players
We expect return ratios to normalize by FY2022-23E as it moves closer to 23-25% levels (see exhibit 48). We expect earnings growth of ~50% CAGR (see exhibit 49) largely on the back of normalization of credit costs and recovery in business momentum that has slowed in FY2021 as SBIC is working through the challenges caused by Covid on its existing portfolio while business momentum slowed as fresh card issuances dropped sharply immediately post Covid and is gradually gaining momentum. We see Covid as a positive impact for the sector and for the leading card issuers as it is giving a strong tailwind for customers to adopt the digital payment platform.
Exhibit 48: Return ratios have been healthy at 23-25% levels Exhibit 49: PAT expected to more than double by 2023 RoE and RoA, March fiscal year-ends, 2013-24E (%) PAT and growth yoy, March fiscal year-ends, 2013-24E (Rs bn, %)
RoE RoA (RHS) PAT PAT growth yoy (RHS) 50 7.5 40 120
40 6.0 32 90
30 4.5 24 60
20 3.0 16 30
10 1.5 8 0
0 - 0 (30)
2013 2014 2015 2016 2017 2018 2020 2019
2013 2014 2016 2017 2018 2020 2015 2019
2021E 2022E 2024E 2023E
2021E 2022E 2024E 2023E
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 50 shows the earnings decomposition based on assets which is the traditional way of looking at lending institution. The metrics that we see is relatively high as compared to all the traditional lending products. This business delivers higher NIM and higher fees. It also has a high cost structure and high provisions. An alternative way is to look at the earnings decomposition through a per card metrics basis (see exhibit 51). We are building a thesis that the earnings growth is being delivered through strong revenue growth as well as growth on a per card basis.
24 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 50: We are building modest assumptions in growth in per-card profitability Per-Card revenue metrics, March fiscal year-ends, 2014-23E (%)
2014 2015 2016 2017 2018 2019 2020 2021E 2022E 2023E Net interest income 13.4 12.9 13.4 13.2 15.5 14.4 15.6 15.4 14.7 15.6 Non-interest income 16.1 15.1 15.8 17.1 19.8 20.8 21.6 18.0 21.3 22.1 Total income 29.5 28.0 29.3 30.3 35.3 35.1 37.2 33.4 36.0 37.7 Operating expenses 18.0 18.7 19.2 20.2 22.3 21.2 21.0 16.4 21.3 22.5 Staff costs 1.3 1.1 1.1 1.1 1.4 2.1 2.1 1.8 1.9 1.8 Operating and other expenses 16.7 17.5 18.0 19.0 20.7 18.7 18.4 14.2 18.9 20.2 Sales promotion 3.6 5.1 5.2 6.8 9.2 9.3 Processing charges 6.4 5.7 5.6 4.9 3.3 - Reward point redemption 1.2 1.7 2.2 2.4 2.3 2.3 Card transaction charges 1.4 1.3 1.4 1.5 1.6 1.7 Collection charges 1.2 1.3 1.2 1.1 1.1 1.1 Other costs 0.0 0.1 0.1 0.1 0.2 0.4 0.5 0.4 0.5 0.5 Pre-provisioning operating profit 11.5 9.2 10.1 10.1 13.0 13.9 16.1 17.0 14.7 15.2 Provisions 4.4 4.3 3.8 3.7 6.1 6.4 8.5 10.8 6.8 6.0 PBT 7.1 5.0 6.2 6.4 7.0 7.5 7.6 6.2 7.9 9.2 PAT 7.1 4.9 4.0 4.2 4.6 4.8 5.5 4.6 5.9 6.9 Leverage 6.9 6.4 6.6 7.2 6.9 6.0 5.1 4.6 4.4 4.2 RoE 48.9 31.2 26.8 30.0 31.7 29.1 27.9 21.1 25.6 28.8
Source: Company, Kotak Institutional Equities estimates
Exhibit 51: We are building modest assumptions in growth in per-card profitability Per-card revenue metrics, March fiscal year-ends, 2014-23E (Rs)
2014 2015 2016 2017 2018 2019 2020 2021E 2022E 2023E Spend/card/year 65,326 80,000 95,879 105,684 140,865 142,140 139,138 93,733 127,680 129,225 Interest income 3,155 3,596 4,072 4,301 5,083 4,922 5,145 4,699 4,282 4,342 Finance costs 1,124 1,255 1,286 1,285 1,303 1,389 1,383 975 885 858 Net interest income 2,031 2,341 2,786 3,016 3,780 3,532 3,763 3,724 3,397 3,484 Non-interest income 2,444 2,731 3,279 3,883 4,807 5,108 5,219 4,359 4,945 4,933 Membership fees and services 2,084 2,309 2,755 3,208 4,010 4,229 4,229 3,739 4,108 4,125 Service charges 42 50 65 130 147 173 125 94 128 129 Business development incentive 63 91 148 241 300 298 348 187 319 323 Insurance commission - - - - 13 12 12 10 10 9 Others 6 8 27 8 18 47 180 44 43 39 Total revenue 4,475 5,072 6,065 6,898 8,587 8,641 8,982 8,083 8,342 8,417 Expenses 2,731 3,397 3,981 4,594 5,415 5,223 5,081 3,972 4,932 5,026 Provisions 664 776 791 849 1,472 1,580 2,062 2,621 1,579 1,333 PBT 1,080 899 1,293 1,456 1,700 1,838 1,838 1,490 1,831 2,059 PAT 1,080 886 837 950 1,112 1,190 1,323 1,109 1,362 1,532
Source: Company, Kotak Institutional Equities estimates
Solid revenue growth with a tight balance between various revenue streams
We are building ~25% CAGR in revenue growth for FY2020-24E on the back of 25% CAGR in NII growth and ~25% CAGR in non-interest income (see exhibit 52). We expect normalization in revenue composition between NII and non-interest income by FY2022 (see exhibit 53). The sharp decline in spends and a largely unchanged trajectory on NII given that existing customers have chosen to convert their revolve position to an interest paying product through restructuring or some form of easy repayment plan implies FY2021 would see a much higher contribution of NII. Also, FY2021 would see lower spend-related fees along with relatively lower-than-historical fee trends on other line items like late fees, over- limit fees, etc. We are building a recovery in spends in FY2022 (see exhibit 54) and a largely unchanged loan mix (see exhibit 55).
KOTAK INSTITUTIONAL EQUITIES RESEARCH 25
Banks SBI Cards and Payment Services
Exhibit 52: Revenue growth to recover by 2022 Exhibit 53: Contribution of non-interest income to revenue has Breakup of revenue, March fiscal year-ends, 2013-24E (Rs bn) increased marginally since 2013 Breakup of revenue, March fiscal year-ends, 2013-24E (%) Non-interest income Net interest income Revenue growth yoy (RHS) Net interest income Non interest income 100 200 68
160 51 80 54 55 54 54 56 56 59 58 54 59 59 58 120 34 60
80 17 40
40 0 46 20 46 45 46 44 44 41 42 46 41 41 42
0 (17)
0
2013 2014 2015 2017 2018 2020 2016 2019
2021E 2023E 2024E
2022E
2013 2015 2016 2018 2019 2014 2017 2020
2022E 2023E 2024E 2021E Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 54: Growth in spends has moderated but still solid Exhibit 55: Share of revolver balances increased in 2020 Growth in loans and spends, March fiscal year-ends, 2014–24E (%) Breakup of loan balances, March fiscal year-ends, 2017-24E (%)
Loans Spends Term Revolver Transactor 80 100 17 23 24 26 31 27 27 27 60 80
40 60 51 45 47 46 40 45 45 45 20 40
0 20 32 29 29 32 29 28 28 28
(20) 0
2014 2015 2016 2017 2018 2019 2020
2017 2018 2019 2020
2021E 2022E 2023E 2024E
2021E 2022E 2023E 2024E
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
Exhibit 56 shows a broad assumption for the credit card industry and SBIC. We are broadly looking at the credit bureau data and see a fairly long opportunity for all players. We are building 25% growth in overall spends during FY2020-25 followed by ~15% growth for FY2025-30 and 10% CAGR for FY2030-35. We are building card growth at 20% in the high growth and ~10% during the moderate period. We see individuals to have 1.8X credit cards per person largely on account of their association with another primary card and followed by another card, which usually tends to be a co-branded card. Even under these conservative estimates, we see that the penetration to the overall bureau would be ~35%.
26 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 56: We see a strong growth for the credit card industry in the medium term Assumptions for the credit card industry, March fiscal year-ends, 2017-35
High growth Moderate growth Slower growth 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 Bureau records of clients 220 231 243 255 267 281 295 310 325 341 358 376 395 415 436 457 480 YoY growth (%) 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 Credit cardholders 26 32 34 43 53 64 76 85 94 102 111 120 130 140 152 164 172 YoY growth (%) 26 23 5 28 24 21 19 11 11 9 9 8 8 8 8 8 5 Penetration (%) 12 14 14 17 20 23 26 27 29 30 31 32 33 34 35 36 36 Cards in force 47 58 61 77 96 116 138 153 169 184 199 216 234 253 274 296 311 YoY growth (%) 26 23 5 28 24 21 19 11 11 9 9 8 8 8 8 8 5 Cards per person (X) 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 SBI Cards (mn) 8 11 12 16 20 26 31 34 39 42 46 51 55 60 66 72 76 YoY growth (%) 32 28 14 30 29 28 20 12 12 10 10 9 9 9 9 9 6 Market share (%) 18 18 20 20 21 22 22 23 23 23 23 23 24 24 24 24 25 Spends (Rs bn) 6,033 7,322 6,035 8,800 12,145 16,315 21,487 25,857 30,113 34,668 39,523 45,009 50,229 56,001 62,380 69,427 76,121 YoY growth (%) 31 21 (18) 46 38 34 32 20 16 15 14 14 12 11 11 11 10 PFCE (Rs bn) 113,059 123,186 135,505 149,055 163,961 180,357 198,393 218,232 240,055 264,061 290,467 319,514 351,465 386,611 425,273 467,800 514,580 YoY growth (%) 11 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 Spends/PFCE (%) 5 6 4 6 7 9 11 12 13 13 14 14 14 14 15 15 15 SBI Cards (Rs bn) 1,033 1,309 1,056 1,764 2,311 3,007 3,692 4,249 4,876 5,492 6,180 6,946 7,801 8,752 9,811 10,990 11,979 Market share (%) 17 18 17 20 19 18 17 16 16 16 16 15 16 16 16 16 16 Spend/card (Rs '000) 143 140 102 127 140 154 170 178 187 196 206 217 223 230 237 244 251 YoY growth (%) 5 (2) (27) 25 10 10 10 5 5 5 5 5 3 3 3 3 3 Credit card dues (Rs bn) 1,198 1,467 1,209 1,763 2,434 3,269 4,306 5,181 6,034 6,947 7,920 9,019 10,065 11,222 12,500 13,912 15,254 Loans/spends (%) 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20
Source: Kotak Institutional Equities
Credit card is a high-margin product and exhibits stickiness of interest rates
Unlike other lending products, the yield on the loan book is quite sticky. It is insensitive to interest rates and the calculated yield changes essentially reflect the changes to the receivable book. Note that the ‘transactor’ does not pay any interest and conversely enjoys 15-30 days of interest free period for the transaction made. On the other hand, a revolver pays 35-40% interest rate while the book under term financing (EMI products) pays 12-20% based on the nature of the transaction. The mix defines the lending yield for SBIC.
On the other hand, SBIC enjoys a superior liability franchise given its ownership structure. This leads to healthy NIM which leads to better return ratios and allows the company to take a marginally higher risk on the asset side of the balance sheet. The only risk is that a higher share of book originated through the SBI channel could lead to lower revolvers and higher transactors. We shall have to work on this as we see this develop between the two partners.
Exhibit 57: Yields are insensitive to funding costs Exhibit 58: Superior NIM led by high yield and low funding costs Margin metrics, March fiscal year-ends, 2014-24E (%) NIM, March fiscal year-ends, 2014-24E (%)
Yield on loan receivables Cost of funds 20 25
15.5 15.6 15.4 15.6 15.8 16 14.7 20 14.4 13.4 12.9 13.4 13.2 12 15
10 8
4 5 10 9 8 7 7 8 8 6 6 6 6 22 21 21 20 23 22 24 22 20 21 21
0 0
2015 2016 2017 2018 2019 2020 2014
2014 2015 2016 2017 2018 2019 2020
2021E 2022E 2023E 2024E
2022E 2023E 2024E 2021E
Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 27
Banks SBI Cards and Payment Services
There is a lower operating leverage and a high cost structure
The card business operates at a high cost structure as that is the nature of this business (see exhibit 59 and 60). We are building operating expenses to grow at 40% CAGR for FY2021- 23E partly on the back of (1) lower base of FY2021 as the acquisition cost as well as the marketing costs is quite low and (2) cost growth would normalize. We don’t see too much of an operating leverage in this model. The three primary costs are essentially marketing costs related to acquisition, activation which includes the reward costs and the regular business overheads.
Exhibit 59: SBIC would have a high cost-income ratio Exhibit 60: SBIC cost-assets would be >20% levels Cost-income ratio for SBIC, March fiscal year-ends, 2014-24E (%) Cost-assets ratio for SBIC, March fiscal year-ends, 2014-24E (%)
80 25
64 20
48 15
32 10
16 5
0 0
2015 2016 2018 2019 2020 2014 2017
2014 2015 2017 2018 2019 2016 2020
2022E 2023E 2021E 2024E
2021E 2022E 2024E 2023E
Source: Company, Kotak Institutional Equities estimates Source: Company, Kotak Institutional Equities estimates
Loan-loss provisions to remain on the higher side
Given the short duration of this business, we note that the loan-loss provisions would be a better indicator of the earnings stress while write-offs would be a better indicator of the balance sheet stress. We are building higher provisions for SBIC for FY2021-22 given that the stress is currently getting reflected through the restructured loan portfolio or the easy repayment plan (see exhibit 61).
Exhibit 61: Expect provisions to be high for FY2021 and steadily decline by FY2024 Loan-loss provisions, March fiscal year-ends, 2014-24E (%)
13.0 12.0
10.4 9.5
7.5 7.8 7.2 6.6 6.5 5.8 5.2 4.7 4.6 4.1 3.9
2.6
0.0
2014 2015 2017 2018 2016 2019 2020
2021E 2024E 2023E 2022E
Source: Company, Kotak Institutional Equities
28 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 62: SBIC – key financial ratios and growth rates March fiscal year-ends, 2016-24E (%)
2016 2017 2018 2019 2020 2021E 2022E 2023E 2024E Growth rates (%) Net loans 29.2 38.9 36.7 27.5 27.4 15.7 20.2 31.0 30.1 Cash and bank balance 31.1 3.1 67.1 64.3 (13.0) 10.0 10.0 10.0 10.0 Total financial assets 29.8 37.8 38.7 28.6 25.0 15.5 19.8 30.3 29.5 Total non-financial assets (33.0) 19.0 375.7 41.7 35.8 10.8 14.6 14.8 15.0 Total assets 27.6 37.4 43.9 29.3 25.6 15.2 19.5 29.4 28.8 Borrowings 61.9 (93.1) 3,651.7 12.5 26.1 17.4 24.8 43.7 38.4 Debt securities 4.9 160.2 (63.4) 38.3 39.4 10.0 10.0 10.0 10.0 Net interest income 34.1 31.2 65.6 25.0 38.0 18.5 11.8 32.8 30.5 Total other income 35.2 43.6 63.6 42.2 32.3 0.0 39.1 29.2 28.9 Fee income 34.4 41.2 65.2 41.1 29.5 5.9 34.7 30.0 28.9 Spend based fees 40.0 24.2 (19.3) 67.0 31.0 30.1 Instance based fees 46.6 29.7 39.9 7.3 29.5 28.0 Subscription based fees 33.7 49.2 17.6 29.8 28.3 27.2 Operating expenses 32.0 39.9 55.8 29.0 26.0 (6.4) 52.2 31.9 32.0 Employee expenses 27.4 27.8 88.0 99.3 23.6 7.1 21.0 21.0 21.0 Pre-provisioning operating profits 40.1 34.1 81.8 44.2 47.8 26.2 1.7 28.8 25.9 Impairment losses and others 14.8 30.0 129.1 43.6 69.0 52.2 (26.2) 9.3 15.5 PBT 61.9 36.6 54.2 44.6 29.6 (2.9) 50.6 45.6 32.6 PAT 6.5 37.5 54.6 43.3 43.9 0.4 50.6 45.6 32.6 Key ratios (%) Yield on average loan receivables 21.0 20.0 22.7 22.4 23.8 21.5 20.3 21.2 21.2 Cost of funds 8.2 7.5 7.2 8.1 8.4 5.9 5.7 5.7 5.7 Net interest margin 13.4 13.2 15.5 14.4 15.6 15.4 14.7 15.6 15.8 Spreads on loans 12.8 12.6 15.5 14.3 15.4 15.6 14.7 15.5 15.5 Loan loss provisions/average loans 3.9 3.8 6.6 6.4 9.5 12.0 7.5 6.5 5.8 Loans-to-borrowings 124.7 124.6 124.3 132.2 131.4 133.7 135.6 135.2 135.4 Tax rate 35.2 34.8 34.6 35.2 28.0 25.6 25.6 25.6 25.6 Dividend payout ratio 27.7 20.1 — 9.7 7.5 — — — — Net interest income/total income 45.9 43.7 44.0 40.9 41.9 46.1 40.7 41.4 41.7 Non-interest income/total income 54.1 56.3 56.0 59.1 58.1 53.9 59.3 58.6 58.3 Fee income to total income 84.0 82.6 83.4 82.8 81.0 85.8 83.1 83.6 83.6 Cost-income 65.6 66.6 63.1 60.4 56.6 49.1 59.1 59.7 60.9 Operating expenses/assets 19.2 20.2 22.3 21.2 21.0 16.4 21.3 22.5 23.0 Contribution of net interest income to total income 45.9 43.7 44.0 40.9 41.9 46.1 40.7 41.4 41.7 Contribution of non interest income to total income 54.1 56.3 56.0 59.1 58.1 53.9 59.3 58.6 58.3 Per card metrics (Rs) Spend/card/year 95,879 105,684 140,865 142,140 139,138 93,733 127,680 129,225 131,301 Interest income 4,072 4,301 5,083 4,922 5,145 4,699 4,282 4,342 4,426 Finance costs 1,286 1,285 1,303 1,389 1,383 975 885 858 875 Net interest income 2,786 3,016 3,780 3,532 3,763 3,724 3,397 3,484 3,551 Non-interest income 3,279 3,883 4,807 5,108 5,219 4,359 4,945 4,933 4,965 Fee income 2,755 3,208 4,010 4,229 4,229 3,739 4,108 4,125 4,153 Total revenue 6,065 6,898 8,587 8,641 8,982 8,083 8,342 8,417 8,516 Expenses 3,981 4,594 5,415 5,223 5,081 3,972 4,932 5,026 5,183 Provisions 791 849 1,472 1,580 2,062 2,621 1,579 1,333 1,202 PBT 1,293 1,456 1,700 1,838 1,838 1,490 1,831 2,059 2,132 PAT 837 950 1,112 1,190 1,323 1,109 1,362 1,532 1,586 DuPont Analysis Net interest income 13.4 13.2 15.5 14.4 15.6 15.4 14.7 15.6 15.8 Non-interest income 15.8 17.1 19.8 20.8 21.6 18.0 21.3 22.1 22.0 Total income 29.3 30.3 35.3 35.1 37.2 33.4 36.0 37.7 37.8 Operating expenses 19.2 20.2 22.3 21.2 21.0 16.4 21.3 22.5 23.0 Provisions 3.8 3.7 6.1 6.4 8.5 10.8 6.8 6.0 5.3 PBT 6.2 6.4 7.0 7.5 7.6 6.2 7.9 9.2 9.5 PAT 4.0 4.2 4.6 4.8 5.5 4.6 5.9 6.9 7.0 Leverage 6.6 7.2 6.9 6.0 5.1 4.6 4.4 4.2 4.1 RoE 26.8 30.0 31.7 29.1 27.9 21.1 25.6 28.8 29.0
Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 29
Banks SBI Cards and Payment Services
Exhibit 63: SBIC – key financials March fiscal year-ends, 2016-24E (Rs mn)
2016 2017 2018 2019 2020 2021E 2022E 2023E 2024E Income statement Interest income 13,803 17,677 27,600 35,757 48,413 52,941 59,148 77,665 101,362 Finance costs 4,358 5,283 7,076 10,094 13,009 10,980 12,229 15,351 20,041 Interest on borrowings 162 157 901 4,280 5,608 — — — — Interest on debt securities 4,196 5,126 5,143 3,515 5,507 — — — — Net interest income 9,445 12,394 20,524 25,664 35,404 41,961 46,919 62,314 81,321 Non-interest income 11,114 15,959 26,102 37,110 49,104 49,106 68,302 88,232 113,708 Income from membership fees and services 9,340 13,183 21,773 30,720 39,787 42,126 56,742 73,779 95,108 Subscription based fees — — 3,255 4,353 6,493 7,637 9,912 12,713 16,174 Spend based fees — — 11,738 16,431 20,407 16,462 27,492 36,027 46,872 Instance-based fees — — 6,779 9,937 12,886 18,027 19,338 25,039 32,061 Net revenues 20,560 28,353 46,626 62,774 84,508 91,067 115,222 150,547 195,029 Expenses 13,496 18,879 29,406 37,947 47,809 44,748 68,124 89,886 118,686 Employee benefit expenses 792 1,011 1,902 3,789 4,684 5,015 6,068 7,342 8,884 Operating and other expenses 12,649 17,787 27,272 33,463 41,888 38,544 60,529 80,604 107,353 Sales promotion 3,623 6,400 12,146 16,552 — — — — — Reward point redemption 1,581 2,250 3,016 4,131 — — — — — Pre-provisioning operating profits 7,064 9,473 17,221 24,827 36,699 46,319 47,098 60,660 76,343 Impairment losses and others 2,682 3,488 7,990 11,477 19,402 29,528 21,805 23,838 27,521 Profit before tax 4,382 5,985 9,230 13,350 17,296 16,791 25,293 36,823 48,821 Tax 1,543 2,081 3,195 4,701 4,848 4,299 6,475 9,427 12,498 PAT 2,839 3,905 6,036 8,649 12,448 12,493 18,818 27,396 36,323 Tax rate (%) 35 35 35 35 28 26 26 26 26 EPS (Rs) 4 5 8 10 13 13 20 29 39 EPS growth (%) 6 38 55 43 44 0 51 46 33
Balance sheet Assets Financial assets 77,391 106,609 147,829 190,124 237,641 274,493 328,978 428,692 555,191 Cash and cash equivalents 2,744 2,829 3,119 7,335 5,151 5,666 6,233 6,856 7,542 Bank balances — — 1,608 433 1,609 1,770 1,947 2,142 2,356 Loans 73,956 102,760 140,455 179,087 228,116 264,016 317,453 416,015 541,246 Non Financial assets 1,413 1,681 7,997 11,335 15,387 17,047 19,531 22,412 25,773 Total assets 78,803 108,291 155,826 201,459 253,028 291,540 348,509 451,104 580,963
Liabilities Financial liabilities 61,419 85,685 124,813 152,817 187,655 213,605 251,792 327,167 421,058 Debt securities 30,947 80,518 29,489 40,793 56,854 62,540 68,794 75,673 83,241 Commercial paper 27,536 75,107 23,391 21,198 25,420 — — — — Debentures 3,411 5,412 6,098 19,595 31,435 — — — — Borrowings 28,340 1,961 73,570 82,733 104,328 122,521 152,846 219,573 303,951 From SBI 28,334 1,953 63,303 73,726 83,564 — — — — Non-Financial liabilities 5,833 8,097 7,445 12,767 11,961 13,157 14,473 15,920 17,512 Provisions 4,238 5,788 3,924 6,284 6,026 6,629 7,292 8,021 8,823 Reward points 1,532 2,301 3,163 4,464 4,059 — — — — Standard assets 290 404 — — — — — — — Doubtful assets 369 436 — — — — — — — Expenses 1,000 1,536 202 724 1,213 — — — — Other non-financial liabilities 1,595 2,309 3,417 5,721 5,935 6,528 7,181 7,899 8,689 Unamortised membership fees and subvention income 841 1,282 1,798 2,627 3,324 — — — — Total liabilities 67,253 93,782 132,258 165,584 199,616 226,762 266,265 343,087 438,570 Equity 11,550 14,509 23,569 35,878 53,412 64,778 82,244 108,017 142,394 Share capital 7,850 7,850 7,850 8,372 9,390 9,390 9,390 9,390 9,390 Reserves and surplus 3,700 6,659 15,719 27,506 44,023 55,389 72,854 98,628 133,004 Total liabilities + Shareholder's equity 78,803 108,291 155,826 201,462 253,028 291,540 348,509 451,104 580,963
Source: Company, Kotak Institutional Equities
30 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
KEY RISKS: A FEW MACRO AND MICRO There are two broad risks that we see in SBIC. On the macro side, India is still evolving on digital adoption and credit cards are one of the many payment products. The two distinct functions of payment and credit can be disrupted by any of the new or existing payment products. On the micro side, it is a high-risk business that needs constant investment in capabilities. Association with SBI is crucial to reduce the risk of originating weaker credit profiles and lower the cost of acquisition. Volatile RoEs, even if superior across the cycle can lower the multiples as the business achieves some degree of scale.
Two broad risk frameworks: controllable and non-controllable
We have discussed the risks in various sections of this note. The macro side where we discuss the risks emerging from non-controllable factors and the micro which is more specific to SBIC. SBIC has delivered profitability over the past few years but changing customer landscape remains crucial alongside competitive environment. A few key risks that may affect the business include: (1) changes to macroeconomic condition and consumer behavior, (2) change in nature of relationship with SBI, (3) competition from other credit card issuers and (4) failure in implementing growth strategy or managing funding and liquidity risks. While SBIC is well placed in the overall ecosystem, possible disruptions from other players or regulator can act as hurdles.
Asian boom-bust cycles give insights into potential risks in the business
Study of research on previous credit card distresses throws some light on what typically drives the boom-bust cycles in this business. While several Asian countries saw credit card balances grow quite strongly during the 2000-2006 period, credit card cycles in three countries – Korea, Hong Kong and Taiwan – stand out for their more severe boom-bust cycles (link to research). There are a few common characteristics that authors point out that drove this: (1) excessive competition in the high-yield, less prime, credit card lending business leading to relaxed lending standards, (2) which leads to rising indebtedness for households especially in the riskier cardholders, (3) followed by sudden deterioration in asset quality leading to significant and prolonged contraction in card receivables. There is a marked increase in credit card debt compared to the total loans and as a share of GDP (see exhibit 64).
Exhibit 64: High exposure to credit cards in countries that went through the crisis Credit card balances outstanding in Asia measured in 2005 US$ (end 2005)
Per capita % of total loans % of retail loans % of GDP Korea 675 5.5 11.0 4.2 Korea (2002) 2,006 21.3 45.1 14.7 Taiwan (1) 1,369 6.7 14.9 8.8 Hong Kong 1,181 3.3 8.2 4.6 China 2 0.1 0.7 0.1 India 3 0.9 3.6 0.4 Malaysia 168 3.0 6.1 3.4 Philippines 18 3.5 34.6 1.5 Singapore 379 1.5 2.9 1.4 Thailand 59 2.5 14.0 2.0 Japan3 527 1.8 6.6 1.6 Memo: United States (2) 2,854 10.5 37.0 6.8 Notes: (1) Includes cash card balances. (2) Household loans do not include mortgages.
Source: BIS research paper
KOTAK INSTITUTIONAL EQUITIES RESEARCH 31
Banks SBI Cards and Payment Services
The unfolding the crisis follows a similar cycle that we see in most lending products
Lack of growth in other lending segments. Episodes of strong growth in credit card portfolios (see exhibit 65) followed the weak demand for corporate credit, ample liquidity and low interest rates following the Asian financial crisis. This incentivized the banking system in some parts to take excessive exposure and risks to this segment. For example, Korean commercial banks financed their own credit card business as well as acted as funding sources to the dominant monoline credit card issuers. Search for yields led to households, mutual/pension funds and insurance companies having outsized exposure to underlying securities of credit card companies. In Hong Kong, low demand for mortgages in the depressed real-estate market (~30% of the total local loan book) forced banks to seek out alternative drivers of growth. In Taiwan, a banking system flush with liquidity and excess reserves of ~20% of deposits drove growth.
New entrants relaxed lending standards. Financial liberalization in these economies invited new players (sometimes inexperienced). While the new players expanded the market with more relaxed lending standards, it forced a response from incumbents as well leading to relaxed screening and underwriting standards. For example, in Hong Kong and Taiwan, new entrants went after the under-served consumer lending segments. In Korea, tax incentives for consumers and merchants to promote the use of credit cards led to some chaebols, with limited experience capturing nearly three-fourth of the market by 2002.
Super-normal return profile. The combined impact of intense competition, entry of new players and high return profile of the product led to card issuers aggressively growing this book at a much faster pace. Like other lending products, default rates were low in the initial period, thus, boosting the return profile on the portfolio even higher. In Korea, cash advance fees and interest charges crossed 20%, compared to unsecured personal loan rates of 6–7%. During boom period, the share of cash lending in total credit card assets was nearly 65% leading to super-normal RoEs of 40% (~6X of banking system average). During peak time in Taiwan, interest earnings and fees related to cash advances was 5X the fees from MDR.
Information asymmetry issues: Similar to India, the infrastructure to support reporting and sharing of credit information was less developed in countries such as HK and Taiwan in terms of reporting lenders, borrower coverage and type of data shared. Korea, on the other hand, saw the government erase about half of the available personal delinquency records (as a relief to soften the impact of Asian financial crisis), making it difficult to underwrite the product. Taiwan, despite having a sophisticated credit bureau system, witnessed an unhealthy behavior as card issuers nudged delinquent borrowers to transfer their loans to new card issuers to repay existing debts without getting reported to credit bureaus. Some markets like Taiwan also saw ‘credit card brokers’ cropping up, helping risky customers get access to the product for a fee and bypass credit reporting requirements.
Exhibit 65: Wide swings in growth rates during and after the crisis Annual growth of total credit card receivables, 1999-2000 (%)
Hong Kong Korea Malaysia Philippines Singapore Taiwan Thailand 1999 7.2 42.9 51.3 n.a. 23.2 27.4 (25.2) 2000 30.1 78.0 33.2 n.a. 25.8 40.9 (3.4) 2001 22.9 122.8 20.9 3.0 21.8 31.6 26.3 2002 (9.6) 39.3 19.5 13.8 15.5 32.4 76.7 2003 ― (45.2) 15.5 8.9 4.4 32.4 30.1 2004 7.8 (34.9) 16.4 17.4 3.0 29.7 25.6 2005 9.5 (5.7) 17.3 19.6 3.4 17.6 21.1
2006 13.3 5.8 19.0 20.3 2.4 (30.7) 19.2
Source: BIS research paper
32 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
How did the crisis unfold?
Unwinding of the cycle. Similar to a typical lending boom, the cycle continued through (1) increased credit limits, (2) adding multiple cards, (3) re-aging (i.e. ever-greening) of loans, etc. As the cycle extended itself, overstretched borrowers started hitting limits. Further, as portfolios seasoned, delinquencies and charge-offs started spiking. Card issuers, sensing trouble, started cutting back card limits especially for riskier customers and sometimes even for better quality customers. With funding lines closed, defaulting customers caused heavy losses on the book and with no growth the portfolios shrunk sharply and return ratios swiftly collapsed.
. Impaired asset ratios in Korea and Taiwan touched ~25% at their peak of the down cycle. In a couple of years post the peak of the cycle, credit card receivables fell by 65% in Korea, ~30% in Taiwan and ~10% in Hong Kong.
Regulators stepped in with tighter rules. Initial policy response from authorities and regulators was to tighten regulations. These steps included establishment of inclusive credit reference agencies, stronger write-off and disclosure requirements. For example, in Korea the regulators (1) upgraded credit card asset classification standards, (2) strengthened provision requirements, (3) applied prompt corrective action to standalone card issuers and (4) raised the minimum capital adequacy ratio to 8% from standalone card issuers, (5) capped cash advance at 50% of credit card assets. While these changes had the right intentions they ended up exacerbating the credit crunch and slowdown.
Clean-up process. While the three countries saw similarities in how the crisis built-up and unfolded, the responses of their governments was different. Hong Kong consolidated through a market-driven mechanism with exit of a player through sale of business and card book to a local player. In Taiwan, about 34 card issuers closed down their businesses altogether. The Korean government intervened through state-owned Korean Development Bank and coordinated a financial rescue package of a leading issuer, LG Card. Both Taiwan and Korea provided regulatory forbearance to the industry to help tide over the crisis.
Exhibit 66: High use of credit cards for cash advance in Korea Credit card use in Asia: purchase versus cash advance, 1998-2006 (%)
Source: BIS research paper
KOTAK INSTITUTIONAL EQUITIES RESEARCH 33
Banks SBI Cards and Payment Services
Exhibit 67: Three episodes of credit card distress in Asia Exhibit 68: Korea: Profitability and credit card lending business Credit card loans and non-performing credit card assets, 1999-06 (%) RoE and cash lending ratio in Korea, 1999-2006 (%)
Source: BIS research paper Source: BIS research paper
Exhibit 69: Taiwan: High share of cash advance income at the Exhibit 70: Hong Kong: Strong correlation between peak of crisis unemployment and charge-offs Profitability in credit card business and cash card lending in Taiwan, Unemployment, personal bankruptcy and credit card charge-off, 1999-06 (%) 1997-2005, (%)
Source: BIS research paper Source: BIS research paper
The retail payment industry is just evolving: the utility can be disrupted
The merchant least prefers it while the customer has a greater affection to use a credit card given its utility of (1) interest free period, (2) reward points and (3) credit function. India is still very early in its adoption. We see that different markets have seen different adoption of the credit card product despite all characteristics of competing payment products being similar. Unfavorable views of the product or negative experiences can lead to customers preferring other products over credit cards. We understand that that fees levied on credit cards is a source of constant dissatisfaction for consumers and the complex ways to charge customers can result in gain in alternate channels. Importantly the payment and credit utility can be disrupted though it remains to be seen if customers want to have it that way.
Single product company has its own share of risks
Unlike a bank, which offers a wide range of payment services, SBIC is a single product company. While the company is well equipped to manage the changes with the credit card landscape, behavioral change of consumers outside of cards could be a area of risk.
34 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Buy Now Pay Later: The recent example would be the rise of ‘Buy Now Pay Later’ (BNPL) products. In characteristic, the solution offered by BNPL companies is similar to the EMI option that is available in cards. These companies have tie-ups with companies such as groceries, clothing or online stores, etc. where consumers can pay a fixed amount each month. These are usually 0% interest rate products. However, it turns into a lending product once the customer has fallen behind scheduled payment. The interest rates on these loans can be similar to that of a regular credit card. Recent reports suggests that the adoption of this product is higher with Gen Z and millennials, who were born between 1981 and 2002. The most common reason for using this product seems to evolve around simplicity of the product and no need to pay credit card interest rates. The most famous ones in this are (1) Bill Me Later/Pay Pal credit, (2) Afterpay, (3) Affirm, (4) Klarna, (5) FuturePay, (6) QuadPay, (7) Sezzle and (8) SplitIt across the world.
The merchant has a strong rationale for using this payment method. Merchants, instead of offering discounts which can affect their brand, can choose this method instead. It can help improve sales and solves the affordability argument for consumers as they don’t need to pay higher interest. In the online platform, the ability to complete sales is much easier through this payment platform. This product is not new in India. Bajaj Finance, for example, has been offering zero interest rate BNPL products for a very long time. However, we have seen the evolution of a few other players as well in recent years. ZestMoney, for example, has also started offering this product. This segment is still small currently (see exhibit 71 and 72).
Exhibit 71: Rise in non-cash payment modes; higher competition Exhibit 72: Digital/ mobile wallets also expected to gain share for cards in online payments Breakup of global POS payments, Calendar year-ends, 2019 and Breakup of global e-commerce payments, Calendar year-ends, 2019 2023E (%) and 2023E (%) POS payments Prepaid card E-com payments Other 100 100 BNPL Charge card 80 80 Cash on delivery Credit card 60 60 Charge and deferred debit card Digital/ mobile Bank transfer 40 wallet 40 Debit card Debit card 20 20 Credit card Cash Digital/ mobile 0 0 wallet 2019 2023E 2019 2023E Source: ‘Global Payments Report’, Worldpay from FIS Source: ‘Global Payments Report’, Worldpay from FIS
Interchange fees play a very critical role in revenues
SBIC generates substantial amount of revenue through interchange fees and business development incentives (see exhibit 73 of the credit card transaction process). A key risk is that the bank is dependent on third party networks like Visa, MasterCard and Rupay as they help in processing the payments made by their credit card customers. The contribution of this fee income is ~25% of the total revenues.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 35
Banks SBI Cards and Payment Services
Outside of the dependency on these networks, the risk of interchange fees being regulated is a key area of risk. We have already seen a substantial amount of work on this issue on the debit card platform across the world in the previous few decades. However, for now, we note that the credit cards intermediation is a lot lower. The European Union had introduced a Interchange Fee Regulation (IFR) in 2015 and this perhaps, led to the largest ever reduction in interchange fees. The IFR capped the charges at 0.20% for debit card and 0.30% for credit card payments. However, we have seen MDR or interchange fees dropping quite consistently in select markets. Exhibit 74 and 75 shows the MDR for card issuers in Australia. Note that it is one of the few places that has witnessed a consistent decline in the past two decades. A steady decline in MDR rates reduces the efficacy of the product. The MDR plays a very critical role in the product offering as the points that the customer generates is translated into an offer. The attraction of the offer is contingent on the MDR rates. A reduction in the rates would result in a lower offer.
A reduction in MDR may not necessarily result in desired outcomes for the consumer. The challenge is that the credit card customer does not feel its impact as the cost of the transaction does not reduce. There have been studies that show that for the merchant: (1) the reduction in price is not meaningful but the merchant is a lot more comfortable to accept the transaction on credit/debit more than before and (2) willing to put in more POS accepting devices.
Exhibit 73: A graphical representation of the major stakeholders in a credit card transaction
Card scheme
₹ Issuer Acquirer bank bank
Interchange fee fees
incentives ₹
₹
Cardholder
Cardholder Merchant servicecharge Merchant
Card- Transaction of goods/ services Merchant holder
Source: Kotak Institutional Equities
36 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 74: MDR has been on a declining trend over the past Exhibit 75: MDR on debit cards have declined across the board two decades between 2017 and 2019 MDR across different payment instruments in Australia, 2003-19 (%) MDR for card transactions across merchant size in Australia, 2017-19 (%) V&M overall V&M credit V&M debit American Express Diners Club EFTPOS 2.5
2.0
1.5
1.0
0.5
-
Mar-04 Mar-05 Mar-06 Mar-09 Mar-10 Mar-11 Mar-12 Mar-15 Mar-16 Mar-17 Mar-20 Mar-07 Mar-08 Mar-13 Mar-14 Mar-18 Mar-19 Mar-03
Notes: (1) Prior to June 2018, MDR for V&M (Visa and Mastercard) debit Notes: cards was slightly overstated, while MDR for V&M credit cards was (1) Merchants ranked in value deciles – average annual value (AU$ slightly understated. mn) of card transactions for each bucket shown in parenthesis.
Source: Reserve Bank of Australia Source: Reserve Bank of Australia
The usage of the brand ‘SBI’ and its distribution
As of 3QFY21, SBI owns 69.5% in SBIC. SBIC has a non-exclusive and non-transferable right to use the logo and certain trademarks for its business operations. SBI can terminate the agreement for various specified factors which includes the bank’s stake in the company falling <26%.
SBIC will provide branch relationship executives at select branches of SBI. SBI provides referrals to the company generated through various channels as decided by SBI. SBIC pays a commission to SBI. The company pays a royalty of 2% or 0.2% of total income, whichever is higher.
Deterioration in macroeconomic conditions or volatility in financial markets The business relies primarily on interest charged on credit card receivables and fee income derived from interchange fees, late fees, annual card fees and service charges to generate revenues. Poor economic conditions tend to lead to a reduction in usage of credit cards and the average purchase amount on transactions, both of which reduce interest and fee incomes.
Further, the occurrence of any disruptions in the financial markets may adversely affect SBIC’ cost of funding, credit card receivables portfolio, business, etc.
Increase in competition from other credit card issuers and other stakeholders
The business faces intense competition in the credit card market from other credit card issuers and payment solutions providers such as banks, payment banks, NBFCs and financial technology enterprises. In particular, mobile, e-wallets and tokenization platforms, including the popular Unified Payments Interface (UPI) platform, present stiff competition since they attract large payment volumes at low or no payment processing fees to merchants.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 37
Banks SBI Cards and Payment Services
Failure in implementing growth strategy or managing funding and liquidity risks
SBIC has experienced significant growth in recent years. However, this growth strategy could face challenges in the future for a variety of reasons, including efficiently managing the operations, failure to maintain the level of customer service and applying its risk management policy effectively. If the company fails to manage its funding and liquidity, it may expose itself to maturity mismatches between its assets and liabilities, face liquidity shortfalls and fail to meet its obligations during a liquidity stress event.
Cost of running this business is quite high
There are two broad costs in this business. On one hand the cost is on acquisition. SBIC acquisition is expected to be on the lower side given its relationship with SBI. However, on the other side, there is a need to constantly engage with the customer to make the card as the preferred choice to make payment. This involves sharing a higher share of the inter- change fees or there is a constant need to advertise the utility of the product. These costs needs to be recouped through better volumes and with lower intervention of the regulation.
38 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
SBI CARDS: BACKGROUND AND OVERVIEW
Brief profile of the company
SBI Cards and Payment Services started operations in 1998 as a joint venture between SBI and GE Capital. In the same year the company received NBFC license from the RBI. In the year 2017, Carlyle (CA Rover) acquired 26% stake in SBIC from GE Capital.
SBI Cards is the only standalone credit cards company with a meaningful scale and size. The company offers a wide credit cards portfolio catering to a broad target customer base. The card portfolio comprises retail cards, corporates cards and within retail, broad categories include premium, travel and fuel, shopping, white label cards, etc. SBIC is the second-largest credit card issuer in India, with a 19-20% % market share of the Indian credit card market in terms of cards outstanding and spends.
SBI is the parent and promoter of the company with ~70% stake as of September 2020. SBIC pays royalty to SBI every year (Rs248 mn in FY2020) as per licensing agreement for use of SBI brand and logo. SBI can terminate the agreement if the stake falls below 26%, among other conditions.
Exhibit 76: Shareholding pattern As of September 2020 (%)
Sr. no. Name of shareholder % stake 1 State Bank Of India 69.5 2 CA Rover Holdings 15.9 3 BNP Paribas Arbitrage - ODI 1.1 4 Government Pension Fund Global 0.6 5 Kotak Standard Multicap Fund 0.5 6 Pioneer Investment Fund 0.3 7 HDFC Equity Fund 0.3 8 RWC Emerging Markets Equity Master Fund Limited 0.3 9 Life Insurance Corporation Of India 0.2 10 Vanguard Total International Stock Index Fund 0.2 11 HDFC Balanced Advantage Fund 0.2 12 Vanguard Emerging Markets Stock Index Fund, A Series Of Vanguard 0.2 13 Societe Generale – ODI 0.2 14 Thornburg Developing World Fund 0.2 15 Robeco Capital Growth Funds 0.2 16 HDFC Top 100 Fund 0.2 17 Fidelity Investment Funds - Fidelity Asia Fund 0.2 18 Fidelity Investment Funds Icvc - Fidelity Global Focus Fund 0.1 19 ITPL - Invesco India Growth Fund 0.1 20 Canara Robeco Mutual Fund A/C Canara Robeco Emerging Equities 0.1
Source: Company, Kotak Institutional Equities estimates
KOTAK INSTITUTIONAL EQUITIES RESEARCH 39
Banks SBI Cards and Payment Services
Exhibit 77: SBIC: Board of directors
Name Responsibility Experience Qualification
He is an associate of the Indian Institute of Bankers. He has been the Bachelor's and Master's degree in Non-Executive Chairman Managing Director of the SBI since August 2016. He was the Managing Dinesh Kumar Commerce and Master's degree in and Nominee Director of Director and Chief Executive Officer of the SBI Funds Management Khara Business Administration, University of the SBI Private Limited. He joined the SBI as a probationary officer in 1984 and Delhi has over 35 years of experience in the banking industry.
Holds a Bachelor's degree in Engineering He has been part of SBI for about three decades leading several and is a Certified Associate of Indian Ashwini Kumar Managing Director and leadership positions - including the Country Head of US Operations. He Institute of Banking (CAIIB), Certified Tewari Chief Executive Officer has served on the Board of International Institute of Bankers, New York Financial Planner (CFP) and has a and the Board of University of Washington Global Bankers Program. certificate in management from XLRI.
He has about 34 years of experience in banking, finance, management and operations. Currently, he is serving as CGM (Associates & Subsidiaries) in SBI. He has earlier served in various geographical He is a Graduate in B.A. (Honours) and is Non-Executive Nominee Devendra Kumar locations across the country a Certified Associate of Indian Institute of Director of the SBI in SBI and erstwhile Associate Banks. He has served as General Bankers (CAIIB). Manager - Network in Maharashtra Circle, Chandigarh Network in e- SBP and Hyderabad Network in e-SBH.
He joined the Carlyle group in 2008 and, presently, he is the Managing Director and head of financial services industry of Carlyle Asia Partners. Bachelor's in Technology in Electrical Non-Executive Nominee Concurrently, he heads the south-east Asia business of the Carlyle Engineering, Indian Institute of Director of CA Rover (an Sunil Kaul group. Previously, he has worked with Citi and has held non-executive Technology Bombay and Post-Graduate affiliate of the Carlyle director positions on the boards of Ta Chong Bank in Taiwan and Diploma in Management from Indian group) Diamond Bank in Nigeria. He has 34 years of experience in the fields of Institute of Management Bangalore private equity, corporate and consumer banking.
He is an associate of the Indian Institute of Bankers and honorary fellow of the Indian Institute of Banking and Finance. He was appointed Bachelor's in Law and Master's in as the vigilance commissioner in Central Vigilance Commission by the Tejendra Mohan Business Administration, University of Independent Director President of India. Presently, he is the Chairman of Advisory Board for Bhasin Delhi and Doctorate in Philosophy, Banking Frauds. Previously, he was associated with the Oriental Bank University of Madras of Commerce, United Bank of India and Indian Bank. He has 10 years of experience in administration and banking industry.
He is a partner at CVK & Associates. He has been practising as a Member of The Institute of Chartered Shriniwas Chartered Accountant for 40 years. He is an Independent Director on Accountants of India (ICAI) and The Independent Director Yeshwant Joshi the Board of L&T Mutual Fund Trustee Ltd. He was the Chairman of the Institute of Company Secretaries of India Financial Reporting Review Board (2019-20). (ICSI) since 1980
He is an associate of the Indian Institute of Bankers and a fellow of the Bachelor's in Science, Birla Institute of Insurance Institute of India. Previously, he has been associated with the Technology and Science and Master's in Rajendra Kumar Independent Director SBI, National Payments Corporation of India and TVS Capital Funds Science, Indian Institute of Technology Saraf Private Limited. He has over 34 years of experience in the banking Kanpur and Diploma in Financial industry. Engineering, University of Bombay
Previously, he was the Chairman and Managing Director of Life Dinesh Kumar Insurance Corporation of India and Independent Director on the board Bachelor's in Science (Hon.), University of Independent Director Mehrotra of Indian Energy Exchange Limited. He has over 42 years of experience Patna in the insurance industry.
Currently, she is associated with Svakarma Finance Private Limited as a Director. Previously, she has been associated with Standard Chartered Bachelor's in Commerce, University of Anuradha Shripad Bank, Swadhaar Finserve Private Limited, Lotus India Asset Poona and Post-Graduate Diploma in Independent Director Nadkarni Management Company Private Limited and Pudhuaaru Financial Management, Indian Institute of Services Private Limited. She has over 30 years of experience across Management Bangalore multiple financial services businesses.
Source: Company, Kotak Institutional Equities
40 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 78: Management team
Name Responsibility Experience Qualification He has been part of SBI for about three decades leading Holds a Bachelor's degree in Engineering and is a Certified several leadership positions - including the Country Head of Ashwini Kumar Managing Director and Associate of Indian Institute of Banking (CAIIB), Certified US Operations. He has served on the Board of International Tewari Chief Executive Officer Financial Planner (CFP) and has a certificate in Institute of Bankers, New York and the Board of University management from XLRI. of Washington Global Bankers Program.
He joined the company from SBIBPMSL on April 1, 2018, with the amalgamation of SBIBPMSL with SBI Card. Bachelor's in Arts from Maharshi Dayanand University, Richhpal Singh Chief Operating Officer Previously, he was associated with Jio Payments Bank Rohtak Limited.
Previously, she was associated with GE Money Financial Aparna Chief Risk Officer Services Limited, American Express Financial Advisors, Bank Master's in Finance and Control, University of Delhi Kuppuswamy of America and ABN AMRO Bank.
He is an associate of the Institute of Chartered Accountants of India. Previously, he was associated with various GE Nalin Negi Chief Financial Officer companies, Nestle India Limited, American Express (India) Bachelor's in Commerce (Hon.) from University of Delhi Private Limited, EXL Service.com (India) Private Limited and ITC Limited.
Chief Product and Previously, he was associated with American Express Bank Post Graduate Diploma in Management from Indian Girish Budhiraja Marketing Officer Limited and ICI India Limited. Institute of Management Bangalore
Previously, he was associated with the erstwhile SBIBPMSL, Bachelor's in Mechanical Engineering, Panjab University Manish Dewan Chief Sales Officer Standard Chartered Bank and American Express Bank and Post Graduate Diploma in Management from Indian Limited. Institute of Management Society, Lucknow
He was deputed to SBI Card by the SBI for a period of two years with effect from September 18, 2017. This was further Naresh Kapur Chief People Officer Bachelor's in Science, Guru Nanak Dev University extended by one year. He has been associated with the SBI since 1990.
He was deputed to SBI Card by the SBI for a period of two Rajendra Singh Head of Internal Audit years with effect from June 1, 2018. He has been associated Associate of the Indian Institute of Bankers with the SBI since 1985.
She has been deputed to SBI Card by the SBI for a period of Suruchi Nagpal Head of Internal Audit two years with effect from June 20, 2019. She has been Master's in Arts from Panjab University associated with the SBI since 1984. Ashok Kumar Head of Workforce Lohmod Effectiveness Bachelor's in Engineering from Punjab Technical University, Chief Information and He was associated with various GE group companies and Pradeep Khurana Jalandhar and Diploma in Advanced Computing from Digital Officer IGE India Limited. Advanced Computer Training School, Pune Previously, he was associated with Lakshmikumaran & Bachelor's in Law from University of Delhi and Bachelor's Ugen Bhutia Head of Legal Sridharan Attorneys and Fox Mandal & Co. in Commerce (Hon.) from University of North Bengal Bachelor's in Science (Hon.) from University of Delhi and Previously, she was associated with various GE companies Rinku Sharma Chief Compliance Officer Post Graduate Diploma in Management from the and DCM Financial Services. International Management Institute
Diploma in Hotel Management from National Council for He was associated with various GE group companies for 11 Hotel Management and Catering Technology, Noida and Amit Batra Head of Operations years. certificate for completion of INSEAD leadership program for senior Indian executives from INSEAD
Bachelor's in Electrical Engineering from University of Delhi Head of Customer Previously, he was associated with the erstwhile SBIBPMSL Monish Vohra and Master's in Business Administration from University of Services and PNB Metlife India Insurance Company Limited Delhi
Bachelor's in Commerce from University of Rajasthan, Anu Choudhary She was associated with the erstwhile SBIBPMSL and Head of Collections Jaipur and Post Graduate Diploma in Management from Lal Gupta Standard Chartered Bank. Bahadur Shastri Institute of Management, New Delhi He has been with SBI Cards for over 3 years and has helped PG Diploma from Institute of Integarted Learning in Vishal Singh Head of Banca Channel create non-metro sales vertical. Management Previously, she was associated with GE Capital for over 8 Nandini Malhotra Chief Credit Officer MA Economics from Delhi School of Economics years as part of the risk function.
Source: Company, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 41
Banks SBI Cards and Payment Services
THE ADDRESSABLE MARKET AND PAYMENT PUZZLE In the first section, we look at PFCE to measure the addressable market for credit cards and compare the same with other geographies. We are still yet to build long term payment behavior of customers though. Merchants, if given a choice, would prefer customers pay through debit cards and probably follow it by cash. Credit card is likely to be the least preferred option as it is the most expensive channel for receiving payment. Yet its acceptance has only gained in recent decades across the world. So we explore the drivers of payment behaviors based on studies done by various central banks and experts in this field.
The PFCE can be defined as the addressable market for credit cards
We believe that the private final consumption expenditure can be one of the measures used to understand the payment landscape. Exhibit 79 reflects the major spend categories where the card can be used. Note that nearly all the segments barring housing can be a potential area for spending through a card network provided there is adequate infrastructure. Note that this reflects spends and not necessarily a credit card spend.
Exhibit 79: Digital payments can access most of these spend categories barring housing Components of PFCE across years, December calendar year-ends, 2016 - 2019 (%)
2016 2017 2018 2019 Food and non alcoholic beverages 29.2 30.4 29.2 27.6 Alcoholic beverages, tobacco and others 2.4 2.3 2.2 2.2 Clothing and footwear 7.1 6.7 6.4 6.5 Housing, water, electricity, gas and other fuels 14.9 14.2 14.1 13.9 Furnishing, household equipment and maintenance 3.0 3.0 2.9 2.9 Health 4.3 4.5 4.5 4.8 Transport 14.9 15.0 16.2 16.6 Communication 2.3 2.1 2.3 2.5 Recreation and Culture 0.9 0.8 0.8 0.8 Education 3.9 4.0 4.2 4.4 Restaurant and hotels 2.0 2.0 2.0 2.0 Miscellaneous 15.0 14.9 15.2 15.8
Source: CEIC, Kotak Institutional Equities
We cross reference the above PFCE reference and see the same in Ireland, a country where we have data based on various spend categories. Exhibits 80 and 81 show the spend categories for personal credit cards and corporate credit cards.
Exhibit 80: Groceries/ perishables account for ~11% of spends on personal credit cards Category-wise spends on personal credit cards in Ireland, December calendar year-ends, 2015 - 2019 (%)
100% Others Entertainment 80% Restaurants/ Dining Professional services 60% Utilities Health 40% Accommodation Transport 20% Hardware Clothing 0% 2015 2016 2017 2018 2019
Source: Central Bank of Ireland, Kotak Institutional Equities
42 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 81: Transport and accommodation accounts for ~32% of spends on corporate credit cards Category-wise spends on corporate credit cards in Ireland, December calendar year-ends, 2015 - 2019 (%)
100% Others Entertainment 80% Restaurants/ Dining Professional services 60% Utilities Health 40% Accommodation Transport 20% Hardware Clothing 0% 2015 2016 2017 2018 2019
Source: Central Bank of Ireland, Kotak Institutional Equities
However, a key challenge is to establish the payment preference as this is quite different across countries. Apart from comparison with normal economic growth, which provides the broader landscape for the retail lending opportunity, we could look at the current penetration of the credit card market from a private final consumption expenditure perspective. We see the ratio of credit card spends to PFCE to be a better representation of the credit card’s addressable market. Exhibit 82 shows that India is on the lower side at 5% as compared to other regions.
In most countries, this stabilizes after a point as most of the spend categories of the customer are probably established in certain payment mechanisms and the shift is probably negligible. In India, we are still in the early stages of digital adoption. At this point, we are probably going to see multiple payment channels getting adopted and credit cards would be one of the many formats.
Exhibit 82: Credit card penetration is quite low in India Ratio of credit card spends to PFCE, December calendar year-ends, 2012 - 2018 (%)
Spends-to-PFCE ratio (%) 2012 2013 2014 2015 2016 2017 2018 Korea 66 66 66 69 74 74 75 Canada 35 35 36 36 38 43 43 Hong Kong 34 34 35 35 35 37 38 Singapore 28 30 30 31 31 32 36 Turkey 34 35 35 35 34 33 34 Australia 31 31 31 31 31 32 31 US 21 22 22 23 24 25 26 Japan 14 14 15 17 18 19 22 Brazil 16 17 17 18 17 18 19 UK 11 11 11 12 12 12 12 Switzerland 9 10 10 10 10 11 12 Sweden 11 11 12 11 11 8 10 Italy 5 5 5 5 6 6 8 Mexico 5 5 5 5 6 6 6 France NA NA 13 8 1 6 6 India 2 2 3 3 4 5 5 Russia 1 2 2 3 3 4 5 Indonesia 4 4 4 4 4 4 4 Saudi Arabia NA 2 3 3 3 3 3
Source: BIS, Kotak Institutional Equities
KOTAK INSTITUTIONAL EQUITIES RESEARCH 43
Banks SBI Cards and Payment Services
A study in Australia over a long dated series shows that there have been inflection points (see exhibit 83). These inflection points are driven by the same set of factors which are (1) adequate infrastructure at the back-end. Australia saw rapid growth in POS machine adoption by merchants in the 1990s, (2) steady expansion in credit card issuance by lenders. Combined with a more favorable macro-economic environment, we saw a sharp shift in spending through the credit card network.
Exhibit 83: Credit card penetration in Australia has been around ~31% levels since 2006 Total value of credit card transactions and private final consumption expenditure in Australia, December calendar year-ends, 1990 - 2019 (AU$ bn)
Value of purchases using credit and charge cards (AU$ bn) Private consumption expenditure (AU$ bn) CC transaction value as % of private consumption expenditure (RHS) 1,100 31 31 31 31 31 31 31 31 31 31 31 32 31 31 35 29 30 28 27 880 28 20 660 18 21 15 440 12 14 9 7 8 6 6 6 6 7 220 7
- 0
1990 1991 1995 1996 1997 1998 2002 2003 2004 2005 2009 2010 2011 2012 2016 2017 2018 1992 1993 1994 1999 2000 2001 2006 2007 2008 2013 2014 2015 2019
Source: BIS, Kotak Institutional Equities
The payment choice is a headache for the merchant and a blessing for customers
All merchants give a wide range of options for customers to pay for goods and services. This would be through (1) cash, (2) debit card, (3) credit card, (4) online or (5) others such as preloaded cards. The payment mode could be contact-based like (cash and physical card), contactless cards or mobile (QR codes, UPI, NEFT or any other formats). It is quite likely that merchants are compelled to cater to customers demand for payment options as it has a positive sales impact. Hence, customers, probably inadvertently or by specific habit choose a specific merchant given their individual choice of payment.
For the merchant, the challenge is that the costs for accepting these payments are quite different. Most survey reports that have happened in North America or Europe suggests the following: (1) credit cards is the least preferred form of payment and (2) debit cards is gradually gaining acceptance instead of cash while other formats are still quite small.
The generally accepted practices across countries in our research suggests (1) merchants are not allowed to have a surcharge across payment instruments as the merchant has the option to disallow a payment mechanism if the merchant is not comfortable with the fees charged on that payment platform and (2) there does not seem to be anything explicit if the merchant can offers a discount on a specific payment process. In most countries, the no- surcharge rule raises the cost for all consumers. Most merchants prefer to charge a uniform rate to their customers rather than differentiating it at the point of purchase. The merchant solves the key challenge of removing one bottleneck that would prevent a purchase. The customer is less concerned on the transaction not being completed and could also benefit from reward programs if offered by the card issuer. Further, cash is a cost that does not earn interest and a wider electronic infrastructure allows the customer to get higher interest.
44 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
The key challenge with accepting cards – the cost benefit analysis for the merchant
From a merchant’s perspective, there needs to be a few choices to be made: (1) Accepting credit cards raises the price for all customers unless the merchant is comfortable to absorb a lower margin for a credit transaction. This would result in customers who prefer paying by cash or debit forcefully looking at alternate places where the product is available at lower cost. (2) Continuous price discrimination would also result in customers mostly with credit card preferring to the use the services of merchant which lowers the potential business that the merchant can have. (3) Price discrimination has challenges as customers need to constantly evaluate the choice of payment for each transaction. This can delay the time taken at the counter which makes the entire experience for other customers less meaningful.
There are two broad costs that the merchant evaluate: (1) explicit and (2) less understood but visible implicit. Explicit costs can be broken in two parts: (1) fixed and (2) variable. The fixed cost is a charge for installation with additional monthly maintenance charged by the payment processor. The variable cost would be charged when there is a transaction. Further, the merchant has also a possible risk if there is a fraudulent activity that is not resolved. This is primarily in the credit card transaction. The implicit costs are the costs is less on electronic methods and mostly in cash such labor and time as there is a need to reconcile and replenish cash by taking/receiving from the local bank which may have cash handling charges as well. There are additional costs of theft or counterfeit notes. These costs are not uniform across merchants. Smaller merchants may have the requisite infrastructure, can choose to deposit cash over a period in time with the bank or the costs associated with set-up and maintenance may outweigh the need to have payment systems or multiple payment systems. A large retail operator may prefer handling less cash as it is relatively inexpensive to do so.
The rationale for the customer to choose a credit card
From a customer’s perspective, credit card turns out to be an elegant product. Once a credit line is established with the lender, the changes to credit limit is a function of their spending pattern and repayment behavior which gets captured through an internal scoring model. The cardholder can choose to complete their entire payment at the end of the billing cycle or delay payment temporarily by a few months by rolling over credit by paying a minimum installment which tends to be ~5% of the outstanding balances. The lender has assessed the borrower based on the initial income profile that plays a critical role when the borrower’s income has changed. Studies across the world have shown that the consumers value these unsecured credit lines even if the interest rate charged is extremely high. The customer has limited choice to get access to liquidity line when there is an emergency. The interest rates play a less critical role as the primary objective to tide over the liquidity challenge as it is mostly assumed to be a temporary event. This forms a majority of customers who are defined as rollover customers or customers who make a purchase taken through an installment option. The limit offered on a credit card is usually a fraction of the overall income of the borrower. The utility of the card is mainly on regular consumption related items and hence, lenders are comfortable offering this product as the interest cost charged by the lender offsets the risks associated with the unsecured credit line offered to the customer whose behavior of spending is not known in advance.
There are several studies and data that provide insights that even a customer with sufficient capacity to pay has shown a high reliance to own and transact through a credit card. We believe that the reward programs, better confidence in dispute resolution or limited consumer liability in case of fraudulent transactions is leading to this segment of customer to use the credit card as compared to cash or debit cards.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 45
Banks SBI Cards and Payment Services
What does survey suggest in terms of the way we pay
We have looked at a few broad surveys on the retail payment survey covering three major markets: (1) The 2019 Diary of Consumer Payment Choice released by Federal Reserve Bank of Atlanta (link) and Federal Reserve Bank of San Fransisco (link). (2) Canada conducts a survey with regular frequency on the methods used by consumers for payments. The report is available in the following link for the year ending 2017 with more granular information on the trends in the past decade. (3) The European Central Bank did a similar study when they released their report, “This Is what’s in your wallet...and how you use it” in June, 2014 (link) and another reported dated 2017 (link). (4) Germany and (5) Australia (link).
The following observations were quite useful from this report.
The survey gives a color that cash utilization has been declining over the past decade. Check usage in purchase transactions has nearly disappeared. This is corroborated in many of the other markets as well.
There is a high preference for cash in all markets. While the usage of cash has been declining, the pace is not uniform across markets. Consumers’ rate cash as an easy-to-use, low-cost, secure and widely accepted payment method. The preference of cash is higher where the age profile is older while other factors include education and income profile of the customer.
As the transactions size declines, the share of cash increases. However, there is a marked change in behavior with the introduction of contactless debit or credit cards.
Cash has a higher preference in professional/personal services, sporting activities and entertainment or meals.
Debit cards generally did not take the top spot for any type of goods. Credit cards saw a higher preference in groceries, fuel, clothing, health care and durable goods. Credit card usage increases by the level of education.
Exhibit 84: Cash is a lot more prevalent for small ticket Exhibit 85: The trend is visible by value and volume across transactions various spend share Payment shares over time: volume, by transaction ticket size Payment shares over time: value, by transaction ticket size
Source: Bank of Canada Source: Bank of Canada
46 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 86: Use of cash has been declining in categories like Exhibit 87: … similar trend seen in groceries and fuel category entertainment, dining and travel Payment shares by transaction value, (%) Payment shares by transaction value (%)
Source: Bank of Canada Source: Bank of Canada
Exhibit 88: Credit cards are gaining traction Exhibit 89: Cash is preferred for smaller ticket transactions Number of transactions per month across payment modes as reported Average payment size across payment modes as reported by surveyed by surveyed users, October 2019 (#) users, October 2019 (US$)
12.5 500
11.8 467 10.0 400 10.0 383 9.2 366 7.5 300
5.0 200
2.5 100 151 2.4 1.8 1.7 0.7 0.1 53 27 80 40
0.0 0
Cash
Debit
Cash
OBBP
BANP
Debit
OBBP
BANP
Credit
Check
Credit
Check
Prepaid
Prepaid Money order Money order Notes: Notes: (a) BANP: Bank account number payment (a) BANP: Bank account number payment (b) OBPP: Online banking bill payment (b) OBPP: Online banking bill payment
Source: 2019 Diary of Consumer Payment Choice, USA Source: 2019 Diary of Consumer Payment Choice, USA
KOTAK INSTITUTIONAL EQUITIES RESEARCH 47
Banks SBI Cards and Payment Services
Exhibit 90: Share of cash in high ticket transactions is low as expected Share of payment instrument usage by purchase amount, 2019 (%)
Source: Diary of Consumer Payment Choice (USA), July 2020
Exhibit 91: Preference towards credit cards has increased marginally from 2016 level State preferences of consumers towards different payment modes, 2016-19 (%)
Debit card Credit card Cash Other 100 7 5 6 7
24 23 80 27 22
60 24 29 29 29
40
20 42 42 42 42
- 2016 2017 2018 2019
Source: Diary of Consumer Payment Choice (USA), July 2020
48 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 92: Survey shows cash has reduced meaningfully while digital has seen a strong traction Share of payments across different age groups in the US, 2019 (%)
100
80 Cash Check 60 Credit card Debit card 40 Prepaid card Electronic payment 20 Others
0 18-24 25-34 35-44 45-54 55-64 65 and older
Source: Diary of Consumer Payment Choice (USA), July 2020
Exhibit 93: Survey shows cash has reduced meaningfully while digital has seen a strong traction Shares of payments by volume and value, October 2019 (%)
Cash Check Debit card Credit card BANP OBBP Other
5
Number 26 31 24 6 4 4
16
Value 6 16 14 24 16 7
0 20 40 60 80 100
Source: 2019 Diary of Consumer Payment Choice, USA
Cash and debit play a bigger role in Germany
The broad trends on payments are quite similar to the other regions where the usage in low value payments is quite high. This progressively reduces when we look at the medium to large value payments. Credit cards are commonly used for hotel bookings, e-commerce transactions and fuel payments
KOTAK INSTITUTIONAL EQUITIES RESEARCH 49
Banks SBI Cards and Payment Services
Exhibit 94: Cash continues to dominate low ticket payments Exhibit 95: Some payments shift from cash to debit cards as Breakup of transaction volume across payment modes for payment payment size increases size < EUR5 in Germany, calendar year-ends, 2008-17 (%) Breakup of transaction volume across payment modes for payment size between EUR5 and EUR20 in Germany, calendar year- ends, Cash Debit card 2008-17 (%) Credit card E-payment scheme Credit transfer Other cashless instruments Cash Debit card Credit card E-payment scheme Credit transfer Other cashless instruments 2017 96 2017 88 9
2014 96 2014 90 8
2011 98 2011 95 4
2008 97
2008 94 4 0 20 40 60 80 100 0 20 40 60 80 100 Source: Payments Diary, Deutsche Bundesbank
Source: Payments Diary, Deutsche Bundesbank
Exhibit 96: Share of cashless payments is significant for payment Exhibit 97: Share of debit cards and cash is similar for EUR50 - size >EUR20 EUR100 size transactions Breakup of transaction volume across payment modes for payment Breakup of transaction volume across payment modes for payment size between EUR20 and EUR50 in Germany, calendar year-ends, size between EUR50 and EUR100 in Germany, calendar year- ends, 2008-17 (%) 2008-17 (%)
Cash Debit card Cash Debit card Credit card E-payment scheme Credit card E-payment scheme Credit transfer Other cashless instruments Credit transfer Other cashless instruments
2017 60 31 2017 39 45 5
2014 68 26 2014 42 43 6
2011 74 21 2011 46 42 6
2008 73 20 2008 48 38 6
0 20 40 60 80 100 0 20 40 60 80 100
Source: Payments Diary, Deutsche Bundesbank Source: Payments Diary, Deutsche Bundesbank
50 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 98: Share of cards is >50% for payments of EUR50-100 Exhibit 99: Credit transfers are common for very high value Breakup of transaction volume across payment modes for payment transactions (>EUR500) size between EUR100 and EUR500 in Germany, calendar year-ends, Breakup of transaction volume across payment modes for payment 2008-17 (%) size >EUR500 in Germany, calendar year-ends, 2008-17 (%)
Cash Debit card Cash Debit card Credit card E-payment scheme Credit card E-payment scheme Credit transfer Other cashless instruments Credit transfer Other cashless instruments
2017 24 46 7 9 2017 25 34 9 19
2014 30 43 9 7 2014 24 14 8 32
2011 26 43 12 12 2011 11 31 24 31
2008 32 38 6 15 2008 39 20 4 35
0 20 40 60 80 100 0 20 40 60 80 100
Source: Payments Diary, Deutsche Bundesbank Source: Payments Diary, Deutsche Bundesbank
Exhibit 100: Credit cards are commonly used for hotel bookings, e-commerce transactions and fuel payments Breakup of transaction value for payments across different places/ purpose of payment, 2017 (%)
Cash Debit card Credit card E-payment scheme Credit transfer Other cashless instruments
Payments to person/ charity Restaurants, bars, cafes/ delivery… Vending machines Entertainment/ recreation Pharmacy Household services Day-to-day retail purchases Other Services outside the home Petrol stations Retail purchase of durable goods Offices of public authorities Mail order Hotel, guest-house E-commerce 0 20 40 60 80 100
Source: Payments Diary, Deutsche Bundesbank
Australia has a higher share of adoption of digital payments
We looked at the recent release from Australia which has done a similar survey. The results of the survey are not too different than what we have seen with other countries. We see a marked change in payment behavior. In a little over a decade, we have seen a reduction in the cash component for retail payments. Many people now tap their cards (or sometimes phones) even for small purchases. When paying with a card in person or online, consumers are more often choosing to use a debit card rather than a credit card.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 51
Banks SBI Cards and Payment Services
Exhibit 101: Cash transactions have declined steadily Exhibit 102: Cash transactions have declined steadily Share of payments by volume across payment modes in Australia, Share of payments by value across payment modes in Australia, 2007- 2007-19 (%) 19 (%)
Cash Debit cards Cash Debit cards Credit and charge cards Internet/Phone banking Credit and charge cards Internet/Phone banking Cheque Other Cheque Other 100 100
80 80
60 60
40 40
20 20
0 0 2007 2010 2013 2016 2019 2007 2010 2013 2016 2019
Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
Exhibit 103: Usage of cash is lower among lower age groups and highest income group Share of number of cash payments within each category in Australia (%)
Source: Reserve Bank of Australia calculations
52 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 104: Cash transactions were significant back in 2007 Exhibit 105: … but have been replaced by cards to a large Share of payment volumes for different merchant categories across extent across merchant categories card and cash in Australia, 2007 (%) Share of payment volumes for different merchant categories card and cash in Australia, 2019 (%) Cash Card 100 Cash Card 100 80 80 60 60 40 40 20 20 0
0
Bills
Other
Holiday
Bills
Services
Other
Transport
station
Food retail
Leisure/
Holiday
Services
Goods retail
Supermarket
Transport
Petrol/ service
station
entertainment
Food retail Leisure/
Goods retail
Supermarket Petrol/ service entertainment Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
Exhibit 106: Cash has been a less preferred mode for high value Exhibit 107: Cash transactions were rarely used for performing transactions >500 AUD transactions in 2019 Share of payment volumes by different payment ticket size across Share of payment volumes by different payment ticket size across card and cash in Australia, 2007 (%) card and cash in Australia, 2019 (%)
Cash Card Cash Card 100 100 4 21 80 80 40 52 54 60 60 64 51 70 95 74 49 64 40 77 40 55 52 45 20 36 20 30 31 19 22 13 10
0 0 3
1-10
1-10
>500
>500
21-50 11-20
21-50 11-20
51-100
51-100 101-500 101-500
Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
KOTAK INSTITUTIONAL EQUITIES RESEARCH 53
Banks SBI Cards and Payment Services
Exhibit 108: Cards were most common in the age group of 30- Exhibit 109: Cards are now most common for the age group 18- 39 years in 2007 29 years Use of cards and cash across different age groups in Australia, 2007 Use of cards and cash across different age groups in Australia, 2019 (%) (%)
Cash Card Cash Card 100 100
18 29 27 24 80 33 80 41
60 60 58 67 77 75
40 78 40 67 68 72 61 52 20 20 34 22 13 14
0 0
>65
>65
18-29 30-39 40-49 50-64
30-39 40-49 50-64 18-29
Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
Exhibit 110: Cards used to be more commonly used by higher Exhibit 111: Cards continue to be more common among the income groups higher income groups Use of cards and cash by (age adjusted) income groups in Australia, Use of cards and cash by (age adjusted) income groups in Australia, 2007 (%) 2019 (%)
Cash Card Cash Card 100 100
22 26 25 80 32 80
60 60 60 58 63 70
40 40 72 69 70 63 20 20 33 30 27 21
0 0
1st
1st
3rd 4th
4th 3rd
2nd
2nd
quartile quartile quartile quartile
quartile quartile quartile quartile
Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
54 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 112: Cards were only marginally more common in Exhibit 113: Cards continue to be more common in capital cities capital cities than regional areas than regional areas Use of cards and cash by location in Australia, 2007 (%) Use of cards and cash by location in Australia, 2019 (%)
Cash Card Cash Card 100 100
25 27 80 80
60 59 60 65
40 40 70 69
20 20 32 25
0 0
city
city
area
area
Capital
Capital Regional Regional
Source: Reserve Bank of Australia calculations Source: Reserve Bank of Australia calculations
Building the infrastructure for payment in India
Several studies across the world by central banks through their research papers show a marked increase in preference of cash over cards. The choice of payment instrument is dependent on various factors which include speed of execution, convenience and availability of payment options. Cash dominates the discussion in payments given that the infrastructure and merchant acceptance is still growing. One of the most interesting developments for India has been the rollout of the payment infrastructure space. When we look at the previous credit card cycle (2005-08) and when we look at the cycle today, the most distinct difference in the POS infrastructure or the ability of the customer to make a payment transaction through a digital format. Aided by the development of the online platform, consumers are lot more comfortable in using the various digital instruments like debit, credit, mobile, UPI or any other format.
Exhibit 114 shows that the density is still quite low as compared to the other regions suggesting that we would continue to see rapid infrastructure expansion in the coming few years. This is despite, India being the second fastest country (after China) to roll out POS terminals in recent years. They have rolled out ~25% CAGR in the past decade (see exhibit 115 and 116). The impetus gained traction post demonetization and the recent Covid impact is likely to accelerate this further in the coming decades. As per RBI, they have grown by 2.6X since demonetization. We have started to see a strong growth in other formats like QR code as well.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 55
Banks SBI Cards and Payment Services
Exhibit 114: India has seen a marked improvement in POS infrastructure over the past few years; a lot of headroom remains for further improvement Density of POS terminals, calendar year-ends, 2012-18 (# per million population)
Australia Brazil China India Indonesia South Africa UK 45
36
27
18
9
0
2013 2014 2017 2018 2015 2016 2012
Notes: (1) POS terminals in India grew from 0.7 per mn in 2012 to 2.8 per mn in 2018.
Source: BIS, World Bank, Kotak Institutional Equities
Exhibit 115: POS terminals in India have grown rapidly at 29% Exhibit 116: Improvement in penetration of POS infrastructure CAGR has contributed to higher POS transactions per card CAGR over 2012-19 for POS terminals, calendar year-ends (%) Average number of POS transactions per card (across debit and credit), March fiscal year-ends, 2013-20 (#) 35 10.0
28 8.0 21 8.2
6.0 14 6.2 5.4 7 4.0 4.5 3 15 26 29 9 11 9 - 2.9 3.0 3.1
2.0 2.7
UK
India
Brazil
China
Australia Indonesia
- South Africa South 2013 2014 2015 2016 2017 2018 2019 2020 Note: (1) 5-year CAGR over 2013-2019 for Indonesia. Source: RBI, Kotak Institutional Equities Source: BIS, World Bank, Kotak Institutional Equities
56 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 117: Number of Bharat QR codes deployed has increased >60% since November 2019 Number of Bharat QR and UPI QR codes deployed, November 2019 onwards (mn)
Bharat QR UPI QR (RHS) 3.0 66 70 60
2.4 2.6 56 2.4 2.2 2.3 2.2 1.8 2.0 2.0 2.1 42 1.9 1.7 1.8 1.6 1.2 28
0.6 14
0.0 0
Jul-20
Jan-20
Jun-20
Oct-20 Feb-20
Apr-20 Sep-20
Dec-19
Nov-19
Mar-20 Aug-20 May-20 Notes: (1) Total number of UPI QR codes deployed was ~60 mn as of September 2020.
Source: RBI
The corporate and retail card businesses
The credit card business can be broadly broken into two major categories: retail and corporate cards. While the retail credit card is self-explanatory, less appreciated is the contribution of corporate credit cards. A corporate card program helps in (1) better expenses management (corporate and through employee spends) as the corporate can get reports on various categories of spends with a customized MIS tools which helps in easier reconciliation and can be integrated with existing accounting software of the company, (2) reduce costs as the rewards on the spends can be offset with lower statement costs or can be cashed through redemption of these points, (3) risk controls which includes specifying spend limits or prevent fraudulent transactions and (4) improve process. Credit card companies offer corporates to extend working capital cycles as the billing cycle is over a period of 20-50 days after the transaction is completed. Exhibit 118 shows some of the credit card for the corporate segment by some of the leading issuers in the market.
The credit risk is low when the card offering is primarily to the company’s employees. The card issuer tends to benefit on the interchange as the rollover is quite negligible. The corporate card offered to self-employed or professional has a credit income as well.
Exhibit 118: Corporate cards are likely to be a small proportion of cards issued but a much higher share of spends Illustrations of corporate card offerings across banks
Source: Company websites, Google
KOTAK INSTITUTIONAL EQUITIES RESEARCH 57
Banks SBI Cards and Payment Services
We don’t have a lot of information on the corporate card spends in India. However, we have looked at three markets to understand the corporate card business. These three countries are Australia (see exhibit 119-122), Ireland (see exhibit 123-126) and Korea (see exhibit 127- 130). The data is quite exhaustive to show that this can be an important source of business for a bank.
In nearly all these countries, the share of corporate credit card as a proportion of the overall credit cards has been rising. The share is quite low at 8-10% by the total number of cards issued as a share of the overall cards. The transaction share by volume also tends to be lower at 6-10% but its stands out on the total share by value at ~20%. The average ticket size is much higher at 2.5-4X the retail card transaction.
Exhibit 119: Corporate cards has seen a steady increase in the Exhibit 120: Average spend per corporate card is 4X of that on a past two decades personal card Share of corporate cards in total cards in Australia, 2002-20 (%) Average spend per card in Australia, Monthly, 2002-20 (AUS$)
10 Personal Commercial 500
8 400
6 300
4 200
2 100
- -
Jul-2008
Jan-2002 Jan-2015
Jun-2007 Jun-2020
Oct-2011
Feb-2016 Feb-2003
Apr-2005 Sep-2010 Apr-2018
Jul-2008
Dec-2013
Nov-2012
Mar-2004 Mar-2017
Aug-2009
May-2019 May-2006
Jan-2002 Jan-2015
Jun-2020 Jun-2007
Oct-2011
Feb-2003 Feb-2016
Apr-2005 Sep-2010 Apr-2018
Dec-2013
Nov-2012
Mar-2004 Mar-2017
Aug-2009 May-2019 May-2006
Source: Reserve Bank of Australia Source: Reserve Bank of Australia
Exhibit 121: The share in transactions is ~5% by corporate cards Exhibit 122: A steady increase in contribution to ~20% by value Share of transactions (volume) corporate cards in total cards in Share of transactions (value) corporate cards in total cards in Australia, 2002-20 (%) Australia, 2002-20 (%)
10 24
20 8
16 6 12 4 8
2 4
- -
Jan-2002 Jan-2003 Jan-2006 Jan-2007 Jan-2008 Jan-2009 Jan-2010 Jan-2011 Jan-2013 Jan-2014 Jan-2015 Jan-2016 Jan-2017 Jan-2018 Jan-2002 Jan-2003 Jan-2006 Jan-2007 Jan-2008 Jan-2009 Jan-2010 Jan-2011 Jan-2013 Jan-2014 Jan-2015 Jan-2016 Jan-2017 Jan-2018 Jan-2004 Jan-2005 Jan-2012 Jan-2019 Jan-2020 Jan-2004 Jan-2005 Jan-2012 Jan-2019 Jan-2020
Source: Reserve Bank of Australia Source: Reserve Bank of Australia
58 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 123: Corporate cards has seen a steady increase in the Exhibit 124: Average spend per card in corporate is 2.6X past five years personal card Share of corporate cards in total cards in Ireland, 2015-20 (%) Average spend per card in Ireland, 2002-20 (EUR)
12 Personal Corproate 160
10 128 8
96 6
4 64
2 32
0 0 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 Source: Central Bank of Ireland Source: Central Bank of Ireland
Exhibit 125: The share in transaction volumes is ~12% for Exhibit 126: A steady increase in contribution to ~20% by value corporate cards Share of transactions (value) corporate cards in total cards in Ireland, Share of transactions (volume) corporate cards in total cards in 2002-20 (%) Ireland, 2002-20 (%) 25 15.0
20 12.0
15 9.0
10 6.0
5 3.0
- - 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019
Source: Central Bank of Ireland Source: Central Bank of Ireland
KOTAK INSTITUTIONAL EQUITIES RESEARCH 59
Banks SBI Cards and Payment Services
Exhibit 127: Corporate cards has seen a steady increase in the Exhibit 128: Average spend per card in corporate is 2.6X past two decades personal card but declining Share of corporate cards in total cards in Korea, 2002-20 (%) Average spend per card in Korea, 2002-20 (Korean Won)
10 Personal Cards Corporate Cards 45,000
8 36,000
6 27,000
4 18,000
2 9,000
0 0
2002 2003 2004 2005 2006 2007 2008 2009 2011 2012 2013 2014 2015 2016 2017 2018 2010 2019
2004 2005 2006 2007 2008 2010 2011 2012 2013 2016 2017 2018 2019 2009 2014 2015 2003
Source: Bank of Korea Source: Bank of Korea
Exhibit 129: The share in transactions is ~8% by corporate cards Exhibit 130: A steady increase in contribution to ~20% by value Share of transactions (volume) corporate cards in total cards in Korea, Share of transactions (volume) corporate cards in total cards in Korea, 2002-20 (%) 2002-20 (%)
10 35
8 28
6 21
4 14
2 7
0 0
2002 2003 2004 2005 2007 2008 2010 2011 2012 2013 2014 2015 2016 2018 2019 2002 2003 2004 2005 2007 2008 2010 2011 2012 2013 2014 2015 2016 2018 2019 2009 2017 2006 2009 2017 2006
Source: Bank of Korea Source: Bank of Korea
60 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
The credit card eventually ends up as a ‘transactor’ to the high credit scorers and a credit product to the lower credit score customers
Unlike a typical retail loans, credit card has two distinct characteristics that separate this product from the rest: (1) nearly all retail products with the exception of home equity line of credit or mortgage loan which has an overdraft facility, establishes a credit line that is completely drawn down by the borrower after the borrower is sanctioned with that facility. A credit card opens a line of credit with the borrower where the utilization period and extent of utilization is relatively unknown and (2) it is a non-collateralized loan where the borrower’s repayment assessment is not done on a continuous basis.
Card companies have a mix of customers with a greater focus on the middle income segment. The objective is to have some ideal balance between customer segments as the payment behavior is quite different across the various segments. The middle income segment is not only large from a share of population perspective but also shows healthy characteristics to utilize their card limits better, leading to a higher share of interest and fee income. However, the risk rises materially as we get into sub or deep subprime. Hence, the risk reward needs to be carefully assessed by the lender. Note that each bank may have a different business model which implies different risk consuming abilities.
A study by Consumer Financial Protection Bureau that was released in July 2019 showed the following insights into the credit card business in the US. The report discusses the services provided by the card as an instrument to borrow. The study showed that there is persistency of card holders to maintain a positive balance for a substantial period of time. These revolver types are found among prime and subprime cardholders. However, the variation in repayment profiles is observed for both high and low credit score accounts, which implies that repayment is not easily predicted by cardholders’ credit score at the outset of revolving.
At any given month, accounts are in four groups: (1) Inactive, (2) transactors, (3) revolvers and (4) transitioners. An account is categorized as inactive if, as of any given month, there are no purchases, balances, or payments made on it in that billing cycle and the prior billing cycle. Similarly, an account is categorized as transacting, as of any given month, any balance on it is paid in full for that cycle and one preceding cycle. Revolvers are those who, as of any given month, carry a positive balance, net of payments, in that cycle and the preceding cycle. This definition of revolving follows the one used in previous CFPB reports on the credit card market. All remaining accounts, or those that transition between the above categories from one month to the next, are categorized as ‘transitioners’.
Exhibit 131 shows the nature of these customers. The studies show that that the share of inactive customers has been gradually declining. ~40% customers are inactive in the study conducted between 2008 and 2015. Among the active users, ~66% of customers tend to be revolvers. The share of transitioners who usually move between becoming a revolver or transactors has been broadly stable at 10%.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 61
Banks SBI Cards and Payment Services
Exhibit 131: ~40-50% of customers are inactive while 66% of active customers have a credit balance Revolving propensity and transition dynamics of US card customers, 2008-15 (# accounts, %)
Source: Consumer Financial Protection Bureau
Exhibit 132 shows the revolving propensity of customers based on their credit scores or default risk. As would have been expected, the propensity to have a balance is well established by customer scores with the share of super-prime customers having lower intent to have a credit balance as compared to customers in the sub-prime segment.
Exhibit 132: Propensity to resolve is higher at lower scores; transactors dominate the higher score Revolving propensity and transition dynamics based on credit scores, 2008-15 (# accounts, %)
Notes: (a) The vertical lines represent the four customer segments based on deep sub-prime, core sub-prime, core- prime and super-prime.
Source: Consumer Financial Protection Bureau
The following two exhibits explain a similar point made previously. We look at another report published by the Bureau of Consumer Financial Protection, US to understand the behavior profile of a credit card holder. Exhibit 133 shows that the revolving customer is most likely to increase as the credit scores of the customer declines. This exhibit shows that number of customers by account who have traditionally kept a revolve option running in their credit card book. Exhibit 134 shows the repayment rate (by amount) of different customer segments. We see that the super-prime segment tends to be the best in terms of repayment rate.
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SBI Cards and Payment Services Banks
Exhibit 133: Lower scores witness a much high revolve rate Exhibit 134: Payment rate higher for super customers Share of accounts revolving in general purpose cards, 2015-18 (%) Payment rate by balance outstanding, 2015-18 (%)
Source: Bureau of Consumer Financial Protection, US Source: Bureau of Consumer Financial Protection, US
Profile of the customer that is consuming credit rather than a transactor
In this section, we get a little deeper by understanding the nature of a credit card holder who has an outstanding debt in his card. Exhibit 135 gives us a snapshot of the profile of the customer.
The following are the key observations from the Survey of Consumer Finance reports in the US over the period 1989-2019.
Credit card that carries some form of debt has been quite consistent at 40-45% levels of the total credit card customers. The rest would be customers who are inactive on their card usage or ‘transactors’. The most common form of credit card is the general purpose credit card and which has a revolve feature. In the initial decades, there was a higher preference for retail store cards or cards issued by specific sectors like fuel, entertainment or travel. This has given way for the general purpose cards.
Card companies prefer looking for an ideal mix of customers with a greater focus on middle income segment. This is evidenced by the percentile of income that carries a credit balance. There seems to be reluctance to issue cards to the lowest income segment while there is negligible requirement of debt in the upper income segment which results in the bulk of credit card debt between the two segments. The share of revolvers from the lowest income segments in the overall revolvers tends to be fairly lower even if they have the highest share of revolve within their customer segment.
Unlike housing or mortgage loans, the relationship established with a credit card customer is quite early when it comes to the age profile. We see ~50% of credit card customers in the age profile of ‘less than 35’ having some form of credit balance while the same for housing is only ~30%.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 63
Banks SBI Cards and Payment Services
Exhibit 135: Who is a credit card debt owner in US? Credit card characteristics debt in US based on surveys, 1989–2019
1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 All families 39.7 43.7 47.3 44.1 44.4 46.2 46.1 39.4 38.1 43.9 45.4 Percentile of income Less than 20 15.3 23.4 26.0 24.5 30.3 28.8 25.7 23.2 19.6 29.0 30.4 20–39.9 27.6 41.9 43.2 40.9 44.5 42.9 39.5 33.4 34.2 41.7 45.5 40–59.9 48.9 51.9 52.9 50.1 52.8 55.1 54.8 45.0 46.9 53.0 55.1 60–79.9 57.3 55.6 60.0 57.4 52.6 56.1 62.1 53.1 49.8 52.8 56.9 80–89.9 58.3 53.6 61.0 53.1 50.3 57.6 55.8 51.0 48.2 51.5 45.9 90–100 40.5 37.9 47.3 42.1 33.1 38.5 40.6 33.6 32.2 34.4 32.1 Age of reference person (years) Less than 35 44.5 51.8 54.7 50.7 49.6 47.5 48.5 38.7 36.8 45.4 47.6 35–44 50.5 50.9 55.9 51.3 54.1 58.8 51.7 45.7 41.7 49.1 50.5 45–54 49.3 48.9 56.4 52.5 50.4 54.0 53.6 46.2 44.3 52.3 51.7 55–64 32.9 37.2 43.2 45.7 41.6 42.1 49.9 41.3 43.4 41.4 46.6 65–74 27.2 32.1 30.5 29.2 30.0 31.9 37.0 31.9 32.8 42.1 41.1 75 or more 10.1 20.1 17.5 11.2 18.4 23.5 18.8 21.7 21.1 26.2 28.0 Family structure Single with child(ren) 35.6 43.3 43.9 38.0 48.1 48.6 45.3 35.3 32.5 43.5 46.7 Single, no child, age less than 55 34.9 41.0 48.4 46.9 47.8 47.6 42.9 37.2 33.6 41.3 42.1 Single, no child, age 55 or more 19.9 25.2 25.1 21.1 27.1 27.8 30.2 26.9 30.0 36.8 36.0 Couple with child(ren) 53.8 56.0 60.9 55.8 52.4 56.7 54.7 47.4 46.6 51.0 53.5 Couple, no child 35.5 40.8 43.3 42.4 40.5 41.8 46.7 40.1 38.5 42.4 44.7 Education of reference person No high school diploma 23.7 27.4 32.4 28.5 30.0 29.5 26.9 27.7 27.4 35.2 32.4 High school diploma 40.8 46.7 49.8 43.0 46.4 48.2 46.8 36.9 36.3 44.3 47.1 Some college 50.5 49.8 55.8 54.3 53.9 55.9 53.4 47.6 45.3 50.8 51.7 College degree 45.5 47.6 46.5 45.5 42.2 44.3 48.0 39.9 37.8 41.3 43.2 Race or ethnicity of respondent White non-Hispanic 41.5 44.2 47.1 44.3 43.3 46.0 45.1 39.3 38.5 42.1 44.5 Black or African-American non- 33.4 43.3 45.3 42.0 52.3 46.8 50.3 39.1 37.3 47.8 47.7 hispanic Hispanic or Latino 34.7 39.8 56.1 46.1 43.3 47.3 45.4 42.1 41.5 49.6 49.9 Other or Multiple Race 36.6 42.9 44.8 43.4 41.5 45.6 48.8 38.0 33.6 44.1 43.7 Current work status of reference person Working for someone else 53.4 53.9 58.0 53.5 53.2 54.9 53.7 45.8 43.9 50.4 51.2 Self-employed 29.4 47.5 45.3 47.5 42.8 44.3 48.9 40.4 42.6 46.1 47.3 Retired 18.3 25.3 25.9 21.0 24.0 25.9 28.2 25.4 27.9 32.7 33.3 Other not working 20.6 29.2 36.8 38.7 32.6 41.0 36.9 35.5 23.8 28.9 37.8 Current occupation of reference person Managerial or professional 53.6 51.3 51.8 53.3 47.3 50.8 52.7 44.6 42.1 48.7 47.9 Technical, sales, or services 49.8 54.1 56.3 52.2 55.7 54.2 53.2 44.6 45.1 52.9 54.2 Other occupation 45.4 53.0 59.3 52.0 52.3 55.2 53.2 45.7 44.7 47.5 50.9 Retired or other not working 18.8 26.2 28.1 24.0 25.4 28.2 29.6 27.6 27.1 32.1 33.9 Region Northeast 38.1 41.7 43.9 38.7 39.7 46.6 44.3 39.9 37.9 43.7 43.1 Midwest 37.5 42.1 46.4 40.2 43.9 44.7 45.5 37.4 40.3 43.6 44.3 South 38.5 45.2 48.0 46.1 44.7 46.0 43.5 38.2 35.9 43.9 46.7 West 46.0 45.0 50.2 49.9 48.4 47.5 52.4 43.0 40.0 44.3 46.0 Urbanicity Metropolitan statistical area (MSA) 41.6 44.0 48.5 44.7 44.8 46.9 46.3 40.3 38.5 44.1 46.5 Non-MSA 31.4 42.5 39.9 40.4 41.9 42.8 44.8 35.0 35.9 42.5 37.4 Housing status Owner 43.9 46.6 51.1 46.2 44.4 48.8 50.1 43.1 42.0 46.4 47.0 Renter or other 32.2 38.6 40.3 40.0 44.3 40.4 37.3 31.8 30.9 39.5 42.4 Percentile of net worth Less than 25 27.6 38.7 41.5 39.5 45.4 40.3 41.0 36.9 33.4 40.0 44.4 25–49.9 48.2 52.6 55.4 54.8 54.9 58.0 52.9 44.5 44.3 52.1 52.6 50–74.9 49.3 49.6 57.3 48.7 44.9 52.9 51.7 46.2 45.5 53.1 53.0 75–89.9 43.4 39.3 39.5 36.7 39.0 40.3 44.1 36.1 35.1 37.5 39.0 90–100 19.1 25.9 27.9 28.4 22.1 23.5 30.5 20.9 20.9 19.8 20.6
Source: Survey of consumer finance in US (1989-2019)
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SBI Cards and Payment Services Banks
Asset quality prediction requires a much better understanding of the utilization levels
Exhibit 136 gives a perspective of the median utilization of a credit card for the various customer segments for CY2007, CY2010, and CY2018. As would have been exhibited, the median cardholder utilization across tiers over time, especially for consumers in lower tiers is extremely high as we move down the customer quality curve.
Exhibit 136: Utilization of credit limits rises sharply to 80% as we move towards sub-prime Median card holder utilization by credit score, 2007/10/18 (%)
Source: Bureau of Consumer Financial Protection, US
The share of consumers with 100% utilization across all general purpose credit cards for these same years (see exhibit 137). As shown, higher proportion of cardholders were ‘maxed out’ or nearly utilized their full limits in the different credit tiers in 2018 than before or during the recession. ~40% of deep subprime consumers have reached 100% utilization. Cardholders in this situation will find it difficult to make credit card transactions.
Exhibit 137: Deep sub-prime has the highest share of customers with 100% of limits utilized Share of cardholders with 100% utilization within various customer segments, 2007/10/18 (%)
Source: Bureau of Consumer Financial Protection, US
The utilization perspective
We looked at three major credit card spending geographies (USA, Australia and New Zealand) to get a perspective on the average utilization of a credit and the downside risk it emerges during a slowdown. The average card utilization has been broadly similar across the three countries (see exhibit 138-143).
No major signs of spike in spending during a slowdown. Given that the credit card is a line of credit where the timing of utilization of the card is unknown to the card issuer, there is always a possibility of risk that is asymmetric in nature. This stems from the belief that the card owner is more likely to spend the card at a time when the liquidity constraints are high, especially during a slowdown. However, data from the three countries that we have been able to analyze does not show this characteristic. We have had two major cycles (late 1990s – a dotcom bubble or crisis that hit emerging markets which had an impact on the overall slowdown in world economy), the second being global financial crisis (late 2000) and one that is unfolding today (Covid).
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Banks SBI Cards and Payment Services
Of the various explanations that could explain this, we believe that there could be a few major reasons: (1) Potential borrowers have either very limited headroom (‘maxed out their spending limits’) in their card leaving little choices but to either default or keep paying the minimum installment that is due for the month. (2) Borrowers, especially those above sub-prime have started to pull back spending which results in lower utilization of the card while lenders may not have necessarily cut back their limits even if they are allowed to do so. In a sense that the response time for lenders to cut limits is much slower as compared to pace at which borrowers have cut back spending. (3) Borrowers have started to pay down their outstanding amount to cut back personal leverage.
Changes in limits, as expected, closely follow the cycle. When we look at the growth in outstanding limits, the changes largely reflect the underlying economic trend. We note the overall credit limits slowed sharply for a few years after 2000 but as the economic cycle recovered and lenders saw an increase in spending, growth in limits started to accelerate. A similar trend was visible in the pre and post global financial crisis.
Exhibit 138: Card utilization is stable at ~20-25% levels in the Exhibit 139: A bit of aggression in enhancing overall limits as past decade economic recovery picks up Card utilization in US, calendar year-ends for the credit card business, Growth in balances and limits in US for the credit card business, 1999-2020 (%) 1999-2020 (%)
40 Balance Limit 24 32 12
24 0
16 -12
8 -24
0 -36
2QCY00 3QCY01 4QCY02 1QCY04 2QCY05 4QCY07 1QCY09 2QCY10 3QCY11 1QCY14 2QCY15 3QCY16 4QCY17 2QCY20 2QCY01 2QCY02 2QCY04 2QCY05 2QCY06 2QCY07 2QCY09 2QCY10 2QCY11 2QCY12 2QCY14 2QCY16 2QCY17 2QCY18 2QCY19 3QCY06 4QCY12 1QCY19 2QCY03 2QCY08 2QCY13 2QCY15 2QCY20 1QCY99
Source: Household debt and Credit Report, US Federal Reserve Source: Household debt and Credit Report, US Federal Reserve
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Exhibit 140: Card utilization is stable at ~30% levels in the past Exhibit 141: A bit of aggression in enhancing overall limits as decade economic recovery picks up Card utilization in New Zealand, calendar year-ends for the credit card Growth in balances and limits in New Zealand for the credit card business, 1992-2020 (%) business, 1992-2020 (%)
35 Total credit limits Total advances outstanding 33
28 22
21 11
14 0
7 (11)
- (22)
Apr1992 Apr1994 Apr1996 Apr2000 Apr2002 Apr2004 Apr2006 Apr2008 Apr2012 Apr2014 Apr2016 Apr2018 Apr2020 Apr1998 Apr2010
Aug1992 Aug1994 Aug1996 Aug2000 Aug2002 Aug2004 Aug2006 Aug2010 Aug2012 Aug2014 Aug2016 Aug2020 Aug2008 Aug2018 Aug1998
Source: Reserve Bank of New Zealand Source: Reserve Bank of New Zealand
Exhibit 142: Card utilization is stable at ~20-25% levels in the Exhibit 143: A bit of aggression in enhancing overall limits as past decade economic recovery picks up Card utilization in Australia, calendar year-ends for the credit card Growth in balances and limits in Australia for the credit card business, business, 1999-2020 (%) 1999-2020 (%)
40 Balance Limit 20
32 10
24 0
16 -10
8 -20
0 -30
Jul-2009
Jan-2004 Jan-2005 Jan-2006 Jan-2007 Jan-2009 Jan-2010 Jan-2011 Jan-2012 Jan-2013 Jan-2015 Jan-2016 Jan-2017 Jan-2018 Jan-2019 Jan-2003 Jan-2016 Jan-2003 Jan-2008 Jan-2014 Jan-2020
Jun-2008
Oct-2012
Feb-2004 Feb-2017
Apr-2006 Sep-2011 Apr-2019
Dec-2014
Nov-2013
Mar-2005 Mar-2018
Aug-2010 May-2020 May-2007
Source: Reserve Bank of Australia Source: Reserve Bank of Australia
Utilization rates peak around 40-45 years of age
We look at a mature market such as US to assess the increase in credit limits and its utilization thereof as credit card-holders age and see their incomes rise (see exhibit 144 and 145). There is one such study conducted by the Consumer Financial Protection Bureau (link) looking at credit card utilizations over the customer lifecycle. Key takeaway for us in this context is average credit card limits increase by over 4X between age 20 and 30, and continue to increase at a slower pace after age 30. Credit utilization declined gradually from age 20 to age 80. On average, 20-year-olds use over 50% of credit whereas 50-year-olds still use 40% of their credit. Credit utilization falls to below 20% by age 70.
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Banks SBI Cards and Payment Services
Exhibit 144: Credit card debt peaks out around 40 years of age Exhibit 145: Credit card utilization levels decline with age Varation of credit card usage levels with age (000's) Variation of credit card utilization levels (credit card debt to limit ratio) with age (X)
Notes: (1) Individual curves represent various birth year cohorts. Notes: (1) Individual curves represent various birth year cohorts. Source: Consumer Financial Protection Bureau (US), Kotak Institutional Equities Source: Consumer Financial Protection Bureau (US), Kotak Institutional Equities
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THE ECONOMICS OF CREDIT CARD OPERATION There is not a lot of public information on the credit card profitability for international and Indian players as many large players have this business within the bank where separate data is not easily available. We looked at select standalone credit card companies along with various regulatory filings to get a perspective of this business. We believe that this business has been historically delivering better return on a through-the-cycle basis for all players.
While the data is not easily available, we have reasons to believe that the credit card business is an extremely profitable business for most lenders even on a risk-adjusted basis. In this section, we look at the various revenue lines and credit costs.
Exhibit 146 shows the profitability of credit card companies. A three-decade average profitability of this business shows a RoA of 3.7%. RoAs expanded before the global financial crisis which has started to trend back to closer to average levels.
Exhibit 146: The credit cards business is a profitable business in the US RoA of credit card companies in the US, December fiscal year-ends, 1986-2017 (%)
9
6
3
0
-3
-6
1986 1993 1994 1995 1996 1997 1998 2006 2007 2008 2009 2010 2011 1988 1989 1990 1991 1992 1999 2000 2001 2002 2003 2004 2005 2012 2013 2014 2015 2016 2017 1987
Source: US Federal Reserve
Exhibit 147 and 148 shows the return on equity for the standalone listed players. Note that the US probably has the largest number of standalone credit card players. In most of the other markets, this is part of the bank’s lending portfolio. There are some differences in the business model where some players may have diversified their book over time to other products like SME lending while a few build a complete product suite on payments which includes the issuing as well as acquisition businesses.
There are several differences in the choices taken by these players. For example, American Express (AMEX) is a more payment related business while the others have chosen to have a relatively higher contribution from the lending business.
However, which way we look at these models, it is fair to assume that the credit card business has delivered superior returns. This is superior to most of the other credit products.
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Banks SBI Cards and Payment Services
Exhibit 147: RoE for US credit card companies have been in the range of 15-28% on average Return on equity for standalone credit card companies, calendar year-ends, 1995-2019
American Express Capital One
Average Return on Equity Average Return on Equity 48 32
40 24
32 16 24 8 16
0 8
0 -8
2001 2007 2013 2019 1995 1997 1999 2003 2005 2009 2011 2015 2017
1997 2003 2009 2017 1995 1999 2001 2005 2007 2011 2013 2015 2019
Discover Financial Services Synchrony Financial
Average Return on Equity Average Return on Equity 40 56
48 32 40 24 32
16 24
16 8 8
0 0
2007 2010 2013 2016 2019 2006 2008 2009 2011 2012 2014 2015 2017 2018
2010 2017 2018 2012 2013 2014 2015 2016 2019 2011 Source: Bloomberg
Interest rates has been mostly sticky for the credit card business across the world
In most markets, interest rates on credit cards have been quite sticky and less responsive to changes in policy rates. There have been several studies on this issue and the results have been broadly uniform that despite competition, it is hard to break the interest rates. The earliest study that we have been able to get was in 1991 which discusses this issue of “The failure of Competition in the Credit Card Market, that high number of players has not necessarily created a competitive environment for credit cards”. The recent reports from the Federal Reserve in US broadly suggest that this stickiness has continued even till today (see exhibits 148 and 149). Note that the interest rates and fees have been areas of study by the government across various time periods. However, the market players have been able to keep interest rates quite high. This is true even in India (see exhibit 150). The rationale for a high interest rate for credit card business stems from a few factors – (1) cost of funds on a transfer pricing basis tends to be quite high, (2) cost of operations is quite high. The acquisition and activation costs in this business are high, (3) cost of credit is high relative to other business. Note that the ticket size is not too high and banks have to constantly evaluate the cost of pursuing recovery as compared to writing it off and (4) reports also suggest that a higher share of customers who pay off their dues implies that the cost of the interest free period has to be subsidized by the customers who chose to delay payment.
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Consumers don’t actively look at interest rates while choosing a credit card as they believe that they expect to pay it off at the end of the period. This behavior appears to be similar to MFI. The key utility of the card is its payment function and credit function.
Exhibit 148: US credit card industry is an example where the Exhibit 149: Interest rates charged has usually been less interest rates has been mostly unresponsive to cost of funds responsive to policy or other interest rates Movement of credit card interest rates and cost of funds for US Quarterly average interest rates on credit card accounts, 1996-2019 players, 1980-1990 (%) (%)
Source: Report to the Congress on the Profitability of Credit Card Source: The Failure of Competition in the Credit Card Market Operations of Depository Institutions
Exhibit 150: Interest rates on credit cards are higher than other forms of credit Interest rates offered by select credit card players in India
Credit card issuer Interest rate (%) Notes SBI Card 40.2 Rate is 30% for secured cards HDFC Bank 40.8 Maximum rate is shown here ICICI Bank 40.8 Rate shown for Emeralde Credit Card Axis Bank 49.4 Rate shown for Select Credit Card RBL Bank/ Bajaj Finserv 48.0 Maximum rate is shown here Citi Bank 42.0 Rate shown for Cash Back Credit Card American Express 42.0 Rate is uniform
Source: Company
The payment fees and the negative outcome fees
One of the most challenging aspects of forecasting in credit card business is the non-interest income. There is a fairly long list of fees that entails each credit card company. It is not restricted to interchange as it is one of the many fee income drivers for the card issuer. We can broadly break up the fee income into three broad categories (see exhibit 151). There are three kinds of negative fees: late fees, over-limit fees and cash advance fees. Some of the other fees include annual fees, balance transfer fees, foreign transactions.
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Banks SBI Cards and Payment Services
Exhibit 151: We are broadly breaking credit card fees in three major buckets Fees can be broken into different buckets
Fees
Easier to understand Cost (Rs/%) Negative outcomes due to customer choices Cost (Rs/%) Others Cost (Rs/%) Annual fees 1,000-10,000 Cash advance / NEFT drawdown 2.50% Reward redemption 100 Interchange/MDR 1-2.5% EMI conversion 100 Duplicate statements 10 Foreign exchange 3.5% Late payment 0-1,300 Railway ticket surcharge 1-2% Payment return 400-500 Fuel surcharge 1-2% Cash processing of card dues 100 Re-issue of cards 100 Balance transfer 1-2% Loan processing 1% Pre-closure of loans 3%
Source: Company, Kotak Institutional Equities
Late fees. A late fee is charged when the borrower makes a payment beyond the due date. The late fees can range from Rs100 to Rs1,300 across players and could be a function of the statement balance. A study on late fees is not necessarily a reflection of the underlying economic conditions but can be more of a behavioral phenomenon. The study on the US credit card market suggests that customers tend to pay lot more fees immediately in the initial stages of their account life. As they have better understanding of the charges, it tends to drop sharply.
EMI conversion charges. Banks allow certain types of transactions to be converted to EMI by the cardholder. This would be ~Rs100/transaction at an interest rate that is usually lower than rolling over the underlying credit.
Over limit fees. This is a fee that is charged to the card holder when the borrower exceeds limit that is available on the card. The over limit fees can be a function of the total balance that exceeds the limit or a minimum of Rs500.
Cash advance fees. All card holders have the option to withdraw cash. However, card issuers generally believe that card holders who take this option are quite risky as they may have exhausted all other options to raise cash. The cardholder is charged 2.5% or a minimum amount. There is usually an upper limit for the amount that can be withdrawn which would be Rs12-15,000/month.
. There is an additional feature in cards these days where borrowers can get this directly to their account as well within 2 days of request. The interest charged is ~2.5% with a processing fee of 1.5%.
. Exhibit 152 shows the growth in cash withdrawals over time. A higher growth in cash withdrawal is not a positive indicator as we have seen with several countries that have gone through a credit card lending issue.
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Exhibit 152: Growth in cash withdrawals has slowed down in the last few years Cash withdrawals from ATM using credit cards, March fiscal year-ends, 2013-20 (Rs bn)
Cash withdrawals on credit cards (LHS) Growth (RHS) 50 60
40 45
30 30
20 15
10 0
0 (15) 2013 2014 2015 2016 2017 2018 2019 2020
Source: Company
Balance transfer fees. Balance transfer allows a credit card holder to transfer other credit card balances to another card. The card issuer can provide an easy payment option and at lower interest rates. There is usually a limit on the amount that can be done through balance transfer which is a function of the outstanding limit on the card. For example, SBIC allows up to 70% of the available credit limit to be used under balance transfer. The borrower can then choose to pay on EMIs. The interest rate tends to be lower than the normal rate to roll over. For example, this could be 0.75%/month if the cardholder chooses a 3-month plan and 1.25%/month if the cardholder chooses a 6- month plan. Overall, the bank can charge fees (1-2% of loans) for this service.
Interchange fees. A typical transaction in a credit card is as follows. The credit card is swiped through an electronic terminal on the merchant’s counter which is usually through a POS machine: (1) The transaction and cardholder details are transmitted to the merchant’s financial institution (the acquirer). (2) If the acquirer is also the issuer, the transaction can be authorized internally and the authorization is returned to the merchant. (3) If the issuer is another institution, the acquirer routes the transaction usually through a ‘switch’ facility provided by the credit card scheme. The issuer either authorizes or declines the transaction and a message is sent back to the acquirer which is then transmitted to the merchant. The cardholder’s available credit limit is adjusted immediately to reflect the current transaction.
There is an overall cost attached to undergo this transaction which essentially determines the interchange costs or the merchant discount rates. The cost benefit of this fees helps in building the market. If the merchant believes that the overall cost (merchant discount rate charged) is higher than the perceived benefit (accepting in cash or other format of payments or risking losing marginal sale volume given the cost), then it would be difficult for the card market to grow even if the acquirer is issuing a lot of cards which they perceive is profitable. The interchange fees are agreed jointly by financial institutions. It could vary by the card issued and the nature of the point of sale as well.
The interchange fee is not a single number and it varies according to various parameters. These would include: (1) Merchant categories – a grocery store transaction would be different to that in services like airline ticketing. (2) Type of credit cards being used. Cards that have a higher reward points is likely to have a higher interchange fees. (3) Processing method. A card-not-present or a contactless card is likely to have a different interchange fees.
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Banks SBI Cards and Payment Services
Others.
. Annual fees. This would range from Rs0-10,000/card annually (including at the time of origination of the card). Most card issuers use this primarily to improve the card activation rates. Also, most card issuers would have schemes that gives this back subject to specific spends achieved by the customer.
. Foreign exchange fees. The bank would charge ~3.5% as mark-up but could vary depending on the nature of the card.
. Payment fees. Several card issuers charge (cash or check) and other processing fees on their cards.
Exhibit 153 shows the revenue mix across the various standalone international credit card companies. American Express has a model that is different than that of the rest. This company has the highest share of non-interest income in its revenue mix. The other players have seen changes to their business model over time but they all have a much higher share of net interest income as compared to American Express. Broadly these reflect choices that each company makes in what they believe are best suited for them.
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SBI Cards and Payment Services Banks
Exhibit 153: Amex drives a larger share of revenues through fees while the others drive through interest income Break-up of revenues across players, calendar year-ends, 1995-2019 (%)
American Express Capital One
NIM Non-interest NIM Non-interest 100 100
80 80
60 60
40 40
20 20
0 0
1995 1997 2009 2011 1999 2001 2003 2005 2007 2013 2015 2017 2019
2005 2007 2017 2019 1995 1997 1999 2001 2003 2009 2011 2013 2015
Discover Financial Services Synchrony Financial
NIM Non-interest NIM Non-interest 100 100
80 80
60 60
40 40
20 20
0 0
2011 2012 2013 2014 2015 2016 2017 2018 2019
2006 2010 2014 2018 2007 2008 2009 2011 2012 2013 2015 2016 2017 2019
Source: Bloomberg
The business operates at a high cost structure across most players
One of the key aspects of the credit card business is the cost structure. Unlike other lending or payment products, the cost of running this business is quite high. However, lenders are quite invested in this product given the high share of contribution to overall profits to the firm. The overall cost structure is a function of the model that is being chosen with a high share of transactors would result in lower lending income and there is a constant need to incentivize the card holder to pay through the lender’s credit card. Models which have a higher share of lending income tends to have a lower cost-income but there is an additional layer of risk that comes in the form of provisions for the bad loan customers. Exhibit 154 shows the cost structure that varies for American Express which is the highest to the rest of the players where there is a higher share of lending business as well.
We can broadly break up the costs into three major parts. The advertising and marketing costs, reward points costs and others.
Advertising and marketing costs. There are broadly three major areas of costs in this segment. (1) Origination costs. (2) Marketing costs. (3) Partnership costs on co-branded cards.
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Banks SBI Cards and Payment Services
. Origination costs. The origination costs can be broken into two parts, at least when we look at the Indian platform. These costs are (1) internal when the cards are sourced through the lenders databases and (2) channel partners when they source it through open platforms. The internal costs are lower as the cost of acquisition of these clients are lower for the originator as it is a cross sell to a customer where the lender has already established his/her credibility. The cost of reaching to these clients is lower as there is a relationship already established by the lender. The external costs are higher considering that the channel partner has choices on partnerships given that the product offering is simple and lacks serious differentiation apart from the limits offered to a client or reward point exchange platform. The channel partner has frequent marketing campaigns which is expensive. These channels tend to have a much higher rejection rates as well which needs to be reimbursed through higher costs.
. The cost can further be broken into two broad segments based on the type of cards being originated. The premium cards or cards where the customer is making an annual payment carries a higher origination costs while the low fee or free annual fee cards carry a much lower origination costs as the profitability is quite different between the two.
. The economics of co-branded cards are not similar. These costs could vary based on the nature of sourcing, platform, nature of the co-brand partner and the relationship that is brought to the customer/lender/partner. Most co-branded cards are in the travel, entertainment, grocery/supermarkets and fuel segments. We are also seeing cards with online websites in recent years. In India, we note card issuers have tied up with banks that don’t have a credit card line on a co-branded relationship basis.
Reward points. One of the most important features that differentiates credit card with other forms of payment is the reward point program. Note that the customer pays the same cost for the product irrespective of the instrument used to make the payment. However, it is only credit cards and to a much smaller extent, debit cards, which offer rewards to the customer. Given the indifference in costs (a discount can always be provided by the seller of goods if purchased on cash) for making the transaction, there is a value attached to spending through a credit card. In a simple explanation, the seller is either forced to increase the cost of the product to all the customers or would have to absorb the cost of the credit card transaction through a lower overall margin in the business, essentially looking at it as another cost of running the business.
An interchange fee is a transfer from a merchant’s bank to a consumer’s bank when a card transaction takes place. In the absence of a transfer from merchants or their banks to consumers or their banks, however, a card transaction will not be feasible, since the consumer’s bank cannot cover its costs by charging the consumer. Merchants can ill afford to refuse card payments as it would entail a loss of business, and banks exploit this by setting high interchange fees. As interchange fee levels are typically agreed upon collectively by banks, they determine a lower bound for merchants’ cost of receiving payment by card.
Others. These would include cost to maintain the entire infrastructure of payments. Unlike other businesses, there is a reasonably large share of employees needed for business intelligence. These units help in identifying opportunities and risks in the business.
The business has a higher share of variable costs as compared to other businesses
When we break the costs in two categories. The credit card business has a higher share of variable costs as compared to fixed costs. The cost of origination or spend-related expenses is largely variable in nature. Lenders can choose to step-up origination when the profitability is higher which is usually reflected through generally better economic conditions. This is also reflected in the spending behavior of existing card holders as well. The throughputs tend to be much higher during this part of the economic cycle. The reverse is usually observed when the economic cycle has reversed.
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Exhibit 154: Lenders with a high share of transactors tend to also have a higher share of cost-income ratio Cost-income ratio for leading US credit card companies, calendar year-ends, 1995-2019
American Express Capital One
Average Cost-income Average Cost-income 80 75
76 68
72 61
68 54
64 47
60 40
1997 2003 2009 2015 2017 1995 1999 2001 2005 2007 2011 2013 2019
1999 2005 2013 2019 1995 1997 2001 2003 2007 2009 2011 2015 2017
Discover Financial Services Synchrony Financial
Average Cost-income Average Cost-income 55 50
50 45
45 40
40 35
35 30
30 25
2011 2012 2013 2014 2015 2016 2017 2013 2014 2006 2007 2008 2009 2010 2018 2019 2010 2011 2012 2015 2016 2017 2018 2019
Source: Bloomberg
Asset quality: forecasting challenges especially with minimum installment option
Unlike a typical retail product where the installment expected from the borrower is well defined, a credit card is quite unique. Secured lending products like a housing or auto or even personal loans have an EMI option. However, a credit card is quite unique as there is an open relationship with a borrower and it hard to predict their spending pattern or repayment behavior. An issuer who does not have enough evidence of the customer profile could find it challenging to build the credit risk of the lender. Further, the ability to have a continuous update of the customer’s income profile is not possible. Hence, lenders can only be imperfect in their assessment of the credit risk. Past income and credit history may serve little purpose if there is a meaningful change in borrowers’ repayment profile. On the other hand, credit card is probably one of the smallest obligations to a lender.
Despite the high interest rates charged for borrowers and a higher exposure of lending to customers that are typically vulnerable to a slowdown, credit card has been an excellent business. Exhibits 155 and 156 show this book for US, New Zealand and Hong Kong. From a risk perspective, this book tends to have the highest impairment ratios as compared to all other retail portfolios.
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Banks SBI Cards and Payment Services
Exhibit 155: Credit card delinquency have had the highest through-the-cycle delinquency ratios 90+ days past due by loan type, calendar year-ends, 1999-2020 (%)
Mortgage Auto Credit card All 16
13
10
6
3
0
1QCY99 4QCY99 3QCY12 2QCY13 1QCY14 4QCY14 3QCY15 2QCY16 1QCY17 4QCY17 3QCY18 2QCY19 1QCY20 2QCY01 1QCY02 4QCY02 3QCY03 2QCY04 1QCY05 4QCY05 3QCY06 2QCY07 1QCY08 4QCY08 3QCY09 2QCY10 1QCY11 4QCY11 3QCY00
Source: Household debt and Credit Report, US Federal Reserve
Exhibit 156: New Zealand has a much lower impairment ratio as compared to US 90+ days past due by loan type, calendar year-ends, 1999-2020 (%)
1.5
1.2
0.9
0.6
0.3
-
2007 2008 2009 2010 2010 2012 2013 2015 2015 2017 2018 2020 2020 2008 2009 2011 2011 2012 2013 2014 2014 2016 2016 2017 2018 2019 2019
Source: Reserve Bank of New Zealand
Charge-offs tends to reflect the true picture than impairment ratios
Charge-offs tends to be a more representative picture of the loan book. Data for US (see exhibit 157) and Hong Kong (see exhibit 158 and 159) shows that this ratio tends to meaningfully higher the delinquent ratios reported. Credit cards repayment has a unique challenge as the customer can (1) pay an amount somewhere between the minimum installment and full installment that is due rather than default, (2) choose to amortize the outstanding loans or specific transactions for a period given by the lender and (3) default. A customer who chooses to pay the minimum installment can choose to pay high interest till the time the borrower fails to do so. It is only after this default that the lenders start to build provisions. There are regulations in various countries where banks are supposed to start charging off these defaulters after certain billing cycles (typically 6 billing cycles).
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Exhibit 157: Charge-offs tend to be higher than delinquency ratios Delinquency and charge-offs on credit card loans across all US commercial banks, 2QCY92 onwards (%)
Charge-offs Delinquencies 12.0
9.6
7.2
4.8
2.4
-
2QCY92 2QCY94 2QCY96 2QCY98 2QCY00 2QCY02 2QCY04 2QCY06 2QCY08 2QCY10 2QCY12 2QCY14 2QCY16 2QCY18 2QCY20
Source: US Federal Reserve
Exhibit 158: Charge-offs have been >5X of delinquent ratios Exhibit 159: Delinquency ratios have been lower in cards Charge-offs as a share of loans, calendar year-ends, 2001-20 (%) portfolio Delinquency as a share of loans, calendar year-ends, 2001-20 (%) 20 2.0
16 1.6
12 1.2
8 0.8
4 0.4
0
-
4QCY01 4QCY02 4QCY03 4QCY04 4QCY06 4QCY07 4QCY08 4QCY09 4QCY10 4QCY12 4QCY13 4QCY14 4QCY15 4QCY16 4QCY18 4QCY19 4QCY11 4QCY17
4QCY05
4QCY01 4QCY03 4QCY04 4QCY05 4QCY06 4QCY08 4QCY09 4QCY10 4QCY11 4QCY13 4QCY14 4QCY15 4QCY16 4QCY18 4QCY19 4QCY07 4QCY12 4QCY17 4QCY02 Source: Hong Kong Monetary Authority Source: Hong Kong Monetary Authority
The minimum installment due challenge. There is a very important relationship that makes the borrower look at the credit card relationship very seriously. For a credit constrained borrower or a borrower who has had an unexpected shock in his/her cash flow would always prefer having a credit card even if the interest rates are high. The cost of maintaining a relationship is quite minimal as there is a need to only pay the minimum installment and not have an adverse score.
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In a study conducted in the US, the authors build their argument on the role played by minimum installment. Minimum installment refers to the smallest payment necessary to remain current on an account in a given month. There does not appear to be any specified rule or guideline that defines this minimum payment but we believe that this is at the discretion of the credit card issuers. Note that consumers who fail to pay the minimum installment incur fees, changes in interest rates, credit score damage, and credit supply reductions. These penalties provide strong incentives for liquidity-constrained borrowers to pay at least the minimum. Several studies suggest that the customers don’t take rational decision when it comes to repayment of debt. This makes the analysis challenging to understand the riskiness of the book from a lenders perspective. Borrowers may choose to pay the minimum installment for an extended period of time. They may not necessarily be averse to pay a significantly higher cost as the absolute cost in terms of money is not high. Note that borrowers can maintain a relationship by paying only the minimum installment due for a significantly long time.
Ability to convert to an amortizing plan as suggested by the lender. The lenders give borrowers an option to convert some part of their outstanding dues within certain period (converting into an EMI) which gives a lot more headroom to repay the debt.
Exhibits 160 and 161 show the overall provisions and charge-offs for the various listed standalone credit card companies. These exhibits show the cyclicality in business along with fairly steep and rapid rise during a slowdown. We read less into the provisions made by American Express in relation to the other players primarily as the lending book is relatively smaller. The charge-offs tends to be 400-500 bps on a through-the-cycle basis.
Exhibit 160: The overall LLPs tends is higher on absolute basis for business that has a higher share of revolvers Loan-loss provisions for leading credit card issuers, calendar year-ends, 1985-2019 (%)
American Express Capital One
Average LLP Average LLP 16 10
13 8
10 6
6 4
3 2
0 0
1997 2003 2011 2017 1995 1999 2001 2005 2007 2009 2013 2015 2019
1997 2003 2009 2015 2017 1995 1999 2001 2005 2007 2011 2013 2019
Discover Financial Services Synchrony Financial
Average LLP Average LLP 12 8.0
10 6.4
8 4.8 6 3.2 4
1.6 2
0 0.0
2006 2009 2011 2014 2017 2010 2013 2014 2017 2008 2010 2012 2013 2015 2016 2018 2019 2011 2012 2015 2016 2018 2019 2007
Source: Bloomberg
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SBI Cards and Payment Services Banks
Exhibit 161: Charge-off is well within the thresholds of income earned for all leading card issuers Charge-off for leading credit card issuers, calendar year-ends, 1985-2019 (%)
American Express Capital One
Average Charge-off (net) LLP Average Average LLP Charge-off (net) Average 16.0 9.0
12.8 7.2
9.6 5.4
6.4 3.6
3.2 1.8
0.0 0.0
1997 2003 2009 2015 2017 1995 1999 2001 2005 2007 2011 2013 2019
1999 2005 2013 2019 1995 1997 2001 2003 2007 2009 2011 2015 2017
Discover Financial Services Synchrony Financial
Average Charge-off (net) LLP Average Average Charge-off (net) LLP Average 10.5 6.0
8.4 5.5
6.3 5.0
4.2 4.5
2.1 4.0
0.0 3.5
2013 2014 2015 2016 2017 2018 2011 2014 2018 2006 2007 2008 2009 2010 2011 2012 2019 2012 2013 2015 2016 2017 2019
Source: Bloomberg
Valuations reflect this superiority in business model
Exhibit 162 and 163 shows that the business has inherent strengths to demand a higher valuation. Amex trades at a superior valuation compared to others, which is expected, given that the nature of their business is more skewed towards the less risky payment business while the others have a higher share of lending business.
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Banks SBI Cards and Payment Services
Exhibit 162: American Express continues to trade at a premium Exhibit 163: American Express continues to trade at a premium to peers to peers PBR (rolling 12-month forward book), November 2006 onwards (X) PER (rolling 12-month forward earnings), November 2006 onwards (X) American Express Capital One Synchrony Discover American Express Capital One 7.0 Synchrony Discover 25
5.6 20
4.2 15
2.8 10
1.4 5
0.0
0
Nov-07 Nov-08 Nov-09 Nov-10 Nov-12 Nov-13 Nov-14 Nov-15 Nov-18 Nov-19 Nov-20 Nov-11 Nov-16 Nov-17
Nov-06
Nov-06 Nov-07 Nov-08 Nov-09 Nov-10 Nov-11 Nov-12 Nov-13 Nov-14 Nov-15 Nov-16 Nov-17 Nov-19 Nov-20 Nov-18 Source: Kotak Institutional Equities Source: Kotak Institutional Equities
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SBI Cards and Payment Services Banks
THE INDIA CARD BUSINESS The previous decade has seen a remarkable resurgence in the credit card business in India led by strong issuance of POS terminals and steady shift in purchase behavior of individuals in the online platform. Lenders, with better data, are offering strong product propositions for transactors, buy now pay later (EMI products) and revolvers. We see solid growth in this platform over the medium term as penetration levels are still low.
A solid growth in card spends led by healthy card issuances
The credit cards industry has been growing at a pretty rapid pace in recent years with 3/5/10-year CAGR of 12%/22%/25% for cards in force fueling consistent spends growth of ~30% over the 3/5/10-year timeframe (see exhibit 164-166). Coming off a short and painful episode during 2008-10, banks were cautious in the few following years. However, growth started to accelerate from FY2016 onwards. A few factors potentially driving this growth are (1) rise in retail consumption supported by ease of financing, (2) willingness of banks to cross-sell to their large customer base where risk is lower and (3) expansion of customer funnel with rise in originations among new-to-credit and younger age groups.
While aggregate metrics have grown at a brisk pace over the past decade, per card or transaction based metrics have seen growth flatten out in recent years. This is potentially driven by greater share of card additions in the younger age groups with much lower credit limits. We explore these and other growth dynamics in the section.
India currently has ~58 mn active credit cards issued to ~30 mn customers. We try to scope the growth potential of the credit card industry through (1) current credit card ownership and comparing with proxies of potential target segment and (2) retail spending at the broad economy level and comparing with spends flowing through card swipes.
Exhibit 164: Faster growth for credit cards issued and spends compared to per card metrics 10/5/3-year CAGR for credit cards, spends, transactions, spends per card and transactions per card, March fiscal year-ends, 2010-20
10Y CAGR 5Y CAGR 3Y CAGR 35
28
21
14
7
- Credit cards (#) Spends (Rs) Transactions (#) Spends per card (Rs) Txn. per card (#)
Source: RBI, Kotak Institutional Equities
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Banks SBI Cards and Payment Services
Exhibit 165: Sharp rise in credit cards in recent years… Exhibit 166: …driving increase in spends Credit cards issues and yoy growth, March fiscal year-ends, 2007- Credit cards spends and yoy growth, March fiscal year-ends, 2007- 1HFY21 1HFY21
(# mn) Credit cards YoY (RHS) (%) (Rs bn) Spends YoY (RHS) (%) 60 30 8,000 45
48 18 6,400 36
36 6 4,800 27
24 (6) 3,200 18
12 (18) 1,600 9
- (30) - -
2012 2013 2014 2015 2019 2020 2010 2011 2016 2017 2018
2008 2009 2011 2012 2014 2015 2017 2018 2020 2007 2010 2013 2016 2019 1HFY21 1HFY21
Source: Kotak Institutional Equities Source: Kotak Institutional Equities
India’s credit card penetration remains fairly low (see exhibits 167 and 168) compared to other countries based on card ownership measured as (1) number of cards per 100 people and (2) share of population above 15 years holding a credit card (see exhibit 169). Interestingly, there is a strong correlation between country’s per capita GDP and credit card ownership. Whether India follows a path similar to other countries remains to be seen, but a low base and supportive macro trends (smart phone/internet affordability, higher convenience, urbanization) will provide tailwinds over the medium-term to support card additions as well as growth in spends through cashless means.
Exhibit 167: Credit card penetration still quite low in India Exhibit 168: Penetration has almost tripled over FY2014-20 Credit card penetration across countries, calendar year-end, 2019 (%) Credit card penetration in India, March fiscal year-ends, 2014-20 (%)
350 4.5 4.3 337 280 3.5 3.6 267 262 2.8 210 225 215 2.7 2.3 140 1.9 151 1.6 1.7 1.8 1.5 1.4 1.5 105 70 92 79 53 12 7 7 4.0 0.9
-
US UK
India 0.0
Brazil
Japan
Korea China
France
Canada
Australia
Germany
Indonesia
Singapore
2011 2012 2014 2015 2016 2018 2019 2020 2013 2017 Hong Hong Kong Notes: Notes: (1) Credit card penetration is average number of cards per 100 (1) Credit card penetration is average number of cards per 100 people. For Japan and US, credit card penetration is as of 2018. people.
Source: BIS, Kotak Institutional Equities Source: BIS, Kotak Institutional Equities
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SBI Cards and Payment Services Banks
Exhibit 169: Strong correlation between GDP per capital and credit card ownership Credit card ownership (age 15+, 2017) and per capital GDP (2019) 80
70 Japan R² = 0.69 HK US South Korea UK 60 Australia
50 Germany Singapore 40 France
30 Brazil 20 China
10 India
- Indonesia - 10,000 20,000 30,000 40,000 50,000 60,000 70,000
Source: World Bank, Kotak Institutional Equities
Assessing growth potential for credit cards
We have already explained the market opportunity through the PFCE structure and we look at the credit cards that can be issued in this section through other means. India has close to ~30 mn credit card holders and ~58 mn cards issued, implying nearly 1.8 cards per cardholder. Traditional metrics of cross-country comparison of card holding suggest large untapped market for this product. Our interactions with industry participants suggests India has approximately 350 mn credit bureau records, which reduces to ~200 mn if we exclude microfinance and business loan borrowers. Another way to map this is that India has nearly ~250 mn individuals with over Rs2.5 mn annual income with nearly 200 mn having bureau records. Of this, nearly 70-80 mn are prime-score customers living in larger cities – this forms the potential customer base of today. With 1.8-1.9X cards per person ratio, the potential card base could be around ~150 mn. In comparison, India has ~58 mn cards in force and ~30 mn cardholders. We corroborate the potential size with other macro-economic vectors such as number of tax filing population, income cohorts or household income strata. The market opportunity is quite large but needs to expand beyond the larger cities and salaried segment.
Income tax filings. Income tax data is an imperfect but still useful pointer towards income profile for the country. Data indicates ~48 mn people with income more than Rs250,000 filed income taxes in FY2018 (see exhibit 170). While this number is slightly dated, it has grown at ~25% CAGR over FY2012-18 (see exhibit 171), reflecting expansion of the target addressable market. We understand from third-party aggregator websites (BankBazaar) that minimum salary requirement for most low-income credit cards is close to Rs250,000, indicating a high potential target segment (see exhibit 172).
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Banks SBI Cards and Payment Services
Exhibit 170: Around ~48 mn tax filers have income over Rs250,000 per annum Individual income tax filings and average gross income, assessment year 2019
Number of Average gross annual Income range (Rs) returns income (Rs mn) 0 0 >0 and <=1,50,000 2.4 0.08 >1,50,000 and <= 2,00,000 1.4 0.18 >2,00,000 and <= 2,50,000 3.8 0.23 >2,50,000 and <= 3,50,000 14.3 0.31 >3,50,000 and <= 4,00,000 5.0 0.37 >4,00,000 and <= 4,50,000 4.2 0.43 >4,50,000 and <= 5,00,000 3.8 0.48 >5,00,000 and <= 5,50,000 3.0 0.52 >5,50,000 and <= 9,50,000 11.2 0.71 >9,50,000 and <= 10,00,000 0.6 0.98 >10,00,000 and <=15,00,000 3.0 1.20 >15,00,000 and <= 20,00,000 1.0 1.72 >20,00,000 and <= 25,00,000 0.5 2.22 >25,00,000 and <= 50,00,000 0.7 3.37 >50,00,000 and <= 1,00,00,000 0.2 6.77 >1,00,00,000 and <=5,00,00,000 0.1 17.95 >5,00,00,000 and <=10,00,00,000 0.0 67.84 Above Rs10,00,00,000 0.0 >150 Total 55.3 Above Rs250,000 income 47.5
Source: Income Tax Department, Kotak Institutional Equities
Exhibit 171: Income tax filers with over Rs350,000 annual income has grown at ~25% CAGR over 2012-18 Number of tax filings with annual income above Rs350,000 during the assessment years, March-fiscal year- ends, 2013-19 (# mn)
35.0 33.3
27.2 28.0 22.9
21.0 19.2
14.7 14.0 12.3 9.2
7.0
- 2013 2014 2015 2016 2017 2018 2019
Source: Income Tax Department, Kotak Institutional Equities
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SBI Cards and Payment Services Banks
Exhibit 172: Credit card can be obtained for a salary as low as Rs12,000 per month Indicative list of low income credit cards
Bank Card Minimum salary Self-employed YES Bank Prosperity Reward Plus Credit Card Rs25,000 per month Minimum ITR per year – Rs0.5 mn SBI Card SimplyCLICK / SimplySAVE Rs18,000 per month - HDFC Bank Bharat CashBack / Freedom Card Rs12,000 per month Minimum ITR per year – Rs0.2 mn HDFC Bank Diners Club Rewardz Card Rs30,000 per month Minimum ITR per year – Rs.0.36 mn HDFC Bank Regalia First Card Rs40,000 per month - ICICI Bank MakeMyTrip Platinum Credit Card Rs250,000 net annual income -
Source: BankBazaar, Kotak Institutional Equities
Household income strata. According to a 2019 BCG report (link), India has 90 mn households earning more than Rs500,000 annual income (see exhibit 173), a segment that can potentially be considered as target segment for credit card issuers. There are potential limitations in using this data such as (1) sample size for construction or other assumptions and (2) unavailability of further scrub of the data to see how many of these have salaried or self-employed or based in urban or rural areas. Nonetheless, this does indicate further room for industry to expand the base as the size of the population itself expands by 5-10% each year.
Exhibit 173: ~90 mn households can be a potential target segment Income-wise households category and 10-year CAGR
Category (annual income) Households (# mn) 10-year CAGR Elite (Rs2 mn and above) 9 13% Affluent (Rs1-2 mn) 24 9% Aspirer (Rs0.5-1 mn) 57 6% Potential opportunity for credit cards 90 Next billion (Rs0.15-0.5 mn) 129 2% Struggler (Below Rs0.15 mn) 67 -2%
Source: BCG report, Kotak Institutional Equities
Occupation-income cohorts. We look at the findings of The Household Survey on India’s Citizen Environment & Consumer Economy (ICE 360° survey), covering 61,000 households (see exhibit 174). It is one of the more comprehensive surveys conducted after the 2012 NSSO survey. We presume categories on employment such as businessmen, self-employed professionals, officers/executives and clerical staff, together comprising ~15% of households or ~40 mn households can be considered as immediate potential target addressable market.
However, three-fourths of this pie is self-employed in nature whereas based on data from SBIC and RBL suggests ~70-80% of customer base is salaried in nature (see exhibit 175). This is a common challenge facing all banks – the opportunity set on the self-employed is higher from a customer addition standpoint, but volatile incomes increases the credit risk perception, especially if the issuer bank does not hold the primary deposit account.
To partly address such issues card issuers offer ‘secured credit cards’, i.e. credit cards backed by fixed deposits (see exhibit 176) with credit limit that is around 75-85% of the FD amount that is locked for its tenure. This product offers a solution for customers with irregular income with no credit history or low bureau score. As the customer builds repayment track record, card issuers can relax the requirements.
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Banks SBI Cards and Payment Services
Exhibit 174: Nearly 15% of India’s households are ripe for credit card penetration Household category, share in total households and median monthly income, 2016
Primary occupation of chief wage % share in Median household earner households income (Rs/month) Cultivators & allied activities 22 12,200 Petty traders 4 13,200 Self-employed Self-employed non-professional 5 16,800 Shop owners/businessmen 10 19,400 Self-employed professional 1 21,500 Clerical staff 1 31,000 Salaried Supervisory staff/officers/executives 3 34,779 Grade IV employee (peons, etc.) 16 18,100 Agriculture and allied wage labour 7 9,309 Labourers Non-agriculture wage labour 25 10,472 Others Others (living on pension, rent, etc.) 6 9,697
Source: ICE Survey, Kotak Institutional Equities
Exhibit 175: Share of self-employed customers has risen in recent years to 20-30% Survey results as of 2016 and SBIC/RBL Bank data as of June 2020, (%)
Survey results* SBI Cards RBL Bank
21% 27% 30%
70% 73% 79%
Notes: (1) Survey results refer to mix of households, identified as potential target segment for credit cards.
Source: Company, Kotak Institutional Equities
Exhibit 176: Card offerings against fixed deposit security
Bank Card Fixed deposit required Joining/annual fee Axis Bank Insta Easy Rs20,000 / 80% of FD as credit limit Joining fee: Rs.500; Annual fee: NIL ICICI Bank Coral Rs20,000 Rs500 ICICI Bank Instant Platinum Rs20,000 NIL SBI Card Unnati Rs25,000 First 4 years – NIL; 5th year on – Rs499 YES Bank Prosperity Rewards Plus Rs50,000 Rs350 YES Bank First Preferred Rs300,000 Rs2500 Bank of Baroda Assure Rs25,000 / 80% of FD as credit limit Rs500
Source: BankBazaar, PaisaBazaar, Kotak Institutional Equities
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SBI Cards and Payment Services Banks
Potential to gain spends market share
Level of spends on credit cards lies at the core of the revenue model as it drives spend-based, subscription-based or loan-based revenues (see exhibit 177 and 178). India has seen a secular growth in aggregate overall spends, growing at 10/5-year CAGR of ~30%. However, growth has largely been driven by card additions as against spends/transactions per card. For example, spend per card and transactions per card have grown at 14%/7%/5% and 11%/5%/1% respectively over 10/5-3-year period. This trend is led by incremental additions at the lower end of the curve with lower credit limit and spends.
Unlike developed markets, lack of industry data (e.g. breakup between retail/corporate cards) on break-up of spends across categories makes it challenging to assess future growth drivers. We look at various independent surveys/studies of the Indian market looking at retail consumption breakdown in terms of (1) categories, i.e. groceries, travel, etc., (2) urban vs rural consumption and (3) offline vs online share across spend categories.
Exhibit 177: Spend per card growth has moderated recently… Exhibit 178: …due to consumers making fewer transactions Credit per card and yoy growth, March fiscal year-ends, 2010 Transactions per card and yoy growth, March fiscal year-ends, 2010- 1QFY21 (Rs) Spend per card (Rs) YoY (RHS) (%) (Rs) 130,000 35 (#) Txn per card (#) Value per txn (Rs) (RHS) 40 3,500
104,000 27 32 3,200
78,000 19 24 2,900
52,000 11 16 2,600
26,000 3 8 2,300
- (5)
- 2,000
2010 2013 2014 2015 2016 2017 2020 2012 2018 2019
2011
2010 2013 2014 2016 2017 2018 2020 2012 2015 2019 2011 Source: Kotak Institutional Equities Source: Kotak Institutional Equities
A 2019 BCG report (link) pegs India’s retail consumption at Rs110 tn in 2018 having grown at ~15% CAGR over 2008-18. We note that this is quite close to official data on private final consumption expenditure of Rs112 tn in FY2019 and Rs123 tn in FY2020. The report provides useful insights on nature of retail spending in India. Some of the key takeaways are (Exhibit 179):
Food, housing & consumer durable and travel & communications are three largest segments with nearly two-thirds contribution.
Rural spending in some ways mirrors population distribution with rural contributing ~50% of total retail spends. Metros and tier-1 cities contribute ~20% and rest across tier-2 to tier-4 towns.
85% of total spends occur in the offline mode (probably indicates cash) at unorganized retail, with offline-organized and online contributing 12% and 3%. While online is small share, the 10-year CAGR is 78% compared to 25% for offline-organized and 12% for offline-unorganized.
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Banks SBI Cards and Payment Services
Exhibit 179: Spends on food dominate overall spends with major contribution from rural and offline/unorganized formats Breakup of Rs110 tn retail spends across categories
Others, Online Offline - Rs15 tn , 3% organize 14% d Health, Food, Metro 12% Rs36 tn, Rs5 tn , 12% 5% 32% Education Tier-1 & leisure, 9% Rs7 tn , Tier-2 7% 4% Rural Tier-3 Clothes & 51% footwear, 11% Offline - Rs8 tn, 7% unorgani Tier-4 zed Housing & Transportat 13% 85% consumer ion & durable, communica Rs22 tn , tion, Rs18 19% tn, 16%
Source: BCG report, Kotak Institutional Equities
Card-based spends can have wallet share gains
To assess the further scope for spends growth through the card ecosystem, we compare the card spends (debit/credit) with overall urban and online plus offline-organized spending. Overall card spends in 2018 was ~15% of the overall urban and online plus offline- organized spending, indicating long runway for growth. There is certainly a threat of new modes/technology disrupting credit cards. For example, we have seen rapid and massive adoption of direct account payment options such as UPI which has certainly chipped away market share from cash as well as card-based transactions (Exhibit 180). However, we don’t get further break-up in terms of person-to-person or person-to-merchant to assess market share gains.
Exhibit 180: Comparison of urban and online/organized retail expenditure with card spends Retail expenditure compared with spends on cards, card volumes for April 2019-March 2020 (Rs bn)
Urban consumption Online + offline (organized) Debit card spends Credit card spends 60,000 54,000
50,000
40,000
30,000
20,000 16,800
10,000 5,900 5,900
- Urban consumption Online + offline Debit card spends Credit card spends (organized)
Source: BCG report, RBI, Kotak Institutional Equities
90 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Shift to online purchase provides natural tailwinds…
Increased tendency to purchase goods and services online naturally dovetails into digital payments. Based on a study by BCG, we note the potential share gains for online spends across several categories (Exhibits 181 and 182) especially for the higher-ticket size segments where credit cards can also offer an EMI-facility at the check-out. While the tendency to pay by cash reduces significantly for online purchases, arguably consumers are presented with many more payment options at the checkout i.e. debit card, credit card, net banking, wallets, short-term loans, etc.
Exhibit 181: There is potential for some categories of spends to move digital/online Breakup of spends across categories into offline/online, 2018 (%)
Offline Pure online Online+Offline Pure offline Online
100
80
60
40
20
- Healthcare Grocery Food Apparel Consumer Home Mobile Travel Movie ordering durable furniture phone tickets tickets
Source: BCG report, Kotak Institutional Equities
Exhibit 182: Large ticket items such as travel have a greater share of online purchases Breakup of spends across categories into offline/online, 2018
Occasions/ Spend/occasion Category Online Offline year (Rs) Leisure travel 46% 54% 1.8 15,051 Order-in food 44% 56% 13.8 605 Mobile 35% 65% 0.4 10,860 Apparel 7% 93% 7.2 2,097 Electricals 2% 98% 1.5 718
Staples 1% 99% 17.0 1,966
Source: BCG report, Kotak Institutional Equities
…but online has more competition with other payment modes
Reports by FIS, a global payments company provides very interesting cross-country comparison of payment modes for both offline and online transactions (Exhibit 183). Trends for India (see exhibit 184 and 185) suggest wider distribution of payment mode preferences versus offline transactions where cash still dominates. Credit cards have only gained a marginal share in online transactions but a relatively larger share in the offline transactions. India has seen a phenomenal uptake of UPI as payment mode (probably dominated by offline) for small ticket transactions with growth outstripping cards (Exhibit 186). While credit cards will increasingly compete with other modes, we do see potential for credit card payments to grow as well. Credit cards are still the preferable choice for larger ticket spends as seen from average ticket size - ~Rs3,000 for credit cards compared to ~Rs1,500 for debits cards and UPI.
KOTAK INSTITUTIONAL EQUITIES RESEARCH 91
Banks SBI Cards and Payment Services
Exhibit 183: Online payment space is more competitive across different modes Share of payment modes for online and POS, 2019
2017 2019 80 72 71
64
48 32 32 26 19 19 17 14 16 16 16 12 11 12 12 16 8 9 5 6 5 2 -
-
Cash
Wallet
Others Others
Debit card Debit card
Credit card Credit card Credit
Wallet/digital
Bank transferBank Cash on delivery Cash Card not present / E-commerce Card present / POS
Source: FIS Worldpay, Kotak Institutional Equities
Exhibit 184: Non-POS spends overtook POS after the lockdown Exhibit 185: Huge bump in non-POS spends recently Breakup of credit card transaction value, November 2019 onwards (Rs Breakup of debit card transaction value, November 2019 onwards (Rs bn) bn)
POS Non-POS POS Non-POS 400 700
320 560
240 420
160 280
80 140
- -
Jul-20 Jul-20
Jan-20 Jan-20
Jun-20 Jun-20
Feb-20 Oct-20 Feb-20 Oct-20
Apr-20 Sep-20 Sep-20 Apr-20
Dec-19 Dec-19
Nov-19 Nov-19
Mar-20 Mar-20
Aug-20 Aug-20 May-20 May-20
Source: RBI Source: RBI
92 KOTAK INSTITUTIONAL EQUITIES RESEARCH
SBI Cards and Payment Services Banks
Exhibit 186: UPI has probably gained spend market share from cards Payments through IMPS, UPI, debit cards and credit cards, March fiscal year-ends, 2010-20 (Rs bn)
IMPS UPI Debit cards Credit cards 25,000
20,000
15,000
10,000
5,000
-
2013 2014 2015 2016 2017 2018 2010 2011 2012 2019 2020
Source: RBI, Kotak Institutional Equities
Customer lifecycle is still nascent
Recent growth in the outstanding credit cards is partly driven by adoption and push towards the younger age population as issuing banks have increased focus on expanding customer acquisition filters. With a rise in several payment options (‘pay later’ or installment loans) backed by fintechs/new entrants, banks have also possibly relaxed the age limit to capture the payments opportunity.
Rising share of young with lower limits
A credit card is one of the first credit products (apart from student loans, if any) adopted by young adults as it’s a relatively safer product for the issuing bank which likely also has the salary account of the cardholder. Bureau data from CRIF Highmark suggests nearly 65% of cardholders onboarded credit with a credit card product. In fact, the number of customers opting for a credit card for the first time has grown to 3X between FY2014-19.
As a consequence, bureau data on age-wise sourcing shows a sharp rise in sourcing to the 18-25 age group, rising to ~15% in April-Sep 2019 period compared to ~2% in FY2016 (see exhibit 187). This trend also reflects in the increase in sourcing share of cards with low credit limits (see exhibit 188). Share of cards with KOTAK INSTITUTIONAL EQUITIES RESEARCH 93 Banks SBI Cards and Payment Services Exhibit 187: Increase in share of sourcing from 18-25 age group Sourcing trends by age of borrowers, March fiscal year-ends, 2016-20 (%) >51 36-50 26-35 18-25 100 2 4 7 6 10 14 80 36 51 52 50 48 60 48 40 37 36 34 32 32 30 20 21 12 11 11 10 9 - 2016 2017 2018 2019 Apr-Sep'2019 Outstanding (Sep'2019) Source: CRIF Highmark, Kotak Institutional Equities Exhibit 188: Increase in share of low limit cards Exhibit 189: Large part of outstanding balance in the 26-50 Sourcing trends by card limit, March fiscal year-ends, 2016-20 (%) years bracket with range of ticket sizes across age groups Age-group wise credit card balance and average balance (in Rs’000) Rs100K - 300K Rs50K - 100K Rs25K - 50K per cardholder, as of September 2019 Rs10K - 25K Source: CRIF Highmark, Kotak Institutional Equities Multiple cards highest in the 26-50 age band Part of the process towards market development and penetration involves higher tendency of cardholders to hold more than one card. Nearly 37% of customers in the age group of 26-35 and 34% in the 36-50 age groups have two or more cards (see exhibit 190). The age- wise distribution of cards has a predictable pattern wherein age groups at the peak of incomes or expenditures hold the highest number of cards. Multi-carding is also explained by the need to hold one basic/core card and adding co-branded or specialized cards for specific use cases such as travel & entertainment, ecommerce, etc. Multiple cards potentially bring down the activity levels as well – SBIC and RBL Bank report 30-day active rate of ~55%. 94 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 190: Nearly ~35% of customers in the age group of 26-35 and 36-50 have 2 or more cards Age-wise distribution of number of cards for the industry, as of September 2019 (%) 1 2 3 >3 40 32 24 16 8 - 18-25 26-35 36-50 >51 Source: CRIF Highmark, Kotak Institutional Equities Locations beyond metros driving customer adds The other key industry trend has been the rapid expansion into non-metro locations. According to bureau data, outstanding share of non-metros expanded to ~40% by Dec- 2019 from ~30% in Dec-2017. However, on a fresh sourcing basis, non-metros are already ~50% in FY2019 (see exhibits 191 and 192). Exhibit 191: Areas beyond metro locations have seen sharper Exhibit 192: Nearly ~50% of new card sourcing outside metros growth Sourcing mix of metros/non-metros, March fiscal year-ends, 2016-19 Cards outstanding by location, As of December 2017-19 (# mn) (%) Metro Tier-2 Tier-3 and beyond Metro Non-metro 55.0 100 8.9 44.0 80 37 37 43 48 6.3 11.2 33.0 60 4.0 8.5 6.0 22.0 40 63 63 30.1 57 52 25.6 11.0 20.9 20 - - Dec-17 Dec-18 Dec-19 2016 2017 2018 2019 Source: CRIF Highmark, Kotak Institutional Equities Source: CRIF Highmark, Kotak Institutional Equities KOTAK INSTITUTIONAL EQUITIES RESEARCH 95 Banks SBI Cards and Payment Services Greater utilization drives shift towards higher limit cards CRIF Highmark provides analysis of card utilization based on credit limits and across vintage of sourcing. We show share of cards with utilizations in the two buckets i.e. <10% and 75- 100% as these two contribute the largest chunk of the total. Cards with low limits ( This trend possibly indicates customer experience of the card starts with a lower limit card but as utilization rates improve, the customer moves to higher limit cards to take care of expenditures (Exhibit 193-195). As the recently sourced customers in the lower limit bracket establish usage history and see their incomes grow, there is a natural increase in credit limits and potentially spends over the medium-term. Exhibit 193: Low limit cards ( FY2017 FY2018 FY2019 FY2020 <10% 75-100% <10% 75-100% <10% 75-100% <10% 75-100% 75 76 80 72 80 72 74 72 69 71 69 71 70 65 66 66 80 70 70 70 70 64 66 69 60 59 59 64 70 63 60 60 54 60 51 49 60 62 51 50 50 50 59 56 40 50 43 40 40 40 32 50 31 29 40 30 30 30 35 35 30 34 31 20 27 20 20 20 23 24 25 20 20 21 19 22 20 10 18 17 17 16 10 16 17 10 18 19 10 14 13 15 15 14 16 15 - - - - 7-9 1-3 4-6 1-3 4-6 7-9 7-9 1-3 4-6 1-3 4-6 7-9 16-18 25-27 10-12 13-15 19-21 22-24 28-30 31-33 19-21 10-12 13-15 16-18 25-27 13-15 16-18 19-21 22-24 28-30 31-33 34-36 10-12 Source: CRIF Highmark, Kotak Institutional Equities Exhibit 194: Medium limit cards (Rs10,000-Rs50,000) have high utilization till one year on the book Utilization rates across year of sourcing for Rs10,000 to Rs50,000 card limit, March fiscal year-ends, 2017-20 (%) <10% 75-100% <10% 75-100% <10% 75-100% <10% 75-100% 60 70 65 80 80 47 60 70 70 50 76 48 73 39 60 60 50 37 50 40 34 36 39 39 32 44 33 33 38 37 50 50 30 40 33 34 28 31 51 51 38 30 27 40 34 40 22 26 25 30 23 21 30 19 30 38 30 20 28 17 27 25 24 20 17 32 17 23 22 20 29 20 20 19 11 27 10 10 10 10 10 - - - - 1-3 4-6 7-9 1-3 4-6 7-9 19-21 10-12 13-15 16-18 Source: CRIF Highmark, Kotak Institutional Equities 96 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 195: High limit cards (>Rs50,000) have high utilization till 28-30 months on the book Utilization rates across year of sourcing for Rs10,000 to Rs50,000 card limit, March fiscal year-ends, 2017-20 (%) <10% 75-100% <10% 75-100% <10% 75-100% <10% 75-100% 74 70 60 80 80 72 50 51 46 70 70 60 50 59 41 58 61 60 50 60 41 40 34 48 32 31 50 50 34 41 40 33 32 31 36 37 36 44 30 30 29 28 30 36 40 40 27 25 30 25 32 33 20 28 30 30 30 29 30 25 20 28 27 27 27 23 15 20 21 20 20 10 18 23 25 9 10 22 10 16 10 - - - - 4-6 1-3 7-9 1-3 4-6 7-9 10-12 13-15 16-18 19-21 Source: CRIF Highmark, Kotak Institutional Equities Credit opportunity is an offshoot of spends and customer mix Apart from convenience of payments, credit cards also have an important functionality of convenience of credit in the form of revolving line of credit. Build-up of credit book is essentially a function of amount of spends and customer propensity to revolve. Few growth dynamics at play are share of customers who are habitual revolvers, occasional revolvers or those where purchases are converted to EMIs (sometimes at ‘zero cost’). Even as spends have a more secular growth trend, card loans have exhibited cyclicality which is typical of most types of credit. Credit card dues in India have grown at ~25% CAGR over FY2015-20 compared to 32% CAGR in spends during this period. There is lack of clarity on how the corporate card spends (typically don’t revolve) influence the mix. Balance of customer mix is critical Credit card customers can be categorized into four categories based on a research on the US credit card industry (link) – (1) Transactors – those who pay their monthly balance in full, (2) Revolvers – those who carry a positive balance at the end of payment cycle, (3) Transitioners – those who move in and out of debt revolving behavior, (4) Inactive – those with no purchase, payments or balance for more than two billing cycles. A few clear takeaways: (a) among active accounts, two out of three cards carry a revolving balance, (b) transitions in an out of credit card debt are relatively rare and occur among only one-tenth of accounts, (c) overall, revolvers are likely to continue borrowing on the card, transactors are unlikely to start revolving and inactive accounts largely remain unused (see exhibit 19 and 197). Further to revolving trends, age profile of debt shows a notable stability reflecting underlying behavior or propensity to revolve of the sub-prime or prime customers at the two ends. It is useful to have this context for a mature market like the US in terms of how this mix has evolved over the years and the mix in terms of credit scores. Unfortunately, we do not benefit from a lot of hindsight knowledge like the US. Data from Transunion CIBIL (albeit slightly dated) on distribution of active cards, loan balances and average balance per card is still somewhat helpful (see exhibit 198). We note that below- prime customers have a higher share of loan balances as well as higher average balance per card compared to prime customers. To the extent banks manage the balance of share of customers with low credit scores but earning recurring interest income versus the default risk, the portfolio can be optimized for higher RoEs. KOTAK INSTITUTIONAL EQUITIES RESEARCH 97 Banks SBI Cards and Payment Services Exhibit 196: Borrowers with higher credit score are less likely to revolve Break-up of credit cards based on customer behavior across time period and credit score (%) Source: CFPB, Kotak Institutional Equities Exhibit 197: Much larger and stable share of transactors in the prime category Break-up of credit cards balance as per age of debt across time period for prime and sub-prime Source: CFPB, Kotak Institutional Equities 98 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 198: Near-prime and sub-prime customers have higher contribution in loan balances with higher average debt per card Breakup of cards outstanding, card balances and average balance across credit scores, December 2017 and December 2018 Source: Transunion CIBIL, Kotak Institutional Equities Spend to loan conversion partly a function of alternative choices Apart from the broad consumption trends driven by incomes, affordability, etc. the tendency to convert spends to loans (revolving or installment-based) is also a function of alternatives available to consumers to get maximum value out of the purchase. Overall ratio of spends in a year to period-end outstanding dues indicates a declining trend over the past six years – declining to 17% in 9MFY20 from 23% in FY2016 (see exhibit 199). Often credit cards compete with installment loans (‘paper finance’) while buying consumer durables. Consumer durable financing market offers interesting insights. Bajaj Finance for a long-time was the largest player in the market partly due to its distribution whereas banks were reluctant due to the need for physical presence and absence of card-based solutions. This changed in recent years and one of the largest card issuers captured market share through zero-cost EMIs offered through a POS machine itself (see exhibit 200). For consumers, it offered a convenient and possibly a cheaper alternative. Exhibit 199: Credit card loans as share of spends has consistently Exhibit 200: Consumer durable financing market share has declined shifted to credit cards from bank financing Credit card dues, spends and dues/spends ratio, March fiscal year- Market share of consumer durable finance, March fiscal year-ends, ends, 2015-9MFY20 (%) 2015-19 (%) (Rs bn) Credit card dues (%) NBFCs Credit cards Banks Spends 100 Spend to loans ratios (RHS) 7,500 7,127 25 18 13 23 26 22 32 29 22 6,033 80 6,000 22 29 20 20 25 60 27 4,589 25 28 4,500 17 19 3,279 40 3,000 2,407 16 1,900 57 58 43 43 47 1,198 1,244 20 1,500 922 13 708 423 552 - - 10 2015 2016 2017 2018 2019 2015 2016 2017 2018 2019 9MFY20 Source: CRIF Highmark, IPO prospectus, Kotak Institutional Equities Source: Public filings, Kotak Institutional Equities KOTAK INSTITUTIONAL EQUITIES RESEARCH 99 Banks SBI Cards and Payment Services Market structure: Large banks dominate and have gained scale over time Even though relatively underpenetrated, the Indian credit card industry has consistently consolidated over the past decade. Of the 25-30 issuers that offer credit cards, the top four players have increased their spend market share to ~75% in FY2021 compared to ~55% in FY2013 (see exhibit 201). Top 10 players have nearly ~95% market share in spends (see exhibit 202). Market share gains are driven by capturing incremental spend per card market share as the cards outstanding market share has been relatively modest. Card economics are largely driven by spends which drive non-credit revenues for transacting customers and credit-driven income for revolving customers. Exhibit 201: Top 10 players hold ~95% cards market share… Exhibit 202: …and similar market share in credit card spends Credit cards outstanding market share, March fiscal year-ends, 2013- Credit cards spends market share, March fiscal year-ends, 2013- 6MFY21 (%) 6MFY21 (%) HDFC Bank SBI Cards ICICI Bank HDFC Bank SBI Cards ICICI Bank Axis Bank Citibank RBL Bank Axis Bank Citibank RBL Bank Amex Standard Chartered Others Amex Standard Chartered Others 100 100 4 12 12 12 10 9 7 80 80 13 12 13 10 7 5 6 13 11 8 6 5 11 9 7 6 16 15 13 8 10 11 12 13 12 12 17 10 60 7 8 60 18 10 10 15 7 8 9 14 6 12 17 16 15 14 13 14 16 16 4 11 11 11 11 11 11 11 40 14 40 20 15 17 12 17 17 18 15 15 15 18 18 19 9 11 11 13 20 20 35 30 31 27 28 30 29 29 27 25 26 29 29 30 29 29 28 29 - - 2013 2014 2015 2016 2017 2018 2019 2020 2021 2013 2014 2015 2016 2017 2018 2019 2020 2021 Source: RBI, Kotak Institutional Equities Source: RBI, Kotak Institutional Equities Incumbents with access to customer pools getting stronger Dominant players in the industry are broadly the ones that have superior customer access from their incumbent businesses. With 70-80% of credit card customers being salaried in nature, issuers with access to these customer pools either hold strong position already or have gained market share in recent years. These include the three frontline private banks (Axis Bank, HDFC Bank and ICICI Bank), whereas SBI has captured this space through SBIC. Bajaj Finance which is another large player operates through a partnership with RBL Bank. Foreign players including American Express and Citi have been losing market share (~30% in FY2013 to ~15% in FY2020) owing to aggressive growth at the frontline players. Reasons for dominance of frontline banks is not surprising as credit card proposition is underpinned by cross-sell to existing liability customer which reduces the sourcing cost as well as potential problem of adverse selection as issuers get a view of customer cash flows through savings account relationship. Ability to capture the relationship in early years of employment improves chances of capturing the spend-driven profit pools that ensue. Scale begets more scale Network economies also explain market share concentration in this business. Large customer base sourced at reasonable cost helps build a fulcrum of revenue base which then provides levers to invest and acquire more customers. With a large part of costs driven by sales and business development costs, issuers are incentivized to acquire customers at a rapid pace and spread the marketing and promotion costs over an expanding card and spend base. It’s important to note that players that dominate the issuing side are also the key players on the merchant acquisition side. Demonetization and proliferation of cashless modes of payments has led to faster rollout of acceptance points by these players (see exhibit 203 and 204). 100 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 203: Sharp growth in POS terminals after demonetization Exhibit 204: Large issuers also have strong market share in POS POS terminal outstanding, January 2012-March 2020 (#) POS terminals market share, as of July 2020 (%) 6,000,000 Others RBL 24% 26% 5,000,000 4,000,000 Demonetization 3,000,000 2,000,000 ICICI Bank 9% 1,000,000 HDFC Bank 17% 0 Axis Bank 10% SBI Jul-14 Jul-19 Jan-12 Jan-17 Sep-13 Sep-18 Nov-12 Nov-17 Mar-16 May-20 May-15 14% Source: RBI, Kotak Institutional Equities Source: RBI, Kotak Institutional Equities Disrupting competition is expensive While the gain in market share by larger private players and SBIC is evident, RBL is a case study of a new/smaller player. The challenge with this analysis is while we get market share data for RBL, there is lack of data on the investment and ongoing expenses supporting this business. Nevertheless, we know from the cost structure of other players (discussed below) that non-staff costs is a much bigger share of costs while staff cost is a much smaller component. We clearly see this shift in cost structure for RBL as well with non-staff costs growing at ~50% CAGR over FY2016-20, which far outpaces growth in staff costs, branches, loans, employees, etc. In other words, between FY2016-20, non-staff costs grew 5X compared to 2X growth for staff costs (see exhibit 205-207). Card companies typically rely on third-parties such as customer acquisition channels, aggregators, payment networks, call center operations, collections, etc. All these cost heads are a part of non-staff costs. Quite likely there were other reasons as well, but we would imagine credit cards probably being a major driver of cost growth. The sharp growth in market share came on the back of access to Bajaj’s customer base. It is unclear what would have been RBL’s cost of acquiring these customers by itself. Exhibit 205: RBL’s market share gains in credit cards accelerated after partnership with Bajaj Finance RBL’s credit cards outstanding and market share in cards/spends, January 2014-July 2020 (%) Cards (#) Card market share (RHS) Spend market share (RHS) 3,000,000 6.0 2,400,000 4.8 1,800,000 3.6 Partnership with Bajaj FInance 1,200,000 2.4 600,000 1.2 - - Jan-17 Jan-18 Jan-19 Jan-20 Jan-14 Jan-15 Jan-16 Sep-17 Sep-18 Sep-19 Sep-20 Sep-14 Sep-15 Sep-16 May-17 May-18 May-19 May-20 May-15 May-16 May-14 Source: Company, Kotak Institutional Equities estimates KOTAK INSTITUTIONAL EQUITIES RESEARCH 101 Banks SBI Cards and Payment Services Exhibit 206: Shift in cost structure towards non-staff costs… Exhibit 207: …as incremental investments probably went Breakup of operating expenses, March fiscal year-ends, 2015-20 towards credit cards business (Rs mn) CAGR for loans, branch, employees, staff/non-staff costs, March fiscal year-ends, 2016-20 (%) Staff cost Non-staff cost 25,000 60 47 20,000 48 15,000 36 32 10,000 24 21 21 16 5,000 12 - - Loans Branches Employees Staff cost Non-staff 2015 2016 2017 2018 2019 2020 cost Source: Company, Kotak Institutional Equities estimates Source: Company, Kotak Institutional Equities estimates Credit card regulations in India Our reading is that the RBI has not been too positive on NBFCs to start credit card operations without prior approval. RBI has a similar stance on working capital loans which is also a type of revolving line of credit. What differentiates credit cards is the direct role in the payments and settlement systems which perhaps increases the contagion risk arising out of failure. RBI’s stringent stand reflects in the industry structure wherein SBIC and BOB Cards are the only two card-issuing NBFCs. RBI allows NBFCs to co-brand cards along with banks without risk sharing but we have not seen major partnerships other than RBL-Bajaj Finance. While this regulatory stance possibly increases the barriers to entry, even markets which allow non-banks to operate (US, Australia) have seen relatively concentration among the top 5-10 players. Wide range of per unit spends across players American Express leads the pack in terms of annual spends per card (~Rs340,000) and average spends per transaction (Rs6,200), given its more premium customer base. IndusInd Bank, although a smaller player (~2% market share), has been targeting to build a similar customer portfolio (see exhibit 208). HDFC Bank and SBI Card have annual spends per card of around Rs150,000, closer to industry average while ICICI Bank and Axis Bank are slightly lower at ~Rs120,000 (see exhibit 208 and 209). 102 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 208: Top 10 players account for ~96% of the market by total transaction value Credit card transaction volume and value, March fiscal year-ends, 2015-2020, 1HFY21 Credit card transaction volume (mn) Credit card transaction value (Rs bn) 2013 2014 2015 2016 2017 2018 2019 20201HFY21 2013 2014 2015 2016 2017 2018 2019 2020 1HFY21 HDFCB 107 161 198 251 333 405 486 610 209 358 457 578 745 975 1,324 1,704 2,123 758 SBI 52 65 78 109 153 212 280 389 145 114 165 213 291 433 770 1,038 1,315 488 ICICI 59 72 91 109 150 189 241 324 115 140 172 216 266 362 515 673 901 331 Citi 82 96 112 130 173 219 239 230 58 227 267 309 353 426 489 532 526 156 Axis 16 27 41 59 88 128 168 199 62 48 88 136 197 287 443 621 768 202 RBL 2 2 1 3 8 19 43 88 32 1 2 5 11 29 69 164 295 117 Amex 19 20 27 36 56 64 77 87 24 155 189 235 293 398 462 559 535 86 Kotak 5 8 10 15 24 36 58 70 21 16 25 33 47 68 108 166 199 68 Others 56 59 62 80 106 142 180 200 66 176 191 201 234 329 445 621 709 223 Total 399 510 619 792 1,092 1,413 1,772 2,198 732 1,235 1,557 1,925 2,437 3,307 4,626 6,079 7,369 2,430 Top 10 94 95 95 96 96 95 95 95 95 94 95 96 97 96 96 96 96 96 Source: Kotak Institutional Equities Exhibit 209: Amex and IndusInd have a more premium customer base Player-wise credit card annual spends and average spend per transaction, March fiscal year-ends, 2015-2020, 1HFY21 Credit card spends per card per year (Rs '000) Average spend per credit card transaction (Rs '000) 2013 2014 2015 2016 2017 2018 2019 2020 1HFY21 2013 2014 2015 2016 2017 2018 2019 2020 1HFY21 Amex 245 294 342 375 431 422 423 339 104 8.2 9.6 8.6 8.2 7.1 7.2 7.2 6.2 3.6 IndusInd 74 82 94 152 198 228 273 250 117 4.0 3.7 3.9 5.5 6.0 5.8 7.0 6.9 5.6 Citi 96 112 128 147 173 188 198 191 113 2.7 2.8 2.8 2.7 2.5 2.2 2.2 2.3 2.7 HDFCB 55 78 104 112 123 138 147 157 103 3.3 2.8 2.9 3.0 2.9 3.3 3.5 3.5 3.6 SBI 44 61 71 86 106 142 143 140 91 2.2 2.5 2.7 2.7 2.8 3.6 3.7 3.4 3.4 RBL 6 13 44 92 137 128 131 134 87 0.3 1.0 3.7 4.3 3.9 3.7 3.8 3.4 3.6 Axis 44 71 87 95 100 113 119 119 58 3.0 3.2 3.4 3.4 3.3 3.5 3.7 3.9 3.3 ICICI 49 57 66 76 92 111 116 114 72 2.4 2.4 2.4 2.4 2.4 2.7 2.8 2.8 2.9 HSBC 73 75 74 80 94 97 99 102 60 2.9 3.0 3.2 3.2 3.0 3.1 3.1 3.2 3.5 Kotak 48 65 67 75 77 86 96 92 59 3.1 3.2 3.3 3.1 2.8 3.0 2.8 2.8 3.2 StanC 170 110 79 88 99 99 103 78 54 3.2 3.2 3.4 2.6 2.4 2.3 2.4 2.4 2.7 Industry 66 82 96 107 122 137 144 141 83 3.1 3.1 3.1 3.1 3.0 3.3 3.4 3.4 3.3 Source: Kotak Institutional Equities Product suite – personal and corporate cards Credit card issuers mainly cater to two categories of customers, personal customers and corporate customers with each category having different features and benefits. Personal cards are offered to retail customers and the product suite includes a variety of cards with different value propositions like cash back, discounts, exclusive access to select facilities or offers on select product categories like travel etc. SBI Card has the widest range of personal credit card products in the industry (see exhibit 210). Exhibit 210: SBI card has the highest number of credit card offerings in the market Player-wise credit card product offerings SBI Card HDFC Bank ICICI Bank Axis Bank RBL Bank IndusInd Bank Number of cards offered 46 20 33 21 30 23 Share of premium cards ~40% ~20% ~45% ~25% ~25% ~70% Range of fees for paid cards (Rs) 500-5,000 500-10,000 200-10,000 250-10,000 500-5,000 250-25,000 Notes: (1) Premium cards are classified as cards with joining fee of more than Rs1,500. (2) Proportion of premium cards is calculated based on total cards offered by the player as per disclosures on the website. Data excludes corporate credit cards. Source: Company website, CRISIL Research Corporate credit cards are designed for specific business requirements, are sourced through direct tie-ups with corporates or private companies and offer real time data and faster reconciliation to its customers. According to CRISIL Research, the proportion of corporate cards, both in terms of volume and value, stands at ~10-15%. Travel and entertainment is the largest segment within corporates and is reasonably well penetrated whereas the use of cards for working capital/vendor payment, etc. (replacing NEFT/RTGS) is relatively untapped. KOTAK INSTITUTIONAL EQUITIES RESEARCH 103 Banks SBI Cards and Payment Services Similar charge structure across issuers We compare the broad structure of important charges applied by the large credit card issuers (see exhibit 211). There is not much difference across issuers on most of the lines of charges such as interest rate on revolving credit, EMI conversion costs, late payment charges or cash advance charges. Lack of a wide range on interest rates probably indicates that the industry has avoided risk-based pricing of loans and prefers a customer filtration process to decide on credit risks while giving EMI loans or balance transfer service. With respect to revolvers the risk is curtailed through active management of card limits as cardholders can always choose to defer making full payments without explicit consent of the issuer. Revolve interest rates tend to remain high and sticky as there is lack of control on cardholder behavior which is a risk that is difficult to price upfront especially for the new-to-product customers. Secondly, the cost of operations is significant in relation to overall costs which makes revolver rates relatively more sticky, similar to a typical microfinance loan. Lastly, unlike a traditional installment loan, the lender has the flexibility to reduce cost through other means such as annual fees which impacts a greater share of cardholders who use it for convenience. Exhibit 211: Similar structure of charges across card issuers Broad structure of charges across issuers Axis Bank Amex Citi HDFC Bank ICICI Bank RBL Bank SBI Cards Interest free period 50 days 51 days 50 days 50 days 48 days 50 days 50 days Minimum repayment amount 5% of outstanding 5% of outstanding 5% of outstanding 5% of outstanding 5% of outstanding 5% of outstanding Communicated at the Communicated at the Communicated at the Communicated at the Cash advance limit 20% 40% 80% time of application time of application time of application time of application NIL for first 180 days Charges on revolving credit 3.4% p.m. 3.5% p.m. 3.5% p.m. 3.5-3.6% p.m. 3.4-3.67% 3.35-3.99% p.m. 3.35% p.m. 3.99% p.m. on 2.5%% for secured 2.5% for secured 2.5% for secured 3.6% p.m. on default 1.99% on Diners default cards cards cards 1.99% on card against FD 13-15% for 3-24 15% for consumer 13-15% for 3-24 22% p.a. for 6-24 EMI conversion 14% at PoS Not disclosed upfront 13% onwards months durable EMI months months 2% (min/max: 1.5% processing fees 16% post purchase 2.5% processing fees Rs99 processing fees No processing fees Rs249/1500) 3% preclosure fees + 3% preclosure fees 2% processing fees 3% preclosure fees 3% preclosure fees 3% preclosure fees 3% preclosure fees next month interest Cash advance 2.5% of amount 3.5% of amount 2.5% of amount 2.5% of amount 2.5% of amount 2.5% of amount 2.5% of amount Rs500 minimum Rs500 minimum Rs500 minimum Rs500 minimum Rs300 minimum Rs500 minimum Rs500 minimum Late payment Rs100-700 Rs500-1000 Rs0-950 Rs0-1300 Rs0-750 Rs50-1250 Rs0-950 Overlimit charges 3% of amount Rs500 minimum 2.5% of amount 2.5% of amount 2.5% of amount Rs600 minimum 2.5% of amount Rs500 minimum Rs500 minimum Rs500 minimum Rs500 minimum Rs500 minimum Eligibility based on 11.4-12.7% (effective Balance transfer 1-2% p.m. 3.5% p.m. 18-24% reducing p.a. 1% fees 1% fees track record ROI) 1.5%% processing 2.5%% processing Available to select Rate and fees not 2.99% (3M loan) or 6-months: 0.75% fees fees bank customers specified upfront Rs499 p.m. 12-months: 1.27% 3% preclosure fees 3% preclosure fees 13.2% p.a. p.m. 2/2.5/3.5% across FX mark-up 3.5% 3.5% 3.5% 3.5% 3.5% 3.5%/1.99% cards Source: Company, PaisaBazaar, BankBazaar, Kotak Institutional Equities Issuers operate with a range of card options Benchmarking card portfolios across issuers is perhaps less relevant given the number of decision variables i.e. annual card fees, reward per unit of spend, reward to rupee conversion ratio, etc. Further, co-branded cards have gained relevance where rewards are linked to specific use cases. Issuers incentivize card spends to waive annual/renewal fees which gets compensated for interchange earned on the spends. For reference purpose we show the broad features of select cards for HDFC Bank and SBIC (see exhibit 212). Issuers incentivize renewal fee rebates based on spends. The objective is not just to drive spends but also to some extent recover cost of customer acquisition incurred in the first year (see exhibit 213). 104 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 212: Most issuers have a broad set of cards for consumer needs Comparison of select credit cards offered by HDFC Bank and SBIC Spends to renewal First year fees Renewal fees waive fees Rewards ratio Eligibility HDFC Bank Infinia Credit Card 10,000 10,000 Rs800K in 12 Months 5 points on Rs. 150 By invitation Diners Club Black Credit Card 10,000 10,000 Rs500K in 12 Months 5 points on every Rs.150 Rs175K pm ITR>Rs2.1 mn/year Regalia Credit Card 2,500 2,500 Rs300K in 12 Months 4 points on every Rs.150 Rs70K pm ITR>Rs0.84 mn/year Diners Club Privilege Credit Card 2,500 2,500 Rs300K in 12 Months 4 points on every Rs.150 Rs70K pm 1 points = 0.5 Rupee ITR>Rs0.84 mn/year Millennia Credit Card 2,500 2,500 Rs100K in 12 Months 1 CashPoint = ₹0.30 Rs25K pm 1 CashPoint = Rs1 for cashback ITR>Rs0.6 mn/year MoneyBack Credit Card 500 500 Rs50K in 12 Months 2 points on every Rs 150 spent Rs25K pm 4 points on every Rs 150 spent online ITR>Rs0.6 mn/year 1 RP = ₹0.20 1 RP = ₹0.25 on SmartBuy Platinum Times Card 1,000 1,000 Rs250K in 12 Months 3 points for every ₹150 Rs35K pm ITR>Rs0.6 mn/year Titanium Times Card 500 500 Rs150K in 12 Months 2 points for every ₹150 Rs25K pm ITR>Rs0.6 mn/year SBI Cards SBI Card Elite 4,999 4,999 Rs1 mn in 12 Months 2 points per Rs. 100 Rs. 60,000 p.m 4 points = Rs. 1 Doctor's SBI Card 1,499 1,499 Rs200K in 12 Months 1 points per Rs. 100 NA 4 points = Rs. 1 SBI Card PRIME 2,999 2,999 Rs300K in 12 Months 2 points per Rs. 100 Rs. 32,000 p.m 20 points per Rs. 100 spent on utility auto debits Apollo SBI Card 499 499 Rs90K in 12 Months 1 points on every Rs. 100 spent NA 3X points on every Rs. 100 spent on all Apollo services 1 points = Rs 1 Lifestyle HC SBI Card PRIME 2,999 2,999 NA 15 points per Rs100 spent NA 4 points = 1 Rs IRCTC SBI Card Premier 1,499 1,499 Rs200K in 12 Months 10% back as points for your ticket purchase on IRCTC NA Club Vistara SBI Card PRIME 2,999 2,999 4 CV Points (per Rs. 200 spent) on all your spends Rs. 40,000 p.m Source: Company, Kotak Institutional Equities Exhibit 213: Wide range of reward expense (as % of spends) across issuers Reward expense, spends and their ratio, March fiscal year-ends 2015-20 2015 2016 2017 2018 2019 2020 Amex Reward provisions (Rs mn) 1,219 1,545 2,772 3,430 3,975 5,050 Spends (Rs bn) 235 293 397 461 559 534 Reward expense/spends (%) 0.52 0.53 0.70 0.74 0.71 0.94 Axis Bank Reward provisions (Rs mn) 84 621 322 891 1,272 2,146 Spends (Rs bn) 135 195 285 440 616 764 Reward expense/spends (%) 0.06 0.32 0.11 0.20 0.21 0.28 Citi Reward provisions (Rs mn) 3,313 4,033 6,050 6,400 5,781 5,042 Spends (Rs bn) 305 349 422 486 529 523 Reward expense/spends (%) 1.09 1.15 1.43 1.32 1.09 0.96 HDFC Bank Reward provisions (Rs mn) 1,129 1,795 3,342 2,620 3,876 5,179 Spends (Rs bn) 569 734 965 1,313 1,692 2,109 Reward expense/spends (%) 0.20 0.24 0.35 0.20 0.23 0.25 ICICI Bank Reward provisions (Rs mn) 1,144 1,535 1,725 1,573 1,892 1,667 Spends (Rs bn) 215 264 361 514 671 898 Reward expense/spends (%) 0.53 0.58 0.48 0.31 0.28 0.19 RBL Bank Reward provisions (Rs mn) 504 1,129 1,925 Spends (Rs bn) 5 11 29 67 161 291 Reward expense/spends (%) - - - 0.75 0.70 0.66 SBI Cards Reward provisions (Rs mn) 746 1,336 2,225 3,016 4,136 5,472 Spends (Rs bn) 209 287 429 765 1,032 1,308 Reward expense/spends (%) 0.36 0.47 0.52 0.39 0.40 0.42 Source: Company, Kotak Institutional Equities KOTAK INSTITUTIONAL EQUITIES RESEARCH 105 Banks SBI Cards and Payment Services Increasing number of co-branded credit card partnerships Co-branded cards are credit cards issued by players in collaboration with partners, which are usually consumer-facing entities with strong and loyal customer bases. They are a differentiated product offering with features designed to address specific needs of customers. Customers earn high reward points along with special offers and promotions for each transaction at partner merchants. With increasing competition in the credit cards space co-branded partnerships differentiate a player’s product suite. Based on SBI Card’s IPO prospectus data, it has 18 co-branded partnerships, the highest in the industry, followed by ICICI Bank at 12 and RBL Bank at 8 (see exhibit 214). Travel and fuel category, and the shopping and entertainment category make up the bulk of the co- brand partnerships for the industry. Players including SBI Card and RBL Bank have also ventured into the healthcare segment in partnership with Apollo, Indian Medical Association (IMA) and Practo. Exhibit 214: SBI Card has the highest number of co-branded partnerships in the industry Number of co-branded partnerships (#) Travel Shopping / Entertainment Payments Lending Healthcare Others 25 20 18 15 12 10 8 6 4 5 3 1 1 0 SBI Card ICICI Bank RBL Bank HDFC Bank Axis Bank Citi Bank Amex IndusInd Bank Notes: (1) RBL has same co-brand offering different cards under travel and other category. Source: Company website, CRISIL Research Robust growth in credit card loans The industry saw robust growth in credit card loans over recent years (~30% CAGR over FY2015-2020). The increasing focus of banks on retail loans amidst a muted environment for corporate loans led to higher growth in unsecured retail loans, including credit cards. However, this started to moderate in the recent quarters to ~25% yoy and more so post the onset of Covid. Credit card loans outstanding/annual spends have declined over time led by faster growth in credit card spends. This indicates an increasing share of non-interest income in the credit card business (Exhibit 215 and 216). 106 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 215: ~30% CAGR in credit card loans over FY2015-20 Exhibit 216: Loans/spends declined over time Credit card loans outstanding , March fiscal year-ends, 2008-4MFY21 Credit card loans/annual spends, March fiscal year-ends, 2008-20 (bn) (bn) Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities Growth in credit card loans indicates rising share of revolvers who pay exorbitant rates but also increasing trend of consumers converting large-ticket spends to EMIs at zero cost or much lower rates. We compare the loans/spends ratio and average loan balance per card across the large issuers (see exhibit 219). Loan/spends ratio is impacted by the share of corporate card spends which is probably higher for Amex (low loans/spends) at one and lower for RBL (higher loans/spends, see exhibit 217). HDFC Bank, the industry spend leader, has consistently maintained the ratio at ~27-29% which indicates its strong market share in EMI-conversion of spends (‘SmartEMI’) at the point of sale. Exhibit 217: Steady increase in share of term balances for RBL Exhibit 218: Share of transactors has been in the range of 25- RBL portfolio breakup, September 2017 to March 2020 (%) 30% for SBI Card SBIC portfolio breakup, 1QFY20, 4QFY20, 1QFY21 (%) Transactors Revolvers Term 100 31 32 30 80 60 38 40 45 40 20 31 27 Source: Company, Kotak Institutional Equities 25 0 1QFY20 4QFY20 1QFY21 Source: Company KOTAK INSTITUTIONAL EQUITIES RESEARCH 107 Banks SBI Cards and Payment Services Exhibit 219: Decline in headline loans to spends ratio for the industry Loan/spends and average balance per card, March fiscal year-end, 2013-20 2013 2014 2015 2016 2017 2018 2019 2020 Amex Spends (Rs bn) 154 188 235 293 397 461 559 534 Loans (Rs bn) 17 21 23 30 36 51 40 53 Loans/spends (%) 11 11 10 10 9 11 7 10 Avg balance per card (Rs) 27,400 33,200 34,100 37,900 38,800 46,200 30,100 33,200 Axis Bank Spends (Rs bn) 48 88 135 195 285 440 616 764 Loans (Rs bn) 67 83 123 153 Loans/spends (%) - - - - 24 19 20 20 Avg balance per card (Rs) - - - - 23,400 21,200 24,000 23,100 HDFC Bank Spends (Rs bn) 353 451 569 734 965 1,313 1,692 2,109 Loans (Rs bn) 101 123 162 205 260 361 466 576 Loans/spends (%) 29 27 28 28 27 28 28 27 Avg balance per card (Rs) 16,700 22,600 29,100 31,400 31,800 37,200 39,600 42,700 ICICI Bank Spends (Rs bn) 140 172 215 264 361 514 671 898 Loans (Rs bn) 36 36 40 55 75 93 123 157 Loans/spends (%) 26 21 18 21 21 18 18 17 Avg balance per card (Rs) 12,900 11,900 12,000 15,900 18,700 20,300 21,400 19,600 IndusInd Bank Spends (Rs bn) 17 21 29 59 101 155 250 300 Loans (Rs bn) 3 5 7 12 17 27 44 48 Loans/spends (%) 20 22 24 20 17 17 18 16 Avg balance per card (Rs) 16,000 17,900 22,700 31,000 33,600 39,000 47,600 38,700 RBL Bank Spends (Rs bn) - 1 5 11 29 67 161 291 Loans (Rs bn) 22 53 105 Loans/spends (%) 33 33 36 Avg balance per card (Rs) - - - - - 43,500 42,300 46,300 SBI Cards Spends (Rs bn) 113 163 209 287 429 765 1,032 1,308 Loans (Rs bn) 33 44 57 74 103 140 179 228 Loans/spends (%) 29 27 27 26 24 18 17 17 Avg balance per card (Rs) 13,600 16,000 19,200 21,700 25,200 26,000 25,000 23,900 Total of above banks Spends (Rs bn) 776 994 1,257 1,637 2,538 3,715 4,981 6,205 Loans (Rs bn) 191 228 289 376 557 777 1,028 1,319 Loans/spends (%) 25 23 23 23 22 21 21 21 Avg balance per card (Rs) 14,600 17,100 20,000 22,500 26,900 30,000 30,900 30,900 Source: Company, RBI, Kotak Institutional Equities Amex/SBIC: Comparing revenue and cost profile Amex and SBI make for a useful comparison (see exhibit 220-223). Amex is the only other standalone credit card player with reported financials which can be compared with SBIC. While it is not a perfect comparison as we don’t get full details of the revenue/cost breakup to fully explain the differences but it helps understand and explain a few aspects of the credit card business such as (1) interest rate changes have marginal bearing on revenues and costs, (2) revolve interest rates are generally high and sticky due to cost of customer acquisition, (3) cost of customer acquisition is recovered either by way of higher spends (interchange income) or through credit (interest income). Amex’s business model also has some contrast to SBIC with higher focus on corporate cards and fee income driving revenue profile whereas SBIC is relatively more balanced with both credit and non-credit revenue drivers. Fees dominate revenues for Amex compared to nearly 50-50 split for SBIC. This corroborates with lower loans/spends ratio for Amex (10%) compared to SBIC (17%). On the expenses side, staff costs are a much smaller share of expenses (~10% of non- interest expense) which compares to 35-40% for the broader private banking space. Secondly, sales/marketing and business development is a large part of the cost base aimed at driving customer acquisition and spend growth. 108 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 220: Amex: Various types of fees drive revenues Exhibit 221: Amex: Marketing and rewards are major cost drivers Revenue breakup, March fiscal year-ends, 2012-20 (%) Cost breakup, March fiscal year-ends, 2012-20 (%) Other non-interest income Commission, exchange & brokerage Interest expense Advt & publicity Employee Income on investments Interest on advances Business support cost Others 100 100 80 80 60 60 40 40 20 20 - - 2012 2013 2014 2015 2016 2017 2018 2019 2020 2012 2013 2014 2015 2016 2017 2018 2019 2020 Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities Exhibit 222: SBIC: Interest income is a crucial revenue driver Exhibit 223: SBIC: Sales promotion and interest costs drive Revenue breakup, March fiscal year-ends, 2012-20 (%) overall costs Cost breakup, March fiscal year-ends, 2012-20 (%) Interest income Membership fees & services Subscription based fees Spend based fees Others Collection & recovery Rewards Transaction charges Instance-based fees Other income 100 Processing charges Sales promotion, fees, commission Employee Finance costs 100 80 80 60 60 40 40 20 20 - 2016 2017 2018 2019 2020 - 2016 2017 2018 2019 2020 Source: Company, Kotak Institutional Equities Source: Company, Kotak Institutional Equities Recasting financials on spends and cards Cards and spends drive bulk of revenues for card companies either directly through fees or through conversion to loans. We compare the underlying operating performance and profitability by common sizing (3-year average) on per Rupee spends and per unit card (compared to traditional approach of calculating on assets). Exhibit 224 highlights the same. Amex makes about ~Rs9,500 fee income per card compared to ~Rs4,100 for SBI Card. However, over 95-100% of this is spent on employees, business development and promotion and rewards. On a net basis, Amex makes ~Rs330 per card compared to ~Rs900 for SBIC due higher net interest income on loan balances by SBIC (~Rs2,000) compared to Amex (Rs1,200). KOTAK INSTITUTIONAL EQUITIES RESEARCH 109 Banks SBI Cards and Payment Services Exhibit 224: Amex makes ~10bps of spends and Rs330 per card on net pre-tax basis Breakup of pre-tax profit as % of spends and per unit card, March fiscal year-ends, average 2018-20 % of spends Per card (Rs) 3.5 14,000 2.8 11,200 2.1 8,400 1.4 5,600 0.7 2,800 0.08 332 - - Others Others Employee Provisions Employee Provisions Pre-tax Pre-tax PBT Pre-tax Pre-tax PBT Other Other income Other Other income Interest incomeInterest Interest income Interest Advt & Advt publicity Interest expense Interest Advt &Advt publicity Interest expense Interest Business supportBusiness Business supportBusiness Source: Company, Kotak Institutional Equities Exhibit 225: SBIC makes 1.3% of spends and ~Rs900 per card on net pre-tax basis Breakup of pre-tax profit as % of spends and per unit card, March fiscal year-ends, average 2018-20 % of spends Per card (Rs) 8.0 10,000 6.4 8,000 4.8 6,000 3.2 4,000 1.6 1.3 2,000 904 - - Others Others Rewards Rewards Employee Employee Provisions Provisions Pre-tax Pre-tax PBT Pre-tax Pre-tax PBT Financecosts Financecosts Other Other income Collection Collection cost Collection cost Interestincome Interestincome Sales promotion Sales Sales promotion Sales Subscription fees Subscription fees Subscription Spend based based Spend fees based Spend fees Processing charges Processing charges Instance-based fees Instance-based Instance-based Instance-based fees Transaction Transaction charges Transaction Transaction charges Source: Company, Kotak Institutional Equities Profitability is strong currently but is a reflection of a strong underlying cycle The card business should be delivering an extremely high RoRWA for all the players in the industry. While we don’t have the specific data on the same, we rely on our channel checks, meetings with the heads of the business for various banks and data from regulators on transactions to compute the earnings and its contribution to various banks. In our view, the cards business’ contribution to loans is likely to be <10% though its contribution to earnings is likely to be mid to high teens for most of the players. Exhibit 226 and 227 below shows our estimate of the card business. Note that the bank does not provide granular information of this portfolio. This is our estimate based on the bank’s outstanding card, total value of transactions, fee income reported by the bank and our estimate of operating expenses and credit costs based on available information on the sector. 110 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Cards business is an important driver to this line of activity and its contribution extends not only in lending but also on fee income. The fee growth from cards business has grown ~35% CAGR and contributes to ~35% of the overall fees. Exhibit 226: Contribution from the credit card business to profitability has been rising over the years Credit card and personal loan business contribution to the overall business for HDFC Bank, March fiscal year-ends, 2016-20 (Rs mn) Credit card business Bank 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020 (% of loans) 4.4 4.6 5.2 5.6 5.9 Average loans (D) 187,685 230,648 324,173 426,155 542,048 4,253,774 5,036,630 6,188,469 7,649,598 9,141,115 Revenues 41,225 53,271 75,640 101,586 127,660 383,432 454,357 553,152 658,691 794,471 Interest income 40,575 49,416 67,560 88,645 111,222 602,214 693,060 802,414 989,721 1,148,127 Interest on loans 33,783 41,517 58,351 76,708 97,569 448,279 520,553 626,618 775,442 917,879 Interest on investments 6,230 7,302 8,498 11,140 12,235 141,200 159,443 162,224 199,975 206,333 Others 562 598 711 797 1,418 12,736 13,064 13,572 14,304 23,914 Interest expenses 14,397 16,562 21,030 28,261 34,764 326,299 361,667 401,465 507,288 586,264 Net interest income 26,178 32,854 46,530 60,384 76,458 275,915 331,392 400,949 482,432 561,863 Non-interest income 15,047 20,417 29,110 41,201 51,202 107,517 122,965 152,203 176,259 232,608 Operating expenses 20,108 27,611 36,087 48,158 60,634 169,797 197,033 226,904 261,194 306,975 PPOP 21,118 25,660 39,553 53,428 67,026 213,635 257,324 326,248 397,497 487,495 Provisions 5,101 6,686 8,342 10,626 12,770 17,840 16,242 15,914 20,788 27,104 PBT 16,016 18,974 31,211 42,803 54,255 186,379 221,391 266,973 321,997 366,072 Contribution to PBT of bank 9 9 12 13 15 Avg. number of cards (mn) A 6.5 8.2 9.7 11.8 13.5 Spends/card (Rs mn) B 733,902 964,813 1,312,987 1,691,970 2,109,333 Spends/card (Rs/year) (B/A) 112,180 118,139 135,311 143,730 156,545 Growth in spends/card (%) 9.4 5.3 14.5 6.2 8.9 Transactions/card (Rs mn) C 250 331 402 484 608 Transactions/card (#/year) (C/A) 38 41 41 41 45 Growth in transactions/card (%) 7.8 6.2 2.4 (0.8) 9.6 Loans/card (D/A) 28,689 28,242 33,408 36,201 40,228 Revenue/card (Rs) 6,301 6,523 7,795 8,630 9,474 NII/card 4,001 4,023 4,795 5,130 5,674 Non-interest income/card 2,300 2,500 3,000 3,500 3,800 Opex/card (Rs) 3,074 3,381 3,719 4,091 4,500 Notes: (a) This is a hypothetical exercise based on external available information (SBIC) which has been fine tuned to HDFC Bank. (b) The yield on loans has been assumed at 19% for cards. Opex and provisions is an internal assumption Source: Company, Kotak Institutional Equities estimates KOTAK INSTITUTIONAL EQUITIES RESEARCH 111 Banks SBI Cards and Payment Services Exhibit 227: HDFC Bank is probably making ~Rs3500-3800/card Revenue profile of retail card business, March fiscal year-ends, 2017-20 (` mn) 2017 2018 2019 2020 Revenues from the card business 25,115 34,551 47,012 58,899 Debit card business Number of cards (Rs mn) Period ending 23.6 24.3 27.0 32.1 Average 23.7 24.5 26.0 29.8 POS transactions Number of transactions (mn) 323 419 537 618 Value of transactions (Rs bn) 447 583 775 925 Average value of transaction (Rs) 1,384 1,392 1,442 1,498 POS volume fees (MDR) 3,355 2,917 3,874 4,625 Revenue profile from debit card business Annual fees 3,321 3,668 4,154 4,774 Issuing bank interchange fees 1,677 1,459 1,937 2,313 Total fees from debit cards 4,999 5,127 6,091 7,086 Growth (%) 3 19 16 Contribution of debit card business (%) 20 15 13 12 Credit card business Number of cards (Rs mn) Period ending 8.5 10.7 12.5 12.5 Average 8.2 9.7 11.8 13.5 POS transactions Number of transactions (mn) 331 402 484 608 Value of transactions (Rs bn) 965 1,313 1,692 2,109 Average value of transaction (Rs) 2,900 3,300 3,500 3,500 POS volume fees (MDR) 12,543 17,069 21,996 27,421 Derived revenue profile for credit card business Credit card fees (Rs mn) 20,117 29,425 40,921 51,813 Annual fees 6,697 8,636 11,301 12,935 Issuing bank interchange fees 9,407 12,802 16,497 20,566 Others 4,013 7,987 13,123 18,312 Fees/card (Rs) 2,463 3,032 3,476 3,845 Notes: (a) HDFC Bank has not provided any break-up of data beyond the payment related fees. We have made these calculations based on our understanding of this business. Note that the card business would be working on a transfer pricing policy that could be different across banks. We would not have information of the same for HDFC Bank but have made some assumptions on the same by incorporating some portion of the investment book to this business. We have made assumption on roll rates and the average yield for this portfolio. The fee for the credit card business is derived based on our assumption of the contribution of the debit card business. (b) We don’t have the annual debit card fees and have assumed an uniform increase of 8%. We are not too sure on the accounting of the ATM business and if these are included in this line item. We have assumed the credit card fees to grow at a similar rate as well. (c) Debit card fees has been taken at 0.75% of the value as the average transaction is Source: Company, Kotak Institutional Equities estimates Exhibit 228 and 229 shows the contribution of the credit card segment to Axis Bank business’. We have attempted to understand the card business for the bank. Note that we don’t have too much information on the same and a lot of what we have published in this report is purely based on our estimates. It is quite likely that the internal numbers tracked by the bank on most of these line items is quite different as compared to our estimates. Based on our calculations, we believe that the credit card business is probably generating ~25% of the overall fees in cards and the majority of card fee income probably comes from the credit card business. As we have seen with our earlier reports on RBL Bank and HDFC Bank, this business is probably quite profitable today. 112 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 228: Credit card business is likely to be ~75-80% of the overall retail card business for the bank Revenue profile of retail card business for Axis Bank, March fiscal year-ends, 2013-20 (Rs mn) 2013 2014 2015 2016 2017 2018 2019 2020 Revenues from retail business 17,310 20,080 26,030 30,270 34,810 48,900 61,430 70,918 Growth in revenues (%) 16 30 16 15 40 26 15 Share of the cards business (%) 26 27 29 34 36 38 40 41 Revenues from the card business 4,501 5,422 7,549 10,292 12,532 18,750 24,330 29,036 Debit card business Number of cards (Rs mn) Period ending 14.3 13.3 14.3 15.5 20.2 22.3 24.5 24.5 Average 13.4 13.9 14.3 15.1 17.5 21.5 25.4 23.9 POS transactions Number of transactions (mn) 41 54 67 88 167 209 304 336 Value of transactions (Rs bn) 68 86 107 133 248 304 446 514 Average value of transaction (Rs) 1,639 1,602 1,596 1,505 1,482 1,450 1,467 1,527 POS volume fees (MDR) 510 646 801 994 1,861 1,519 2,230 2,568 Revenue profile from debit card business Annual fees 1,344 1,529 1,721 1,961 2,451 3,231 4,070 4,064 Issuing bank interchange fees 255 323 401 497 931 759 1,115 1,284 Total fees from debit cards 1,598 1,852 2,121 2,458 3,381 3,990 5,185 5,348 Growth (%) 16 15 16 38 18 30 3 Contribution of debit card business (%) 36 34 28 24 27 21 21 18 Credit card business Number of cards (Rs mn) Period ending 1.1 1.4 1.7 2.4 3.3 4.5 6.0 7.0 Average 0.9 1.2 1.5 2.0 2.9 3.9 5.1 6.6 POS transactions Number of transactions (mn) 16 27 40 58 87 128 167 198 Value of transactions (Rs bn) 48 88 135 195 285 440 616 764 Average value of transaction (Rs) 3,000 3,200 3,300 3,400 3,300 3,400 3,700 3,800 POS volume fees (MDR) 767 1,407 2,154 3,119 4,563 7,038 9,860 12,222 Derived revenue profile for credit card business Credit card fees (Rs mn) 2,902 3,570 5,427 7,833 9,150 14,760 19,145 23,688 Annual fees 558 795 1,079 1,542 2,352 3,464 4,917 6,862 Issuing bank interchange fees 575 1,055 1,615 2,339 3,422 5,278 7,395 9,167 Others 1,770 1,719 2,733 3,952 3,377 6,018 6,834 7,659 Fees/card (Rs) 3,123 2,917 3,520 3,860 3,190 3,792 3,738 3,590 Notes: (a) Axis Bank has not provided any break-up of data beyond the retail card fees. We have made these calculations based on our understanding of this business. Note that the card business would be working on a transfer pricing policy that could be different across banks. We would not have information of the same for Axis Bank but have made some assumptions on the same by incorporating some portion of the investment book to this business. We have made assumption on roll rates and the average yield for this portfolio. The fee for the credit card business is derived based on our assumption of the contribution of the debit card business. (b) We don’t have the annual debit card fees and have assumed a uniform increase of 8%. We are not too sure on the accounting of the ATM business and if these are included in this line item. We have assumed the credit card fees to grow at a similar rate as well. (c) Debit card fees has been taken at 0.75% of the value as the average transaction is Source: Company, Kotak Institutional Equities KOTAK INSTITUTIONAL EQUITIES RESEARCH 113 Banks SBI Cards and Payment Services Exhibit 229: Credit card and personal loans’ contribution would decline in the medium term as earnings move to a normalized level Hypothetical revenue and profitability of the unsecured card business of Axis Bank, March fiscal year-ends, 2020 (Rs mn) Credit Personal Bank card Contribution loans Contribution Total Contribution (Rs mn) (Rs mn) (%) (Rs mn) (%) (Rs mn) (%) (% of loans) 2.6 6.5 9.1 Average loans 5,331,111 141,048 2.6 346,150 6.5 487,197 9.1 Revenues 407,428 42,966 10.5 26,541 6.5 69,507 17.1 Interest income 626,352 29,181 4.7 47,382 7.6 76,563 12.2 Interest on loans 483,030 25,389 5.3 38,076 7.9 63,465 13.1 Interest on investments 112,460 2,975 2.6 7,302 6.5 10,277 9.1 Others 30,862 817 2.6 2,004 6.5 2,820 9.1 Interest expenses 374,290 9,903 2.6 24,303 6.5 34,205 9.1 Net interest income 252,062 19,278 7.6 23,080 9.2 42,357 16.8 Non-interest income 155,366 23,688 15.2 3,461 2.2 27,149 17.5 Operating expenses 173,046 29,691 17.2 8,654 5.0 38,345 22.2 PPOP 234,381 13,274 5.7 17,887 7.6 31,162 13.3 Provisions 185,340 4,231 2.3 6,923 3.7 11,154 6.0 PBT 49,041 9,043 18.4 10,964 22.4 20,007 40.8 Average number of cards (mn) 6.6 Receivables/card (Rs) 21,400 Spends/card (Rs/year) 115,777 Transactions/card (#/year) 30 Revenue/card (Rs) 6,490 NII/card 2,900 Non-interest income/card 3,590 Opex/card (Rs) 4,500 Notes: (a) This is a hypothetical exercise based on external available information (SBIC) which has been fine tuned to Axis Bank. Note that the management has not given us any information on the same on any of the above parameters like interest rate on the portfolio, fee income, operating costs for this business and credit costs. (b) The yield on loans has been assumed at 18% for cards and ~11% for personal loans. (c) Opex to loans has been assumed at 2.5%, non-interest income at 1% and provisions at 1.25% for personal loans. (d) Transfer pricing has not been considered for this exercise but we have loaded the SLR costs to the business Source: Company, Kotak Institutional Equities Exhibit 230 shows the contribution of the credit card segment to RBL’s business. This is an entirely hypothetical exercise based on external and internal inputs. The management has not given us any specific numbers on any line items and we have used the performance of SBIC for the credit card business of RBL. Based on this exercise, we can understand the importance of this segment to RBL Bank. The throughputs of the cards business have been quite impressive when we look at the number of transactions, spends and average transaction/card especially in an environment impacted by Covid. In the past, the management had indicated that it would want a substantial increase in its credit card base going ahead (>3 mn currently). This would entail quite a lot of expenses upfront as most of it would be origination costs. We don’t have the details of the contract that the bank has with Bajaj Finance (management guided that the co-branded franchise has crossed 1 mn customers). 114 KOTAK INSTITUTIONAL EQUITIES RESEARCH SBI Cards and Payment Services Banks Exhibit 230: Credit card contribution is quite meaningful for RBL Bank Hypothetical revenue and profitability of the card business of RBL Bank, March fiscal year-ends, 2018-2021E (Rs mn) Credit card business Bank 2018 2019 2020 2021E 2018 2019 2020 2021E (% of loans) 4.9 8.6 15.4 14.6 Average loans (D) 17,737 40,733 86,378 85,553 359,748 472,880 561,636 586,887 Revenues 5,030 10,851 20,252 22,920 28,345 39,818 55,399 56,163 Interest income 3,901 8,694 18,366 17,959 45,076 63,007 85,144 86,198 Interest on loans 3,370 7,617 15,893 15,485 34,309 50,498 69,068 69,224 Interest on investments 492 942 2,111 1,948 9,982 10,934 13,727 13,363 Others 39 136 361 526 785 1,574 2,349 3,611 Interest expenses 1,352 3,240 7,513 6,788 27,413 37,612 48,847 46,562 Net interest income 2,549 5,455 10,853 11,172 17,663 25,395 36,296 39,635 Non-interest income 2,481 5,397 9,398 11,748 10,682 14,424 19,102 16,528 Operating expenses 3,092 7,115 12,303 14,610 15,034 20,420 27,883 27,504 PPOP 1,938 3,737 7,949 8,310 13,311 19,398 27,516 28,659 Provisions 709 1,629 3,455 3,422 3,645 6,407 19,989 21,064 PBT 1,229 2,107 4,494 4,888 9,665 12,992 7,528 7,596 3,315 4,322 2,471 1,945 Tax rate (%) 34.3 33.3 32.8 25.6 34 33 33 26 PAT 807 1,406 3,018 3,637 6,351 8,670 5,057 5,651 Contribution to PAT of bank 13 16 60 64 Outstanding cards (average, # mn) 0.5 1.2 2.3 2.8 Spends (Rs mn) 67,215 160,596 290,585 355,966 Spends/card (Rs)- yearly 130,443 128,664 127,896 125,338 Growth in spends/card (%) 961.4 (1.4) (0.6) (2.0) Transactions (# mn) 18.6 43.1 87.9 Transactions/card- yearly 36 35 39 Growth in transactions/card (%) 1,037.2 (4.5) 12.1 Loans/card (D/A) 34,421 32,633 38,018 30,124 Revenue/card (Rs) 9,762 8,694 8,913 8,070 NII/card 4,947 4,370 4,777 3,934 Non-interest income/card 4,814 4,324 4,137 4,137 Opex/card (Rs) 6,000 5,700 5,415 5,144 Growth (%) (5) (5) (5) Loan to average spends (%) 26.4 25.4 29.7 24 Cost-income (%) 61.5 65.6 60.8 63.7 Credit cost (% of loans) 4.0 4.0 4.0 4.0 Notes: (a) This is a hypothetical exercise based on external available information (SBIC) which has been fine tuned to RBL Bank. Note that the management has not given us any information on the same on any of the above parameters like interest rate on the portfolio, operating costs for this business and credit costs. (b) The yield on loans has been assumed at 18% for cards. (c) Transfer pricing has not been considered for this exercise but we have loaded the SLR costs to the business Source: Company, Kotak Institutional Equities KOTAK INSTITUTIONAL EQUITIES RESEARCH 115 Kotak Institutional Equities: Valuation summary of KIE Universe stocks 3 Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Automobiles & Components Amara Raja Batteries REDUCE 929 730 (21) 159 2.2 171 36 46 52 (7.3) 27.5 13.3 26 20.3 17.9 14.1 11.3 9.8 3.9 3.4 3.0 15.8 17.7 17.6 1.0 1.2 1.4 10.9 Apollo Tyres REDUCE 178 175 (2) 113 1.5 638 4.3 11.1 16.1 (47.8) 155.7 44.8 40.9 16.0 11.0 7.9 6.1 4.7 1.0 1.0 0.9 2.6 6.2 8.5 0.7 1.5 1.5 19.1 Ashok Leyland BUY 95 115 21 280 3.8 2,936 (0.3) 3.4 7.5 (121.4) 1,412.9 117.2 NM 27.6 12.7 38.9 13.4 7.6 3.9 3.5 3.0 NM 13.4 25 0.0 1.1 2.4 44 Bajaj Auto BUY 3,415 3,900 14 988 13 289 154 185 216 (12.5) 19.7 17.1 22.2 18.5 15.8 16.7 13.3 10.9 4.6 4.1 3.8 21 23 25 2.7 3.2 3.8 42 Balkrishna Industries SELL 1,557 1,250 (20) 301 4.1 193 52 62 77 4.2 19.5 24.4 30.1 25.2 20.2 17.7 14.7 11.8 5.4 4.8 4.1 18.9 20 22 1.4 1.6 1.7 24 Bharat Forge SELL 528 320 (39) 246 3.3 466 (0) 13 19 (102.4) 7,097.2 50.4 NM 41.8 27.8 49.4 21.1 15.9 4.7 4.3 3.8 NM 10.8 14.7 0.0 0.6 0.6 20 CEAT ADD 1,064 1,250 17 43 0.6 40 75 91 109 20.3 20.2 19.9 14.1 11.8 9.8 8.0 6.4 5.5 1.4 1.2 1.1 10.1 11.1 12.0 1.1 1.1 1.1 3.8 Eicher Motors SELL 2,451 1,920 (22) 670 9.1 272 57 84 109 (15.7) 47.7 30.8 43.3 29.3 22.4 30.9 22.3 17.2 7.0 5.9 4.8 17.3 22 24 0.5 0.5 0.5 50 Endurance Technologies REDUCE 1,266 1,020 (19) 178 2.4 141 34 49 59 (16.2) 44.7 21.9 38 26.0 21.3 17.4 13.2 11.0 5.2 4.5 3.8 13.9 17.3 17.9 0.4 0.6 0.8 2.2 Escorts BUY 1,243 1,535 24 110 2.3 101 72 85 96 31.7 17.6 13.3 17.3 14.7 13.0 9.8 8.1 6.7 2.4 2.1 1.9 14.2 14.6 14.5 0.9 1.0 1.2 34 Exide Industries REDUCE 186 165 (11) 158 2.2 850 8.0 9.7 10.6 (19.9) 21.1 9.2 23.3 19.3 17.7 12.4 10.5 9.5 2.4 2.2 2.0 10.5 11.8 12.0 1.9 1.9 1.9 9.5 Hero Motocorp SELL 3,083 2,700 (12) 616 8.4 200 136 175 202 (14.7) 29.2 14.9 22.7 17.6 15.3 14.5 10.8 9.2 4.1 3.7 3.4 18.6 22 23 2.9 3.4 3.9 70 Mahindra CIE Automotive SELL 169 110 (35) 64 0.9 378 1.8 8.2 12.1 (80.6) 347.1 48.3 92.4 20.7 13.9 17.9 9.3 6.9 1.4 1.3 1.2 1.5 6.4 8.8 — — — 0.3 Mahindra & Mahindra BUY 711 770 8 884 12.0 1,138 32 44 49 35.1 35.6 12.7 22.1 16.3 14.5 13.4 10.8 9.3 2.2 2.0 1.8 10.2 12.7 12.8 0.5 0.9 1.0 56 Maruti Suzuki SELL 7,483 5,800 (22) 2,260 30.8 302 170 253 310 (8.9) 48.6 22.4 44 30 24 28.2 17.8 13.8 4.4 3.9 3.5 10.3 14.0 15.3 0.8 0.8 1.0 115 Motherson Sumi Systems ADD 161 155 (4) 507 6.9 3,158 2.7 7.5 9.0 (26.2) 173.2 20.5 58.8 21.5 17.9 11.8 6.3 5.2 4.3 3.4 2.8 7.5 17.7 17.1 0.7 1.0 1.1 27 MRF SELL 75,367 68,000 (10) 320 4.3 4 2,441 3,281 3,947 (27.3) 34.4 20.3 31 23.0 19.1 11.2 9.0 7.4 2.4 2.2 2.0 8.1 10.0 10.9 0.1 0.1 0.2 36 Schaeffler India SELL 4,419 3,500 (21) 138 1.9 31 87 139 166 (26.5) 60.7 19.5 51 32 27 25.5 17.1 14.3 4.3 3.8 3.4 8.8 12.8 13.5 — — — 0.7 SKF REDUCE 1,705 1,450 (15) 84 1.1 49 43 54 67 (26.4) 26.2 22.9 40 31 26 28.9 21.9 17.7 5.7 5.0 4.3 14.4 15.9 16.9 6.4 0.5 0.7 0.6 Tata Motors SELL 186 135 (28) 670 8.4 3,829 (10.6) 12.1 19.6 48.8 213.9 61.7 NM 15.4 9.5 5.3 3.9 3.1 1.1 1.1 1.0 NM 7.2 10.6 — — — 134 Timken SELL 1,187 830 (30) 89 1.2 75 22 36 43 (33.6) 64.9 20.0 55 33 28 31.5 20.2 16.8 6.5 5.6 4.7 11.1 18.1 18.4 0.1 0.1 0.2 0.7 TVS Motor SELL 483 300 (38) 230 3.1 475 7.5 15.5 20.1 (41.9) 106.0 29.4 64 31 24 22.3 14.9 12.3 6.0 5.3 4.6 9.7 18.2 21 0.6 0.8 1.0 19.4 Varroc Engineering BUY 392 380 (3) 53 0.7 135 (20) 23 35 (10,817.5) 213.9 56.2 NM 17.3 11.0 12.7 5.8 4.7 1.9 1.7 1.5 NM 10.1 13.8 — — — 1.3 Automobiles & Components Cautious 9,162 124.7 (1) 106 28 45.5 22.1 17.3 12.9 9.2 7.5 3.1 2.8 2.5 6.9 12.8 14.5 1.0 1.2 1.4 722 Banks AU Small Finance Bank SELL 856 690 (19) 263 3.6 304 39.6 24.5 32.0 78.4 (38.1) 30.7 22 35 27 — — — 4.8 4.3 3.7 24.2 12.5 14.3 — — — 11.4 Axis Bank BUY 618 625 1 1,891 25.7 2,822 34.4 43 54 496.2 24.5 25.4 18 14.4 11.5 — — — 2.0 1.8 1.6 10.9 12.3 13.9 0.8 1.0 1.3 179 Bandhan Bank ADD 406 400 (2) 654 8.9 1,610 20.1 20.4 24.8 7.3 1.0 22.0 20.2 20.0 16.4 — — — 3.7 3.1 2.6 19.3 16.3 16.9 — — — 51 Bank of Baroda ADD 62 65 4 288 3.9 4,627 8.8 18.3 20 648.3 106.8 9.3 7 3.4 3.1 — — — 0.5 0.5 0.4 6.0 11.6 11.5 2.8 5.9 6.4 31 Canara Bank REDUCE 125 100 (20) 206 2.8 1,454 (1.0) 6.5 18.3 95.2 723.0 181.8 NM 19.3 6.8 — — — 0.6 0.6 0.6 NM 2.0 5.3 — — — 29 City Union Bank REDUCE 182 170 (7) 134 1.8 737 13.5 18.8 23.6 109.4 39.3 25.4 13 9.7 7.7 — — — 1.3 1.2 1.0 18.2 23 27 1.3 1.8 2.3 4.6 Daily Summary India DCB Bank BUY 119 150 26 37 0.5 310 9.3 11.6 16.7 (14.2) 23.9 44.4 12.7 10.3 7.1 — — — 1.1 1.1 0.9 8.8 10.0 13.0 0.8 1.0 1.4 3.3 Equitas Holdings BUY 66 100 51 23 0.3 342 7.8 8.3 16.3 30.2 5.3 96.9 8.5 8.0 4.1 — — — 0.8 0.7 0.6 9.2 8.8 15.4 — — — 3.2 Federal Bank BUY 67 80 19 134 1.8 1,993 7.1 7.7 11.7 (8.4) 8.1 52.4 9.5 8.8 5.8 — — — 0.9 0.9 0.8 9.4 9.5 13.2 2.3 2.5 3.9 33 HDFC Bank ADD 1,413 1,475 4 7,781 105.9 5,483 53 58 68 10.3 10.4 16.3 27 24 21 — — — 4.1 3.6 3.2 15.9 15.5 16.0 0.7 0.8 0.9 215 ICICI Bank BUY 520 600 15 3,590 48.8 6,893 23.3 27 30 90.0 15.9 11.4 22 19.3 17.3 — — — 2.6 2.4 2.2 12.3 12.3 12.5 0.9 1.0 1.2 187 IndusInd Bank ADD 867 900 4 656 8.9 756 26 61 75 (58.8) 132.4 22.9 33 14.2 11.6 — — — 1.8 1.6 1.4 5.5 11.2 12.5 0.5 1.1 1.3 205 Karur Vysya Bank BUY 46 65 41 37 0.5 799 4.7 7 9 60.5 39.0 42.7 10 7.0 4.9 — — — 0.6 0.6 0.5 5.6 7.4 10.0 2.7 3.7 5.3 1.6 Punjab National Bank REDUCE 32 32 (1) 339 4.6 10,481 0 4 6 (8.2) 858.1 36.1 71 7.4 5.4 — — — 0.6 0.6 0.5 0.7 5.4 6.8 — — — 28 RBL Bank BUY 229 270 18 137 1.9 597 9.5 19 24 (4.8) 96.0 28.5 24 12.4 9.6 — — — 1.1 1.1 1.0 4.9 8.5 10.1 0.6 1.2 1.6 54 State Bank of India BUY 275 340 24 2,456 33.4 8,925 24 30 39 46.6 24.8 30.4 12 9.3 7.1 — — — 1.3 1.1 1.0 8.8 10.0 11.7 0.1 0.1 0.1 179 Ujjivan Financial Services BUY 280 345 23 34 0.5 121 33.6 44 — 24.9 31.6 (100.0) 8 6.3 - — — — 1.4 1.1 — 17.0 19.3 NM 1.5 2.1 0.0 2.7 Ujjivan Small Finance Bank ADD 40 40 0 69 0.9 1,750 2 2 3 (3.1) (4.8) 82.5 22 22.9 12.5 — — — 2.2 2.0 1.7 10.1 8.9 14.1 0.0 0.0 0.0 1.0 Union Bank REDUCE 31 27 (11) 195 2.7 6,407 3 0 4 131.7 (86.2) 1,041.9 11 82.3 7.2 — — — 0.5 0.5 0.5 3.0 0.4 4.6 1.3 0.2 2.1 2.5 KOTAK INSTITUTIONALKOTAK YES Bank SELL 18 11 (38) 446 6.1 25,055 (1) (0) 0 95.4 49.9 131.1 NM NM 190.2 — — — 1.6 1.6 1.6 NM NM 0.7 0.0 0.0 0.0 44 Banks Attractive 20,163 274.3 116.2 28.4 26.0 22 16.9 13.4 1.8 1.6 1.5 8.2 9.7 11.1 0.6 0.8 0.9 1,286 - December 29, December29, 2020 Source: Company, Bloomberg, Kotak Institutional Equities estimates EQUITIES RESEARCH EQUITIES KOTAK INSTITUTIONAL EQUITIES RESEARCH 3 Kotak Institutional Equities: Valuation summary of KIE Universe stocks India Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) KOTAK INSTITUTIONAL EQUITIES RESEARCH INSTITUTIONALKOTAK EQUITIES Building Products Astral Poly Technik SELL 1,610 870 (46) 243 3.3 151 19.2 25 31 16.7 32.0 24.3 84 64 51 47.8 37.4 29.9 13.8 11.8 10.1 17.7 20.0 21 0.1 0.3 0.5 4.4 DailySummary Building Products Cautious 243 3.3 16.7 32.0 24.3 84 64 51 47.8 37.4 29.9 13.8 11.7 10.1 16.5 18.5 19.7 0.1 0.3 0.5 4.4 Capital goods ABB SELL 1,218 980 (20) 258 3.5 212 10 20 26 (43.5) 101.7 32.0 123 61 46 87.7 40.8 30.7 7.2 6.7 6.2 5.9 11.4 13.9 0.5 0.6 0.7 2.8 Ashoka Buildcon BUY 92 135 46 26 0.4 281 11.3 11.9 12.9 (18.1) 5.8 7.7 8.2 7.7 7.2 6.1 5.2 4.4 0.9 0.8 0.8 11.6 11.2 11.0 2.0 2.1 2.2 1.8 Bharat Electronics BUY 115 120 5 279 3.8 2,437 7.0 7.3 7.5 (6.9) 4.9 2.5 16.5 15.7 15.3 10.2 9.1 8.5 2.5 2.3 2.2 16.1 15.5 14.6 2.3 2.4 2.4 17.5 BHEL SELL 35 26 (27) 123 1.7 3,482 (3.8) 1.8 2.8 10.4 148.5 52.5 NM 19.1 12.5 (8.8) 6.9 5.3 0.4 0.4 0.4 NM 2.2 3.4 (4.8) 2.1 2.9 17.2 Carborundum Universal ADD 415 310 (25) 79 1.1 189 13.6 16.1 18.3 (5.3) 18.1 14.1 30 26 23 17.5 14.7 12.7 3.9 3.5 3.2 13.3 14.3 14.8 0.9 1.1 1.2 1.8 Cochin Shipyard BUY 363 520 43 48 0.6 132 35 43 43 (27.2) 20.4 1.1 10.3 8.5 8.4 5.3 5.2 4.8 1.2 1.1 1.0 12.0 13.4 12.5 3.2 3.5 3.8 1.9 Cummins India BUY 569 600 5 158 2.1 277 22 28 32 (14.8) 28.4 14.2 26 20 17.9 27.7 20.2 17.4 3.6 3.5 3.3 14.1 17.4 18.8 2.1 2.7 3.1 9.9 Dilip Buildcon BUY 397 515 30 54 0.7 137 25 45 61 (19.0) 83.2 35.2 16.1 8.8 6.5 6.0 4.5 3.9 1.4 1.2 1.0 8.9 14.5 16.7 0.1 0.2 0.3 1.0 IRB Infrastructure BUY 112 145 29 39 0.5 351 13 10 9 (37.8) (20.0) (10.9) 8.8 11.0 12.3 6.5 5.9 4.8 0.6 0.5 0.5 6.6 5.0 4.3 3.4 1.7 2.2 1.0 Kalpataru Power Transmission BUY 306 475 55 46 0.6 153 25 39 43 (2.4) 56.8 11.7 12.4 7.9 7.0 4.7 3.8 3.2 1.2 1.0 0.9 10.4 13.5 12.9 1.1 1.5 1.7 2.2 KEC International BUY 370 380 3 95 1.3 257 24.0 32 35 9.3 31.4 11.3 15.4 11.7 10.5 8.8 7.0 6.3 2.8 2.4 2.0 20 22 20 0.7 0.9 1.0 2.3 - L&T BUY 1,289 1,300 1 1,811 24.6 1,403 34 63 76 (46.9) 86.9 21.0 38 21 16.9 24.6 18.2 16.7 2.7 2.5 2.3 7.5 12.5 13.9 1.1 1.5 1.8 96 December29, 2020 Siemens SELL 1,573 1,150 (27) 560 7.6 356 35 40 42 65.5 12.6 6.7 45 40 37 31.6 27.8 26.1 5.4 5.0 4.6 12.7 13.1 12.8 0.6 0.7 0.8 14.0 Thermax BUY 911 850 (7) 108 1.5 113 18 29 36 (2.6) 55.2 24.6 50 32 26 33.8 23.0 18.6 33.8 23.0 18.6 6.8 10.3 12.3 1.2 1.6 2.1 0.9 Capital goods Attractive 3,684 50.1 (30.6) 74.2 17.3 36 21 17.7 2.4 2.2 2.0 6.5 10.6 11.5 1.0 1.4 1.7 170 Commercial & Professional Services SIS BUY 439 425 (3) 65 0.9 149 16 19 24 5.5 17.5 27.5 27 23 18.3 13.2 12.0 10.2 4.1 3.5 2.9 15.8 16.0 17.4 0.2 0.2 0.3 0.9 TeamLease Services ADD 2,581 2,550 (1) 44 0.6 17 45 67 93 118.9 50.2 38.1 58 38 28 39.7 29.0 22.4 6.8 5.8 4.8 12.5 16.3 18.8 — — — 0.8 Commercial & Professional Services Attractive 109 1.5 20.7 25.5 30.6 35 28 21 17.8 15.4 12.8 4.8 4.1 3.5 13.9 14.9 16.4 0.1 0.1 0.2 2 Commodity Chemicals Asian Paints REDUCE 2,684 2,000 (25) 2,574 35.0 959 27.4 37.2 44.0 0.7 35.8 18.3 98 72 61 59.6 47.0 41.1 22.3 19.2 16.6 24 29 29 0.5 0.7 0.8 75 Berger Paints SELL 741 505 (32) 720 9.8 971 7.0 9.8 11.6 3.2 40.5 18.5 106 75 64 64.4 47.9 41.3 23.0 19.4 16.4 23 28 28 0.2 0.4 0.5 11.3 Kansai Nerolac ADD 572 560 (2) 308 4.2 539 9.4 13.0 15.3 (5.5) 38.9 17.1 61 44 37 39.1 28.8 25.1 7.5 6.8 6.2 12.8 16.3 17.3 0.5 0.8 0.9 1.8 Tata Chemicals ADD 478 355 (26) 122 1.7 255 20.0 33.3 36.8 (36.9) 66.5 10.7 24 14.4 13.0 7.5 5.7 5.0 0.9 0.9 0.8 3.9 6.3 6.7 1.5 2.4 2.7 28 Commodity Chemicals Neutral 3,724 50.7 (6.2) 40.5 17.2 86 61 52 46.7 36.0 31.7 11.6 10.5 9.5 13.5 17.2 18.1 0.5 0.7 0.8 116 Construction Materials ACC BUY 1,622 1,800 11 305 4.1 188 76.1 90.8 102.1 5.3 19.2 12.4 21 17.9 15.9 9.7 8.1 6.7 2.5 2.3 2.2 12.1 13.5 14.1 2.3 2.8 3.1 39 Ambuja Cements BUY 247 300 21 491 6.7 1,986 12.2 14.4 17.4 15.6 18.0 20.5 20 17.1 14.2 7.7 6.2 4.9 2.1 1.9 1.7 10.3 11.8 12.9 6.9 1.1 1.3 30 Dalmia Bharat BUY 1,055 1,250 19 197 2.7 187 37.5 42.1 63.1 168.8 12.2 50.0 28 25 16.7 8.6 7.9 6.1 1.8 1.7 1.5 6.6 7.0 9.7 — — — 3.2 Grasim Industries ADD 907 875 (3) 597 8.1 657 54.2 76.5 100.1 2.9 41.2 30.9 16.7 11.9 9.1 8.5 6.3 4.9 1.0 0.9 0.8 6.1 8.0 9.7 0.2 0.4 0.6 25 J K Cement ADD 1,906 2,000 5 147 2.0 77 81.5 116.9 138.3 26.8 43.4 18.4 23 16.3 13.8 11.5 8.7 7.4 4.1 3.3 2.7 19.1 23 22 0.5 0.5 0.5 3.7 JK Lakshmi Cement BUY 337 350 4 40 0.5 118 22.9 29.6 35.8 (2.6) 29.6 20.7 14.7 11.4 9.4 6.6 6.1 5.7 2.1 1.8 1.5 14.9 16.7 17.3 1.0 1.3 1.6 1.7 Orient Cement ADD 84 75 (11) 17 0.2 205 8.9 6.7 8.5 109.6 (24.1) 26.9 9.5 12.6 9.9 5.1 5.9 5.0 1.4 1.3 1.2 15.3 10.5 12.3 2.4 2.4 2.4 0.8 Shree Cement SELL 23,716 17,500 (26) 856 11.6 36 543.6 774.9 904.9 24.9 42.6 16.8 44 31 26 23.2 17.5 14.9 5.9 5.1 4.3 14.3 17.8 17.8 0.5 0.5 0.5 23 UltraTech Cement ADD 5,142 5,250 2 1,484 20.2 289 177.5 231.7 281.1 33.6 30.6 21.3 29 22 18.3 14.8 11.9 10.1 3.4 3.0 2.6 12.3 14.2 15.0 0.3 0.4 0.5 53 Construction Materials Attractive 4,133 56.2 21.1 30.5 23.1 25 19.4 15.8 11.5 9.1 7.5 2.4 2.2 1.9 9.5 11.2 12.3 1.3 0.7 0.8 181 Source: Company, Bloomberg, Kotak Institutional Equities estimates 4 KOTAK INSTITUTIONAL EQUITIES RESEARCH 4 Kotak Institutional Equities: Valuation summary of KIE Universe stocks 5 Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Consumer Durables & Apparel Crompton Greaves Consumer SELL 357 255 (29) 224 3.0 627 8.0 9.5 10.6 1.1 18.9 11.7 45 38 34 33 29 25 12.4 9.9 8.0 31 29 26 0.8 0.7 0.7 10.5 Havells India SELL 904 600 (34) 566 7.7 626 14.7 16.2 18.6 24.8 10.3 14.7 62 56 49 41 38 33 11.7 10.4 9.3 20 19.7 20 0.6 0.6 0.7 28 Page Industries REDUCE 27,583 21,000 (24) 308 4.2 11 285 428 499 (7.5) 50.3 16.7 97 64 55 62 44 37 32.3 26.0 21.6 36 45 43 0.6 0.9 1.1 19.3 Polycab ADD 1,050 970 (8) 157 2.1 149 44 52 58 (13.7) 18.0 9.9 24 20 18.2 15 13 11 3.6 3.1 2.7 16.1 16.5 15.9 0.6 0.7 0.7 6.4 TCNS Clothing Co. REDUCE 451 390 (13) 28 0.4 66 (5) 14 17 (149.5) 358.7 22.9 NM 33 27 46 12 10.2 4.4 3.7 3.2 NM 12.4 12.9 — — — 0.4 Vardhman Textiles ADD 1,076 720 (33) 62 0.8 57 25 90 104 (70.8) 260.6 16.1 43 12.0 10.3 15.3 7.4 6.4 1.0 0.9 0.9 2.3 8.0 8.7 1.2 1.9 2.3 0.6 Voltas SELL 816 655 (20) 270 3.7 331 14.0 21.3 24.7 (13.6) 51.8 16.1 58 38 33 51 32 28 5.9 5.3 4.8 10.5 14.5 15.2 0.4 0.7 0.8 22 Whirlpool SELL 2,581 1,750 (32) 327 4.5 127 33 49 61 (12.4) 49.1 24.5 78 53 42 53 37 29 11.6 10.4 9.5 15.6 21 24 0.4 0.8 1.2 2.7 Consumer Durables & Apparel Cautious 1,941 26.4 (13.3) 41.6 57 40 35 37 27 23 7.4 6.6 12.9 16.3 16.7 0.6 0.7 91 Consumer Staples Bajaj Consumer Care ADD 220 230 5 32 0.4 148 15.0 14.8 15.7 19.7 (1.3) 6.1 14.6 14.8 14.0 11.3 11.3 10.2 4.3 3.8 3.4 31 27 26 3.6 3.6 4.1 1.7 Britannia Industries ADD 3,604 4,050 12 868 11.8 240 78 81 93 32.8 2.9 15.8 46 45 39 35 33 29 29.1 21.2 17.8 50 54 50 3.0 1.4 1.6 42 Colgate-Palmolive (India) ADD 1,583 1,680 6 431 5.9 272 34 38 43 18.4 11.8 14.8 47 42 37 30.6 27.5 24.2 26.5 25.3 23.9 57 61 67 2.0 2.2 2.6 17.7 Dabur India REDUCE 525 480 (9) 928 12.6 1,767 9.7 11.1 12.5 12.6 14.0 12.5 54 47 42 44 38 33 12.8 11.6 10.6 25 26 26 1.1 1.3 1.5 29 Godrej Consumer Products ADD 727 750 3 744 10.1 1,022 15.7 18.5 21.2 13.7 18.0 14.5 46 39 34 32 27 24 8.2 7.4 6.7 18.9 19.8 21 1.0 1.3 1.6 16.2 Hindustan Unilever ADD 2,389 2,500 5 5,613 76.4 2,343 35 43 51 11.4 23.3 18.0 69 56 47 48 40 34 12.9 12.3 11.8 32 23 26 1.3 1.6 1.9 73 ITC BUY 210 250 19 2,578 35.1 12,318 10.4 12.4 13.4 (9.8) 18.5 8.3 20 17.0 15.7 14.4 11.9 10.8 3.9 3.8 3.7 18.9 22 23 4.3 5.1 5.5 79 Jyothy Laboratories ADD 151 160 6 55 0.8 367 6.0 6.3 7.1 27.2 4.6 13.5 25 24 21 17.5 16.6 14.8 4.2 3.9 3.7 17.3 16.9 18.0 2.3 2.7 3.0 1.0 Marico ADD 407 400 (2) 525 7.1 1,290 8.9 9.9 11.0 10.1 10.6 12.0 46 41 37 33 29 26 15.9 14.6 13.5 36 37 38 1.7 1.9 2.1 17.7 Nestle India REDUCE 18,597 16,000 (14) 1,793 24.4 96 226 265 307 10.5 17.5 15.6 82 70 61 54 47 41 80.5 53.7 38.8 105 92 74 1.0 0.8 0.9 38 Tata Consumer Products ADD 602 530 (12) 555 7.6 922 10.1 12.3 14.3 26.4 21.7 16.6 60 49 42 33 29 25 3.8 3.7 3.5 6.6 7.6 8.4 0.6 0.7 0.8 33 United Breweries ADD 1,164 1,125 (3) 308 4.2 264 3.7 19.7 24.9 (77.3) 435.6 26.0 316 59 47 83 30 25 8.7 7.6 6.8 2.8 13.8 15.4 0.1 0.5 0.7 10.5 United Spirits ADD 580 620 7 421 5.7 727 7.0 14.1 17.2 (38.9) 101.5 22.0 83 41 34 41 25 22 9.5 7.7 6.6 12.1 21 21 — — 0.9 16.3 Varun Beverages BUY 897 1,000 11 259 3.5 289 10.9 28.8 35.9 (32.7) 163.8 24.6 82 31 25 24 14 12 7.0 5.8 4.8 9.0 20 21 0.1 0.3 0.3 4.3 Consumer Staples Attractive 15,110 205.6 2.5 21.9 13.6 46 38 33 33 27 24 9.2 8.6 8.1 20.0 23 24 1.8 2.0 2.3 379 Diversified Financials Bajaj Finance REDUCE 5,204 3,000 (42) 3,136 42.7 600 73 135 172 (17) 85 27 71 39 30 — — — 8.6 7.2 6.0 12.8 20 22 0.1 0.3 0.3 284 Bajaj Finserv BUY 8,995 8,000 (11) 1,431 19.5 159 270 425 528 28 58 24 33 21 17.0 — — — 4.6 3.9 3.3 13.7 19.9 21 0.2 0.2 0.2 105 Cholamandalam BUY 386 350 (9) 317 4.3 820 20.0 26.4 32.7 56 32.0 23.8 19.3 14.6 11.8 — — — 3.5 3.0 2.4 18.4 20 21 0.6 0.8 0.9 25 HDFC ADD 2,476 2,240 (10) 4,457 60.6 1,789 61 68 81 (40.3) 10 20.4 40 37 30 — — — 4.1 3.8 3.5 11.0 10.8 12.0 0.9 1.0 1.2 162 HDFC AMC REDUCE 2,895 1,950 (33) 616 8.4 213 57 68 79 (3.5) 19 15.8 51 43 37 — — — 13.5 11.8 10.3 28 29 30 1.1 1.3 1.5 12.8 IIFL Wealth ADD 1,010 1,100 9 88 1.2 88 34.7 45.1 60.7 46 29.7 34.6 29 22 16.6 — — — 3.1 2.9 2.7 10.4 13.4 17.0 5.0 2.9 3.0 0.5 Daily Summary India L&T Finance Holdings ADD 94 90 (4) 188 2.6 2,005 4 9 13 (55.7) 136 49.6 25 10.6 7.1 — — — 1.2 1.1 1.0 5.1 11.2 14.9 1.5 1.7 1.7 18.6 LIC Housing Finance ADD 367 400 9 185 2.5 505 55.3 73.8 85.9 16 33.4 16.5 6.6 5.0 4.3 — — — 1.1 0.9 0.8 14.5 17.0 17.2 2.5 3.4 3.9 33 Mahindra & Mahindra Financial BUY 176 160 (9) 217 3.0 1,232 8.3 17.2 20.7 (44) 107.0 20.9 21 10.3 8.5 — — — 1.6 1.4 1.3 7.7 13.1 14.3 0.7 2.0 2.4 23 Muthoot Finance REDUCE 1,218 1,150 (6) 489 6.6 401 83 94 104 11.3 12 11.0 14.6 13.0 11.7 — — — 3.5 2.9 2.4 26 24 22 1.4 1.5 1.7 40 Shriram City Union Finance BUY 1,065 1,400 31 70 1.0 66 138 179 200 (9.0) 30 11.7 7.7 5.9 5.3 — — — 0.9 0.8 0.7 12.0 13.9 13.8 1.7 2.5 2.8 0.6 Shriram Transport BUY 1,016 1,100 8 257 3.5 253 74.5 113.9 149.1 (32) 53.0 30.9 13.6 8.9 6.8 — — — 1.3 1.1 1.0 9.6 12.9 15.0 1.1 1.7 2.2 59 Diversified Financials Attractive 11,513 156.6 (16.5) 37.9 20.0 33 24 20 3.9 3.5 3.1 11.6 14.2 15.6 0.7 0.8 1.0 764 Source: Company, Bloomberg, Kotak Institutional Equities estimates KOTAK INSTITUTIONALKOTAK - December 29, December29, 2020 EQUITIES RESEARCH EQUITIES KOTAK INSTITUTIONAL EQUITIES RESEARCH 5 Kotak Institutional Equities: Valuation summary of KIE Universe stocks India Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo KOTAK INSTITUTIONAL EQUITIES RESEARCH INSTITUTIONALKOTAK EQUITIES Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Electric Utilities CESC BUY 604 800 32 80 1.1 133 91 105 113 (8) 16.0 7.7 6.7 5.7 5.3 4.9 4.4 3.9 0.6 0.5 0.5 9.3 9.9 9.9 2.1 2.2 2.4 2.3 DailySummary JSW Energy BUY 69 65 (6) 113 1.5 1,640 5.2 5.3 6.3 (18) 1 18.9 13.3 13.1 11.0 6.1 5.3 5.0 0.9 0.8 0.8 7.1 6.7 7.4 — — — 2.4 NHPC ADD 23 26 13 232 3.2 10,045 3.0 3.2 3.2 5.8 6 1.0 7.8 7.3 7.3 10.8 9.7 9.1 0.7 0.7 0.7 9.3 9.5 9.2 7.2 7.8 7.8 1.9 NTPC BUY 100 125 24 994 13.5 9,895 12.7 15.0 16.0 14.2 18.2 6.6 7.9 6.7 6.3 8.1 6.2 5.3 0.8 0.8 0.7 10.7 11.7 11.5 3.4 4.5 4.8 48 Power Grid BUY 192 220 15 1,002 13.6 5,232 21.8 26 28 8 19.1 7.8 8.8 7.4 6.9 6.7 6.0 5.5 1.4 1.3 1.2 17.0 18.6 18.3 5.6 6.7 7.2 28 Tata Power BUY 77 67 (13) 247 3.4 3,196 4.0 5.3 6.0 (11) 33 14.0 19.4 14.6 12.8 8.4 8.2 7.8 1.1 1.0 1.0 6.3 7.4 7.8 — — — 26 Electric Utilities Attractive 2,668 36.3 8.2 17.4 7.3 8.8 7.5 7.0 1.0 0.9 0.8 11.2 12.1 12.0 4.1 4.9 5.2 109 Fertilizers & Agricultural Chemicals Bayer Cropscience SELL 5,534 3,900 (30) 249 3.4 45 140.8 156.4 176.5 8.9 11.1 12.8 39 35 31 28 25 21 8.1 6.8 5.8 22 21 20 0.5 0.6 0.6 2.3 Dhanuka Agritech SELL 815 650 (20) 39 0.5 48 37.0 40.8 45.8 24.4 10.4 12.2 22.0 20.0 17.8 16.5 14.6 12.7 4.6 4.0 3.5 23 21 21 1.1 1.5 2.0 0.8 Godrej Agrovet SELL 530 455 (14) 102 1.4 192 15.4 18.0 20.9 33.5 17.1 16 34 29 25 18 16 13 4.1 3.7 3.3 12.7 13.4 13.8 1.0 1.2 1.4 1.1 PI Industries SELL 2,225 1,700 (24) 337 4.6 148 50.9 59.5 70.8 54.2 17 19 44 37 31 31 25 21 10.1 8.4 6.9 26 25 24 0.3 0.5 0.6 16.9 - Rallis India ADD 274 310 13 53 0.7 195 11.8 14.9 18.0 30.5 26.0 21.1 23.2 18.4 15.2 16.4 13.0 10.7 3.4 2.9 2.5 15.3 17.0 17.9 1.0 1.1 1.2 2.0 December 29, December29, 2020 UPL SELL 453 375 (17) 346 4.7 765 32.4 37.3 41.2 39.6 15.1 10.3 14 12.2 11.0 7.6 6.8 6.1 1.9 1.7 1.5 14.4 14.9 14.7 1.8 2.1 2.3 59 Fertilizers & Agricultural Chemicals Cautious 1,126 15.3 36.3 15.7 13.1 25 21 18.8 12.4 11.0 9.8 3.8 3.4 3.0 15.6 15.8 15.7 1.0 1.1 1.3 82 Gas Utilities GAIL (India) BUY 123 140 14 553 7.5 4,510 8.0 10.4 11.5 (39.2) 29.4 10.8 15.3 11.8 10.7 11.1 8.4 7.3 1.2 1.1 1.1 8.0 9.9 10.5 3.3 4.1 4.9 31 GSPL SELL 223 200 (10) 126 1.7 564 13.2 11.8 8.0 (23.1) (10.6) (32.2) 16.8 18.8 27.8 7.1 7.5 9.9 1.7 1.6 1.5 10.6 8.7 5.6 0.9 1.1 0.9 2.3 Indraprastha Gas ADD 490 500 2 343 4.7 700 16.1 23.0 25.6 (3.2) 42.4 11.4 30.4 21.3 19.1 21.5 15.3 13.5 5.8 4.9 4.2 21 25 24 0.6 1.0 1.4 21 Mahanagar Gas BUY 1,052 1,200 14 104 1.4 99 65.3 90.8 96.4 (12.5) 39.1 6.1 16.1 11.6 10.9 10.2 7.3 6.5 3.1 2.7 2.3 20 25 23 2.4 3.3 4.0 14.9 Petronet LNG BUY 251 300 19 377 5.1 1,500 19.6 21.7 24.1 11.0 11.0 10.8 12.8 11.6 10.4 7.1 6.5 5.9 3.2 3.1 2.9 26 27 29 5.8 6.9 8.1 16.2 Gas Utilities Attractive 1,502 20.4 (20.9) 22.5 7.9 16.6 13.5 12.5 10.4 8.5 7.7 2.0 1.9 1.8 12.2 14.0 14.2 3.0 3.8 4.5 85 Health Care Services Apollo Hospitals ADD 2,389 2,240 (6) 332 4.5 139 -3.4 40 60 (119) 1,261 50 NM 60.3 40.1 26.1 19.2 17.2 10.0 9.1 7.9 NM 15.9 21 (0.1) 0.7 1.0 51 Dr Lal Pathlabs SELL 2,298 1,400 (39) 192 2.6 83 30.0 39.3 42.7 10.8 31.1 8.6 76.6 58.4 53.8 49.2 36.7 33.7 15.9 13.3 11.4 22 25 23 0.4 0.5 0.6 6.5 HCG BUY 166 150 (9) 21 0.3 143 (8.7) (2.4) (1.7) 28 73 27 NM NM NM 16.8 9.3 8.0 2.5 2.5 2.6 NM NM NM — — — 0.2 Metropolis Healthcare SELL 1,984 1,450 (27) 101 1.4 51 37.1 41.8 45.5 23.8 12.6 9 53.4 47.4 43.6 34.7 30.0 27.0 15.6 12.8 10.8 32 30 27 0.6 0.6 0.7 3.4 Narayana Hrudayalaya BUY 446 375 (16) 91 1.2 204 -7.8 7.2 10.7 (233.6) 193 48 NM 61.7 41.7 86.9 19.6 15.8 9.3 8.1 6.8 NM 14.0 17.7 — — — 1.2 Health Care Services Attractive 820 11.2 (70) 475 31 286.2 49.8 37.9 24.9 17.2 15.2 7.8 7.0 6.1 2.7 14.0 16.1 0.1 0.5 0.6 63 Hotels & Restaurants Jubilant Foodworks ADD 2,726 2,700 (1) 360 4.9 133 19 43 53 (20) 128.2 25 145.1 63.6 51.0 42.8 27.4 23.1 28.1 20.6 16.3 21 37 36 0.2 0.6 0.7 34 Lemon Tree Hotels BUY 40 35 (13) 32 0.4 790 -1.5 0.0 0.7 (1,168) 99 5,898 NM NM 59.8 62.8 19.3 13.2 4.5 4.7 4.7 NM NM 7.9 — 0.9 1.4 1.8 Hotels & Restaurants Attractive 391 5.3 (57) 343 35 303.8 68.5 50.9 44.6 26.0 21.0 19.7 16.1 13.5 6.5 23 26 0.2 0.6 0.8 36 Insurance HDFC Life Insurance ADD 679 650 (4) 1,371 18.7 2,010 6.8 7.4 7.8 5.8 8.2 6.3 99 92 86 — — — 17.9 16.5 15.2 18.8 18.7 18.3 0.3 0.3 0.3 47 ICICI Lombard SELL 1,498 980 (35) 681 9.3 454 34.5 33.7 38.3 31 (2) 14 43 44 39 — — — 9.0 7.9 6.8 23 19.6 18.7 0.2 0.5 0.5 13.3 ICICI Prudential Life BUY 501 530 6 719 9.8 1,436 8.5 9.6 9.9 14 13.2 3.4 59 52 50 — — — 8.5 7.5 6.7 15.2 15.2 14.0 0.3 0.3 0.3 14.0 Max Financial Services NR 696 — — 240 3.3 343 9.5 26.7 16.0 (6) 180 (40) 73 26 43 — — — — — — 13.5 38 17.3 0.1 0.9 0.2 16.2 SBI Life Insurance BUY 902 1,150 28 902 12.3 1,001 17.8 20.8 23.6 25.3 16.9 13.1 51 43 38 — — — 9.5 8.0 6.8 20 20 19.3 0.3 0.4 0.4 18.8 Insurance Attractive 3,913 53.2 19.5 21.7 2.2 62.4 51.3 50 11.0 8.9 8.3 17.6 17.3 16.5 0.2 0.2 0.3 109 Source: Company, Bloomberg, Kotak Institutional Equities estimates 6 KOTAK INSTITUTIONAL EQUITIES RESEARCH 6 Kotak Institutional Equities: Valuation summary of KIE Universe stocks 7 Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Internet Software & Services Info Edge SELL 4,629 2,910 (37) 595 8.1 128.3 25.8 43.4 53.3 (4.2) 68.6 22.7 179.6 106.6 86.9 170.7 99.4 79.0 13.0 11.9 10.8 9.5 11.7 13.1 0.1 0.2 0.3 32 Just Dial SELL 621 550 (11) 38 0.5 61.8 25.9 29.9 35.5 (38.2) 15.3 18.8 23.9 20.8 17.5 16.4 13.7 11.4 3.1 2.7 2.3 12.7 14.0 14.4 — — — 23 Internet Software & Services Cautious 634 8.6 (18.3) 51.2 21.7 129.1 85.4 70.1 121.6 79.7 65.2 11.0 9.9 8.9 8.5 11.6 12.7 0.1 0.2 0.3 55 IT Services HCL Technologies ADD 922 945 3 2,501 34.0 2,716 45.3 50.0 55.1 11.1 10.4 10.1 20.3 18.4 16.7 12.3 11.1 9.8 4.2 3.6 3.1 23 21 19.8 1.1 1.5 1.5 108 Infosys BUY 1,240 1,400 13 5,283 71.9 4,250 43.7 48.9 55.4 12.2 12.0 13.2 28.4 25.3 22.4 18.8 16.8 14.8 7.2 6.5 5.9 27 27 28 2.1 2.4 2.8 180 L&T Infotech ADD 3,641 3,350 (8) 636 8.7 176 101.3 115.3 138.1 17 13.8 19.7 35.9 31.6 26.4 23.8 21.6 18.4 9.8 8.2 6.8 30 28 28 0.9 1.0 1.1 24 Mindtree SELL 1,609 1,225 (24) 265 3.6 165 60.9 67.1 73.3 59 10 9 26.4 24.0 22.0 16.7 15.4 13.9 7.0 5.8 4.9 29 26 24 1.1 1.3 1.4 31 Mphasis REDUCE 1,561 1,350 (13) 291 4.0 187 66.3 74.3 83.3 4 12.0 12.1 23.5 21.0 18.7 15.4 13.5 11.9 4.5 4.1 3.6 20 20 20 2.2 2.2 2.2 8.3 TCS REDUCE 2,929 2,800 (4) 10,992 149.5 3,750 86.6 99.6 110.7 0 15.0 11.2 33.8 29.4 26.5 23.7 21.0 18.8 12.9 10.9 10.0 38 40 39 1.2 2.0 3.0 160 Tech Mahindra BUY 947 1,020 8 825 11.2 880 47.5 55.4 64.3 3.5 16.8 16.0 20.0 17.1 14.7 11.4 9.8 8.4 3.5 3.2 2.9 18.3 19.6 20 2.3 2.5 2.7 64 Wipro ADD 383 380 (1) 2,188 29.8 5,649 18.0 20.0 21.9 8.6 10.7 9.6 21.2 19.2 17.5 14.0 12.8 11.4 4.1 3.4 3.0 18.7 19.1 18.2 0.5 1.3 1.3 78 IT Services Attractive 22,982 312.7 6.0 12.0 11.7 28.1 25.1 22.5 18.7 16.7 14.9 7.4 6.4 5.7 26 26 25 1.4 2.0 2.5 654 Media DB Corp. REDUCE 83 81 (3) 15 0.2 175 5.3 14.1 14.2 (66.5) 166.7 1.2 15.7 5.9 5.8 5.1 2.5 2.7 0.8 0.8 0.9 5.4 14.3 14.6 2.4 14.4 15.6 0.3 Jagran Prakashan REDUCE 43 37 (13) 12 0.2 281 3.9 7.3 8.4 (43.6) 87 NA 10.9 5.8 NA 2.5 1.6 NA 0.6 0.6 NA 5.7 10.3 11.5 4.7 11.7 11.7 0.2 PVR BUY 1,310 1,500 14 72 1.0 55 -92.9 39.5 59.5 (421) 143 51 NM 33.2 22.0 (22.7) 11.8 9.1 3.4 3.2 2.8 NM 9.9 13.5 (0.7) 0.3 0.5 42 Sun TV Network REDUCE 491 435 (11) 193 2.6 394 38.9 39.2 41.4 10 0.7 5.6 12.6 12.5 11.9 8.6 8.4 8.0 3.2 3.1 3.0 26 25 26 5.1 5.6 6.1 18.2 Zee Entertainment Enterprises ADD 220 225 2 211 2.9 960 10.9 16.5 17.9 (2.1) 51.4 8.4 20.2 13.3 12.3 12.7 8.4 7.3 2.1 1.9 1.7 10.9 15.3 14.9 1.6 1.8 2.0 63 Media Cautious 504 6.9 (26.5) 67.3 9.6 22.2 13.3 12.1 12.8 7.9 7.0 2.3 2.2 2.0 10.5 16.4 16.7 2.7 3.7 4.0 124 Metals & Mining Hindalco Industries BUY 240 330 38 539 7.3 2,220 19.2 28.9 31.5 7.7 50.6 9 12.5 8.3 7.6 6.7 5.4 4.8 0.9 0.8 0.7 7.1 9.8 9.7 0.4 0.4 0.4 53 Hindustan Zinc BUY 242 295 22 1,022 13.9 4,225 17.7 20.3 22.7 9.7 14.7 11.8 13.7 11.9 10.7 8.3 7.0 6.3 3.2 3.2 3.2 21 27 30 8.8 8.4 9.4 4.4 Jindal Steel and Power BUY 267 320 20 272 3.7 1,020 30.0 25.8 26.1 492 (14) 1 8.9 10.3 10.2 5.1 4.9 4.5 0.8 0.7 0.7 9.2 7.4 7.0 — — — 35 JSW Steel ADD 387 375 (3) 934 12.7 2,402 22.2 28.8 34.5 120.1 30 19.8 17.4 13.4 11.2 8.7 6.9 5.9 2.2 1.9 1.7 13.7 15.5 16.0 0.5 0.5 0.5 37 National Aluminium Co. SELL 43 30 (29) 79 1.1 1,866 2.4 2.0 2.9 228 (16) 42.9 17.5 20.9 14.6 5.5 7.4 6.7 0.8 0.7 0.7 4.4 3.6 5.0 0.0 2.4 3.4 8.9 NMDC REDUCE 116 95 (18) 355 4.8 2,931 14.0 10.3 10.0 (4.3) (26.2) (3) 8.3 11.2 11.6 8.4 19.2 (24.9) 1.2 1.1 1.1 14.5 10.1 9.3 3.0 4.5 4.3 13.4 Tata Steel BUY 633 800 26 728 9.9 1,146 53.3 82.1 96.1 51 54 17 11.9 7.7 6.6 7.1 5.7 5.4 1.0 0.9 0.8 8.3 11.9 12.4 2.4 2.7 2.7 132 Vedanta BUY 163 145 (11) 608 8.3 3,717 15.2 20.3 23.4 133 34 15.0 10.8 8.0 7.0 4.7 3.9 3.4 1.2 1.2 1.1 10.8 14.8 16.3 17.1 9.2 10.2 80 Metals & Mining Attractive 4,537 61.7 55.1 23.7 12.9 12.5 10.1 8.9 6.7 5.8 5.3 1.4 1.2 1.1 10.9 12.4 12.9 5.0 4.1 4.5 364 India Daily Summary India Source: Company, Bloomberg, Kotak Institutional Equities estimates KOTAK INSTITUTIONALKOTAK - December 29, December29, 2020 EQUITIES RESEARCH EQUITIES KOTAK INSTITUTIONAL EQUITIES RESEARCH 7 Kotak Institutional Equities: Valuation summary of KIE Universe stocks India Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo KOTAK INSTITUTIONAL EQUITIES RESEARCH INSTITUTIONALKOTAK EQUITIES Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Oil, Gas & Consumable Fuels BPCL BUY 383 425 11 830 11.3 1,967 37 37 39 250.1 0.1 6.1 10.4 10.4 9.8 7.9 8.2 7.4 2.1 1.9 1.7 20.8 18.9 18.3 4.5 4.8 5.1 51.1 DailySummary Coal India BUY 138 180 31 848 11.5 6,163 17 17 18 (36) 0.4 4.8 7.9 7.9 7.5 8.3 6.8 6.0 2.8 2.9 3.0 34.1 36.1 39.6 14.5 14.5 14.5 29.1 HPCL BUY 215 260 21 327 4.5 1,524 46 33 35 548.6 (27.8) 3.4 4.6 6.4 6.2 6.1 7.4 6.7 1.0 0.9 0.8 22.5 14.4 13.8 6.5 6.2 8.0 23.7 IOCL BUY 92 100 9 863 11.7 9,181 13.8 13.3 14.1 449.2 (3.6) 6.5 6.7 6.9 6.5 5.9 5.8 5.5 0.8 0.8 0.7 13.0 11.7 11.7 6.8 6.5 6.9 25.8 Oil India SELL 111 70 (37) 121 1.6 1,084 4 6 9 (82) 71.3 52.3 30.5 17.8 11.7 9.8 7.9 6.3 0.5 0.5 0.5 1.6 2.7 4.1 0.7 2.2 3.4 2.0 ONGC SELL 94 60 (36) 1,180 16.1 12,580 5 7 12 (65) 50.5 73.2 20.1 13.4 7.7 5.3 4.5 3.4 0.5 0.5 0.5 2.5 3.7 6.2 2.1 3.1 4.8 35.5 Reliance Industries ADD 2,003 2,150 7 11,874 161.5 6,032 67 90 110 0.6 34.4 22.4 29.8 22.2 18.1 15.8 10.1 9.5 2.4 2.1 2.1 8.5 10.4 12.1 0.3 0.4 0.4 425.6 Oil, Gas & Consumable Fuels Attractive 16,043 218.3 12.7 20.9 21.0 19.0 15.7 13.0 10.5 8.0 7.3 1.7 1.5 1.4 8.8 9.5 11.1 1.9 2.0 2.2 593 Pharmaceuticals Aurobindo Pharma REDUCE 908 830 (9) 532 7.2 586 59 60 63 21.8 1 6.0 15.3 15.2 14.3 9.2 8.7 7.8 2.4 2.1 1.9 15.7 14.0 13.2 0.8 1.0 1.2 40.5 Biocon SELL 466 240 (48) 559 7.6 1,202 7.8 9.9 11.3 26 27 14.4 60 47 41 26.6 20.6 18.3 6.9 6.2 5.5 11.5 13.2 13.5 0.6 0.7 0.9 27.2 Cipla BUY 830 915 10 669 9.1 806 29.7 33 49 54.9 12 46 28 24.9 17.0 15.4 13.9 9.6 3.7 3.3 2.9 13.3 13.4 16.9 0.7 0.8 1.1 84.1 - Divis Laboratories REDUCE 3,766 3,000 (20) 1,000 13.6 265 71 86 97 37 21 13.0 53 43.9 38.8 37.2 30.9 27.2 11.7 10.0 8.6 22.1 22.7 22.0 (0.7) (0.8) (0.9) 63.5 December 29, December29, 2020 Dr Reddy's Laboratories SELL 5,202 4,000 (23) 865 11.8 166 157 203 267 21 29 31.5 33 25.6 19.5 18.7 14.4 11.3 4.9 4.2 3.5 14.8 16.4 18.1 0.5 0.6 0.6 123.0 Laurus Labs REDUCE 348 310 (11) 186 2.5 536 17.1 18.7 23 257.9 9 22 20 18.6 15.2 14.1 12.2 9.6 6.9 5.1 3.8 34.1 27.2 24.9 — — — 22.9 Lupin ADD 984 1,000 2 446 6.1 450 27 42 51 24.5 56 21 36 23 19.2 15.8 11.0 9.1 3.3 2.9 2.6 8.9 12.5 13.4 0.4 0.6 0.8 48.8 Sun Pharmaceuticals ADD 587 525 (11) 1,408 19.2 2,406 21.2 23.7 28 27.0 11 17 28 25 21.1 16.1 13.9 11.9 3.0 2.7 2.5 10.9 11.6 11.6 0.2 0.8 0.9 73.5 Torrent Pharmaceuticals REDUCE 2,795 2,550 (9) 473 6.4 169 71 88 104 23.6 24 17 39 32 27 19.3 16.8 14.9 8.4 7.2 6.1 21.4 22.7 22.6 0.9 1.1 1.3 21.4 Pharmaceuticals Attractive 6,139 83.5 32.5 17 21 31 27 21.9 17.6 14.9 12.4 4.3 3.8 3.3 13.8 14.3 15.1 0.3 0.5 0.6 505 Real Estate Brigade Enterprises BUY 247 230 (7) 51 0.7 204 4.7 13 17 (26) 177 31 52.0 18.8 14.4 16.8 6.8 5.7 2.2 2.0 1.8 4.2 11.1 13.2 1.0 1.0 1.0 0.9 DLF BUY 233 200 (14) 577 7.9 2,475 4.7 8.1 8.8 297 72 10 50 28.9 26.4 42.4 30.8 30.5 1.6 1.6 1.5 3.3 5.6 5.8 0.9 0.9 0.9 39.5 Embassy Office Parks REIT ADD 346 375 9 305 4.2 772 11.3 13.4 15.4 14 19 15 31 26 22 18.9 16.8 15.4 1.2 1.3 1.4 4.0 4.9 6.0 6.4 7.5 8.6 3.5 Godrej Properties SELL 1,424 700 (51) 359 4.9 252 10.2 13.3 33.1 (5.2) 31 149.0 140 107 43 ##### 168.4 60.9 7.1 6.7 5.8 5.2 6.4 14.4 — — — 26.0 Mindspace REIT ADD 332 330 (1) 197 2.7 593 14 16 18 69.4 9.5 13 23.0 21.0 18.5 18.6 15.0 13.5 1.2 1.2 1.2 9.1 5.7 6.5 2.4 6.1 6.6 2.3 Oberoi Realty ADD 538 570 6 195 2.7 364 21 26 31 13.3 21.0 18 25.0 20.7 17.5 19.0 16.2 13.5 2.1 1.9 1.7 8.7 9.7 10.4 0.4 0.4 0.4 4.2 Prestige Estates Projects ADD 272 275 1 109 1.5 401 4.0 11.5 20 (57.9) 185 71 68 24 13.9 9.9 7.6 6.2 2.0 1.9 1.7 3.0 8.1 12.6 0.6 0.6 0.6 2.1 Sobha BUY 354 400 13 34 0.5 95 11 33 50 (64) 212.3 51.0 33.3 10.7 7.1 6.4 4.7 4.1 1.4 1.2 1.1 4.1 12.2 16.5 2.0 2.0 2.0 2.1 Sunteck Realty BUY 350 300 (14) 51 0.7 140 8.8 18.4 16 23.0 109 (13) 40 19.0 21.8 30.6 15.3 17.0 1.6 1.5 1.4 4.1 8.2 6.7 0.3 0.3 0.3 2.8 Real Estate Attractive 1,879 25.6 77.2 49 26 43 29 22.8 23.7 17.4 14.9 1.9 1.8 1.8 4.4 6.3 7.7 1.6 2.1 2.3 84 Retailing Aditya Birla Fashion and Retail BUY 164 180 10 136 1.9 915 (5.7) 2.0 3.5 (201.1) 134.7 78.9 NM 83 47 35.7 10.6 9.2 7.1 6.0 5.3 NM 7.9 12.1 — — — 7.2 Avenue Supermarts SELL 2,678 1,475 (45) 1,735 23.6 648 15.6 33 42 (25.5) 108.6 27.7 171 82 64 111 55 43 14.3 12.2 10.3 8.7 16.1 17.3 — — — 23.5 Titan Company ADD 1,544 1,325 (14) 1,370 18.6 888 8.4 20 26 (49.9) 137.3 28.2 183 77 60 96 49 39 19.2 16.3 13.8 10.8 22.8 24.8 0.2 0.4 0.5 54.4 Retailing Attractive 3,241 44.1 (53.3) 227.6 30.3 261 80 61 95 44 36 15.2 12.9 10.9 5.8 16.2 17.8 0.1 0.2 0.2 85 Speciality Chemicals Castrol India BUY 122 165 35 121 1.6 989 6.3 8.9 9.6 (25.2) 41.5 7.9 19.5 13.8 12.8 12.5 9.0 8.3 8.1 7.7 7.2 43.3 57.1 58.0 4.1 6.6 7.0 2.7 Pidilite Industries REDUCE 1,757 1,550 (12) 893 12.1 508 20.8 30 36 (10.0) 44.9 19.6 85 58 49 56 39 33 17.4 14.8 12.5 22.0 27.4 27.7 0.4 0.6 0.7 23.3 S H Kelkar and Company BUY 125 130 4 18 0.2 141 8.5 8.8 9.9 83.4 3.2 13.2 14.7 14.3 12.6 9.4 8.3 7.4 1.8 1.7 1.5 13.4 12.2 12.6 1.2 1.8 2.4 1.6 SRF ADD 5,505 5,000 (9) 326 4.4 58 177 216 271 28.4 22.1 25.2 31.1 25.5 20.3 18.1 15.2 12.4 4.9 4.2 3.5 17.9 17.8 18.8 0.3 0.3 0.4 17.5 Speciality Chemicals Attractive 1,357 18.5 (1.0) 34.7 18.6 48 36 30.1 29.8 22.7 19.3 9.6 8.2 7.0 19.9 23.1 23.5 0.7 1.1 1.2 45 Source: Company, Bloomberg, Kotak Institutional Equities estimates 8 KOTAK INSTITUTIONAL EQUITIES RESEARCH 8 Kotak Institutional Equities: Valuation summary of KIE Universe stocks 9 Fair O/S ADVT Price (Rs) Value Upside Mkt cap. shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) 3mo Company Rating 28-Dec-20 (Rs) (%) (Rs bn) (US$ bn) (mn) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E (US$ mn) Telecommunication Services Bharti Airtel BUY 522 710 36 2,846 38.7 5,456 (0.2) 10.2 21.4 NM NM NM NM 51.3 24.4 8.4 6.8 5.5 4.9 4.8 4.2 NM 9.5 18.4 1.2 1.2 1.2 120.1 Vodafone Idea RS 10 — — 299 4.1 28,735 (8.7) (6.8) (5.0) NM NM NM NM NM NM 10.9 8.7 7.1 (0.8) (0.6) (0.5) 167.0 47.0 26.4 — — — 40 Tata Communications BUY 1,065 1,075 1 304 4.1 285 46.6 52.5 62.5 22.9 12.7 19.2 22.9 20.3 17.0 9.2 8.1 7.1 NM 24.1 10.6 NM 264 86.5 0.4 0.6 0.7 1.7 Telecommunication Services Attractive 4,087 55.6 41.8 55.3 126.6 NM NM 165.9 9.0 7.4 6.2 11.5 14.9 18.0 NM NM 10.8 1.5 1.6 1.6 201 Transportation Adani Ports and SEZ BUY 484 495 2 982 13.4 2,032 22.2 29.4 32.5 (17.4) 32.2 10.4 21.7 16.4 14.9 15.7 11.8 10.2 3.4 2.9 2.5 16.5 18.8 17.7 0.8 0.9 0.9 44.7 Container Corp. SELL 393 360 (8) 239 3.3 609 9.4 12.5 16.4 (44.6) 33.2 30.6 42 31 24 20.5 16.2 13.0 2.3 2.3 2.2 5.6 7.3 9.3 1.3 1.7 2.3 13.2 Gateway Distriparks BUY 118 135 15 15 0.2 125 3.7 3.6 6.2 (12.3) (4.0) 73.7 31.7 33.0 19.0 7.8 7.9 6.6 1.0 1.0 1.0 3.3 3.0 5.1 2.5 2.5 2.5 0.2 GMR Infrastructure BUY 26 26 0 157 2.1 6,036 (3.7) (1.4) (0.5) (23.1) 63.1 65.4 NM NM NM 86.1 18.8 13.3 (3.7) (3.3) (4.2) 66.3 18.3 7.4 — — — 5.1 Gujarat Pipavav Port BUY 93 120 29 45 0.6 483 4.8 6.3 7.3 (20.5) 31.5 15.1 19.4 14.7 12.8 8.8 7.5 6.5 2.2 2.2 2.2 11.2 14.7 17.0 4.8 6.3 7.2 0.7 InterGlobe Aviation BUY 1,688 1,990 18 650 8.8 383 (173.8) 87.7 120.3 (2,580.1) 150.5 37.1 NM 19 14.0 NM 5.0 3.8 184.5 17.4 3.8 NM 165.5 76.6 — — — 40 Mahindra Logistics REDUCE 417 340 (18) 30 0.4 71 5.6 11.7 15.6 (37.5) 110.9 33.2 75 36 27 23.3 14.5 11.5 5.2 4.7 4.1 7.1 13.8 16.4 — — — 0.4 Transportation Attractive 2,117 28.8 (171.2) 380.9 27.7 NM 22 17.1 26.1 10.1 8.3 5.3 4.4 3.6 NM 20.2 21.0 0.6 0.8 0.9 104 KIE universe 143,722 1955.3 20.5 35.1 20.9 30 22.4 18.5 14.2 11.3 9.9 3.1 2.8 2.6 10.1 12.4 13.8 1.3 1.5 1.7 Notes: (a) We have used adjusted book values for banking companies. (b) 2021 means calendar year 2020, similarly for 2022 and 2023 for these particular companies. (c) Exchange rate (Rs/US$)= 73.50 Source: Company, Bloomberg, Kotak Institutional Equities estimates India Daily Summary India KOTAK INSTITUTIONALKOTAK - December 29, December29, 2020 EQUITIES RESEARCH EQUITIES KOTAK INSTITUTIONAL EQUITIES RESEARCH 9 Disclosures of the following trategic transaction n an merger or s As of September 30, 2020 any,are effect in longer no stock for this , if if , fair value , if any,if stock,, for because this there not a sufficient is fair value . Percentage of companies covered by Kotak Institutional Equities, the specifiedwithin category. Percentage of companies each within category for which Kotak Institutional Equities and or its affiliates has provided investment banking services the previouswithin months.12 * The above categories are defined as follows: Buy = We expect this stock to deliver more returns than 15% over the next months;12 Add = We expect this stock to deliverreturns 5-15% over the next months;12 Reduce = We expect this stock to deliver returns over -5-+5% the next months;12 Sell = We expect this stock to deliver less returns overthan -5% the next months.12 Our target prices are also on a horizon 12-month basis. These ratings are used illustratively to comply with applicable regulations. As of 30/09/2020 Kotak Institutional Equities Investment Research had investment ratings on 204 equity securities. luded r display not applicable.or is months. . The. investment previous rating and SELL 3.4% 21.1% fair value term in stock volatility prices related the to movements in market.Hence, a may Rating particular not , if any,if , have been temporarily. suspended Such suspension compliance is in with applicable regulation(s) - 1.0% 14.2% fair value +5% returns+5% over the next months. 12 REDUCE - month horizonmonth basis. 5 - - 15% returns15% over the next 12 5% returns5% over the next months. 12 The is information not available fo - - ake account into short ADD 25.5% 2.5% Kotak Securities coverage has suspended company. of this are also on a on 12 are also Kotak Securities Research the has suspended investment rating and The information is not meaningful and thereforeis exc Kotak not cover does Securities company. this The investment rating and The coverage represents overall view each fundamental the analyst’s on outlook Sector.The coverage consist of one view will Attractive,Neutral, Cautious. BUY 2.0% 39.2% We expect stock to deliver this We expect stock to deliver this 5 We expect this stockWe expect to deliver this < We expect stock to deliver this more than returns 15% over the months. 12 next Fair Value estimates 0% 10% 50% 40% 30% 20% 70% 60% Source: Kotak Institutional Equities Kotak Institutional Equities Research coverage universe coverage Research Equities Institutional Kotak Distribution of ratings/investment banking relationships NA Not NA = or NotAvailable Applicable. = NM Meaningful. Not involving this companyinvolving and in certain other circumstances. CoverageCS = Suspended. Not NC = Covered. Suspended. Rating RS = fundamental for determining an basis investment rating or not beand should relied upon. Otherdefinitions Coverage view. designations: Otherratings/identifiers = Rated.Not NR and/or Kotak circumstances in policies Securities when Kotak Securities affiliates or an its advisory acting in capacity is i SELL. Our SystemOur Ratings not t does accordance bestrictly in with the System Rating at times. all Ratings and other definitions/identifiers other and Ratings Definitions ratings of BUY. ADD. REDUCE. Disclosures Corporate Office Overseas Affiliates Kotak Securities Ltd. Kotak Mahindra (UK) Ltd Kotak Mahindra Inc 27 BKC, Plot No. C-27, “G Block” 8th Floor, Portsoken House 369 Lexington Avenue Bandra Kurla Complex, Bandra (E) 155-157 Minories 28th Floor, New York Mumbai 400 051, India London EC3N 1LS NY 10017, USA Tel: +91-22-43360000 Tel: +44-20-7977-6900 Tel:+1 212 600 8856 Copyright 2020 Kotak Institutional Equities (Kotak Securities Limited). All rights reserved. 1. Note that the research analysts contributing to this report may not be registered/qualified as research analysts with FINRA; and 2. 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