INDIA DAILY

March 18, 2021 India 17-Mar 1-day 1-mo 3-mo Sensex 49,802 (1.1) (3.7) 6.2 Nifty 14,721 (1.3) (3.2) 7.1 Contents Global/Regional indices Dow Jones 32,826 (0.4) 3.8 8.3 Special Reports Nasdaq Composite 13,472 0.1 (3.5) 5.5 Theme Report FTSE 6,786 (0.3) 1.1 3.6 Nikkei 29,914 (0.0) (1.2) 11.6 Reliance Industries: E2G: JioMart survey 2.0 Hang Seng 29,034 0.0 (6.6) 8.8 Daily Alerts KOSPI 3,048 (0.6) (2.8) 10.0 Value traded – India Company alerts Cash (NSE+BSE) 627 802 424 25,89 Derivatives (NSE) 34,492 36,608 L&T Technology Services: LTTS - Deputy CEO's perspectives 2 Deri. open interest 6,459 6,264 5,615 Sector alerts

Automobiles & Components: Electric scooter segment at an inflection point Forex/money market

Banks: The retail show goes on Change, basis points

17-Mar 1-day 1-mo 3-mo Telecommunication Services: Telemeter 3.0 - Bharti shines, Jio loses on VLR front; VIL gains majorly in UP (W) Rs/US$ 72.5 (8) (22) (104) 10yr govt bond, % 6.8 (1) 29 63

Net investment (US$ mn)

15-Mar MTD CYTD (8,390 FIIs (132) 23,258 ) MFs (21) 4,137 (7,073)

Top movers

Change, %

Best performers 17-Mar 1-day 1-mo 3-mo

TTMT/A in Equity 130 (3.7) (1.3) 70.3

TTMT in Equity 306 (4.4) (7.4) 68.3

VEDL in Equity 224 (1.1) 16.2 53.0

GRASIM in Equity 1,367 (1.3) 10.4 49.8

ADSEZ in Equity 688 (4.1) 5.0 47.1

Worst performers

BIOS in Equity 388 (0.9) (7.3) (15.8)

DRRD in Equity 4,359 (2.0) (5.2) (14.1)

PLNG in Equity 229 (3.4) (4.8) (11.8)

DIVI in Equity 3,378 0.0 (6.6) (11.7)

IPRU in Equity 427 (3.9) (12.6) (11.5)

[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 Reliance Industries (RIL) ADD Oil, Gas & Consumable Fuels March 18, 2021 THEME Sector view: Attractive E2G: JioMart survey 2.0. Our key takeaways from primary survey of 100 retailers CMP (`): 2,055 using JioMart in Bengaluru region include—(1) JioMart has enhanced economics for Fair Value (`): 2,050 retailers through a combination of lower prices, higher discounts and reasonable credit terms, (2) all retailers are packaging and delivering B2C orders for JioMart in BSE-30: 49,802 lieu of margins and delivery fees, and (3) JioMart’s B2B service levels seemed to be better in Bengaluru vis-à-vis Mumbai, wherein we conducted a survey in December.

Reliance Industries Stock data Forecasts/valuations 2021E 2022E 2023E CMP(Rs)/FV(Rs)/Rating 2,055/2,050/ADD EPS (Rs) 73.5 84.5 101.5 52-week range (Rs) (high-low) 2,369-867 EPS growth (%) 10.1 15.1 20.1 Mcap (bn) (Rs/US$) 12,183/168 P/E (X) 28.0 24.3 20.3 ADTV-3M (mn) (Rs/US$) 25,698/354 P/B (X) 2.4 2.2 2.0 Shareholding pattern (%) EV/EBITDA (X) 16.6 11.1 9.0 Promoters 49.1 RoE (%) 9.2 9.7 10.3 FPIs/MFs/BFIs 27.2/4.7/5.7 Div. yield (%) 0.3 0.4 0.4 Price performance (%) 1M 3M 12M Sales (Rs bn) 4,956 6,208 6,785 Absolute (1.3) 3.5 105.8 EBITDA (Rs bn) 787 1,112 1,328 Rel. to BSE-30 2.4 (2.5) 26.4 Net profits (Rs bn) 443 537 644

Survey of grocery retailers: JioMart stacking up as preferred distributor

We surveyed 100 grocery retailers in Bengaluru who have been in a partnership with JioMart for an average of the past six months. The purpose of this survey was to understand: (1) JioMart’s value proposition to retailers versus other distributors, (2) willingness of retailers to act as sellers on JioMart’s B2C online platform and (3) perception of JioMart’s overall offering. Our survey may have an exclusion bias as we excluded retailers who are not partners with JioMart. We present key findings of the survey in brief below and in detail later in the note.

 JioMart has chalked up noteworthy economics for all retailers. All retailers suggested that product prices offered by JioMart are typically lower than other distributors. More than half of the surveyed retailers recognized that availability of products, comprehensive range and discounts offered by JioMart are also better than traditional distribution channels. Tarun Lakhotia  All kiranas/retailers pack and deliver orders coming via JioMart. Interestingly, all respondents mentioned that B2C orders from JioMart’s portal are being supplied and Garima Mishra delivered to households directly by the retailers; this is contrary to Mumbai, wherein most retailers were providing only last-mile delivery for products supplied by JioMart. Retailers Iftekhar Bidkar earn their product margins besides an average delivery charge of Rs15-20 per order.

 JioMart’s servicing levels in Bengaluru seemed to be better than Mumbai. JioMart Shubhangi Nigam seems to be offering better servicing levels in Bengaluru compared to Mumbai, wherein we conducted a survey in December 2020. Nearly 63% of retailers surveyed in Bengaluru indicated that JioMart representatives visit the stores at least on a monthly basis.

 Retailers viewing the JioMart partnership as positive for their business. Approval ratings for JioMart were very high with most of the retailers indicating that they have benefited from their partnership with JioMart so far.

 JioMart’s private labels stocked by all retailers, unlike Amazon. JioMart’s products under the private labels of Reliance Retail are stocked by all the retail partners perhaps indicating push from JioMart as well as better general acceptance of these brands. On the contrary, only 22% of Amazon retailers seem to be stocking its private labels. [email protected] Contact: +91 22 6218 6427

For Private Circulation Only. In the US, this document may only be distributed to QIBs (qualified institutional buyers) as defined under rule 144A of the Securities Act of 1933. This document is not for public distribution and has been furnished to you solely for your information and may not be reproduced or redistributed to any other person. The manner of circulation and distribution of this document may be restricted by law or regulation in certain countries, including the United States. Persons into whose possession this document may come are required to inform themselves of, and to observe, such restrictions.

Oil, Gas & Consumable Fuels Reliance Industries

About E2G and KIE’s Primary Research Practice

 Ear to the Ground (E2G), our market research series, is supported by KIE’s Primary Research Practice, a proprietary initiative that focuses on qualitative and quantitative primary market research. The practice is backed by extensive analyst experience in primary market research relating to B2B, B2C retail and agriculture.

 The objective of this practice is to help analysts understand on-ground realities in the context of their research and offer investors a context for our research and insights.

 KIE’s primary research desk also conducts and analyses bespoke market research for clients.

2 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

SURVEY OBJECTIVE E2G – Ear to the Ground is KIE’s market research series, which is our proprietary model focusing on primary research survey. We conducted a primary research survey among 100 retailers based out of Bengaluru. These retailers are primarily small mom-and-pop grocery shops. The key objective of surveying these retailers was to understand: (1) JioMart’s value proposition to retailers versus other distributors, (2) willingness of retailers to act as sellers on JioMart’s B2C online platform, and (3) JioMart’s perception in the retailer community.

We conducted a survey of 100 retail shops in Bengaluru with an aim to learn more about JioMart’s B2B and B2C grocery operations. All retailers that we interviewed have had a partnership with JioMart for the past few months. We detail below the key purpose of the survey:

 Key reasons for kirana shops to partner with JioMart.

 What is JioMart’s overall share in kiranas’ overall product purchase?

 What proportion of retailers are using JioMart for services other than product procurement (inventory management, B2C sales on JioMart, receiving payments)?

 What are the most important attributes that determine the order of preference of retailers for selecting their distributor partners?

 How does JioMart’s distributor service stack up against others?

 Overall satisfaction levels of retailers with JioMart. How many retailers are happy with JioMart’s service? What can JioMart do better in order to serve its customers better?

 How do retailers perceive JioMart? What, in their opinion, is the reason for JioMart to seek their partnership?

METHODOLOGY

We conducted field surveys across 100 local grocery shops (selling primarily staples, packaged food, snacks and beverages, HPC, etc.). These retailers have standalone stores in Bengaluru that cater largely to walk-in customers. Participants were shop owners who are the primary decision makers of procurement and merchandising. The survey was developed by KIE’s research team covering the retail sector.

(For more details on our methodology, please refer to Appendix 2).

KOTAK INSTITUTIONAL EQUITIES RESEARCH 3

Oil, Gas & Consumable Fuels Reliance Industries

SURVEY OF GROCERY RETAIL SHOPS IN BENGALURU: KEY FINDINGS Key findings of the survey are: (1) JioMart is offering cheaper product price to retailers compared to other distributors, (2) food and grocery is the most important category accounting for bulk of sales at these retailers, (3) JioMart has improved its service levels but there is headroom available to get more kiranas onboarded on the JioMart B2C platform, and (4) for the shops surveyed, JioMart seems to have a much larger share of the distribution pie compared to competitors such as Amazon.

Retailers typically engage with a large number of distributors to source products

 Foods (staples, snacks and beverages, packaged goods, dairy) constitute 66% of the sales of the retailers we surveyed on an average. Remainder 34% consists of personal care, household hygiene and baby care products. Staples, which is a mix of branded and unbranded items, constitutes a solid 41% of average sales of these retailers.

Exhibit 1: Food sales form a heavy 66% of retailers’ average daily sales Breakdown of retailers' sales mix (% of value)

Dairy Household hygiene 4% 12%

Baby care Staples 9% 41%

Personal care 13%

Packaged foods Snacks and 10% beverages 11% Notes: (a) Staples includes dal, pulses, oil, flour, spices, sugar, salt, etc. (b) Snacks and Beverages includes biscuits, chips, tea, coffee, soft drinks, etc. (c) Packaged foods includes noodles, pasta, ketchup, chocolates, honey, pickles, etc. (d) Personal care includes soaps, hair color, oral care, powders, sanitary pads, etc. (e) Baby care includes diapers, baby foods, baby bath, skin care, etc. (f) Household hygiene includes detergents, cleaners, insect repellents, etc. (g) Dairy includes milk, bread, butter, cheese/yogurt, eggs, etc.

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 Our survey also revealed that these retailers typically deal with multiple distributors. A

majority of the retailers (77%) engage with more than 15 distributors, and all deal with more than 10 distributors. This is in contrast to Mumbai-MMR region survey (Dec ’20), where only 25% dealt with more than 15 distributors.

4 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 2: 77% of the retailers deal with more than 15 distributors Breakdown of distributor count for different retailers (% of respondents)

10-15 distributors 23%

>15 distributors 77%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

JioMart has cornered a decent 20% market-share among distributors

 The retailers that we surveyed have been engaged with JioMart for an average of six months in Bangalore. Most of them seem to have partnered with JioMart after the lockdown restrictions eased in July/August 2020.

Exhibit 3: The retailers we surveyed have been partners with JioMart for an average of six months Location-wise average number of months of partnership with JioMart (#, months)

(#) 10.0 9.4 9.3 8.9 9.0 8.0

7.0 6.2 6.0 5.0 4.0 3.0 2.0 1.0 0.0 Bangalore Mumbai Thane Navi Mumbai

Notes: (a) Mumbai-MMR region figures are representative of data till Dec’20 whereas for Bengaluru till Feb’21

Source: E2G Survey-JioMart (Feb’21, Dec’20), Kotak Institutional Equities

 Per our survey, 100% of respondents mentioned that price levels and availability were the most important parameters while deciding on engaging with a distributor. 79% and 75% mentioned that comprehensive range and discount offered were critical respectively, while 73% mentioned that timely delivery was also important. Other important parameters are quality of goods, door step deliveries, general service levels and credit facility.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 5

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 4: Retailers’ have placed price levels and availability as top priorities for distributor choice Key parameters involved in selection of distributors by retailers (% of respondents)

Price level 100

Availability of the goods 100

Comprehensive range of products & SKUs 79

Discount offered 75

Timely delivery 73

Quality of the goods 67

Door step delivery 59

Proximity of the supplier 58

Good treatment/ servicing 57

Credit Facility 55

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 JioMart scores high on most of these parameters, particularly price. It also enjoys high approval ratings among retailers that we surveyed. When specifically quizzed on various benefits offered by JioMart, respondents mentioned: (1) margin offered by JioMart is 10- 20%, higher than 8-15% offered by the traditional distributors and 8-12% offered by Amazon, (2) JioMart offers an additional 5-10% discount on a case by case basis (2-7% for other distributors, 4-8% for Amazon), (3) it also offers 10-15 days of credit period compared to 10-30 days for other distributors, and (4) it supports online placement of orders unlike the traditional distributors.

 All retailers acknowledged that JioMart offers a single-point destination for all-product sourcing and 72% suggested that JioMart offers timely doorstep delivery. Nearly half of the respondents rated them well on quality of products, discounts offered and being a supplier of choice.

Exhibit 5: JioMart’s pricing in the B2B business is the top draw for retailers Key parameters involved in selection of JioMart as distributor by retailers (% of respondents)

Price of products are cheaper than distributors price 100

All the products are available at single source (rather than 100 buying different products from different distributors)

Doorstep delivery 100

Timely delivery of products 72

Quality of products 56

Jiomart has own private labels (Best Farms, Good Life etc) 55

Discounts/schemes are better than authorized 54 distributors/wholesalers

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

6 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 6: JioMart scores meaningfully over other distributors on profit margins and discounts offered Key operating metrics of distributors as revealed by retailers

JioMart Distributor Amazon Profit Margin 10-20% (depending on 8-15% (depending on 8-12% (depending on product) product) product) Discounts 5-10% depending on 2-7% (depending on 4-8% depending on product & company product & company) product & company Credit period 10-15 days 10-30 days 8-12 days

Minimum order quantity/value (Rs) ~3,500 2,000-10,000 (retailer 3,000-5,000 dependent) Online Order Yes No Yes Delivery Support Yes Yes Yes Reconcilliation Yes Yes Yes Total respondents 100 100 32

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 100% of the retailers claim that JioMart’s prices are lower than of the other authorized distributors or wholesalers. All 32 retailers dealing with Amazon also mentioned of lower prices vis-à-vis other traditional distributor channels.

 JioMart seems to have cornered a sizeable 20% share in the overall distribution business offered by the retailers we surveyed. This is relevant in the context that most retailers deal with multiple distributors.

Exhibit 7: JioMart has cornered a significant 20% share of the retailers’ distribution needs Share of different distributors among the retailers surveyed (%)

Direct (from suppliers/company/i mporters), 7% Amazon, 4%

Authorized distributors, 43% Wholesalers, 26%

JioMart, 20%

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 Average turnaround time to source and deliver products to kiranas is lowest for JioMart. However, this is not meaningfully different from other distribution channels.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 7

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 8: JioMart has lowest turnaround time in terms of delivering products to retailers Average number of days needed to source products (#)

Average days needed for procurement (#) 1.80 1.61 1.61 1.60 1.44 1.40 1.33 1.20 1.00 0.80

0.60

0.40 0.20 - Authorized distributor Wholesalers JioMart Amazon

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 Unsurprisingly, all respondents buy a variety of food, grocery and FMCG products from JioMart. When we questioned the retailers on what JioMart had promised them initially (at the start of their partnership), they mentioned that JioMart promised: (1) good profit margin, credit facility, (2) discounts and deals, and (3) growth in customer base (online/offline orders).

Exhibit 9: Qualitative responses on benefits promised by JioMart Breakdown of retailers’ responses on JioMart’s promised benefit (% of respondents)

Immediate/doorstep delivery within 24 Product range hours 9% 8%

Online orders 11%

Credit facility, good profit margin and Grow customer offers base 41% 13%

Discounts and deals 18%

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 Private label products are being pushed by distributors. 100% of the surveyed retailers buy JioMart’s private label products across different product categories. This compares with only 37% of Mumbai retailers stocking JioMart’s private label products surveyed in December 2020. Nearly 13% of retailers stock private label products of other distributors such as Amazon and Metro. A better way to look at this is to look at only those 32 retailers with a partnership with Amazon – only 22% of these retailers stock Amazon’s private label products implying that pushing private label is an important part of JioMart’s distribution strategy.

8 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 10: 100% of retailers stock JioMart’s labels whereas only 22% of the retailers dealing with Amazon stock its private labels Breakdown of retailers’ responses on stocking with private labels of Amazon and JioMart (% of respondents)

Retailers stocking Amazon's private labels (%) Retailers stocking JioMart's private labels (%)

No Yes 0% 22%

No 78%

Yes 100%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 Overall, JioMart enjoys high approval ratings with retailers. This is despite the fact that JioMart representatives visit their kirana partners fewer number of times compared to traditional distributors.

Exhibit 11: 100% of retailers are satisfied with JioMart Breakdown of retailers’ responses on overall experience with JioMart (% of respondents)

Average, 0%

Highly satisfied, Satisfied, 50% 50%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 9

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 12: 86% of retailers say that business has benefitted post JioMart tie-up Breakdown of retailers’ responses on benefit from JioMart tie-up (% of respondents)

Don’t know (as started recently), 14%

No, 0%

Yes, 86%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 JioMart’s representatives’ visits to the retail shops seems to have shown some improvement in the last two months but are still lower and infrequent when compared to visits made by regular distributors.

Exhibit 13: JioMart sales representatives visit retailers once a month Chart on retailers’ responses on JioMart salesperson’s visit (% of respondents)

Jiomart sales rep visits (% of eligible respondents) Distributors sales rep visits (% of eligible respondents) 70% 66% 63% 60%

50%

40% 37%

30% 22% 20% 12% 10%

0% Weekly Fortnightly Monthly Does not visit

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

JioMart: engagement on B2C still to pick up

 JioMart engages with small retailers in two ways: (1) acting as a distributor by supplying products to retailers, and (2) utilizing the small store network to fulfill its orders for JioMart’s B2C portal. Our survey in Bengaluru revealed that the B2B and B2C services offered by JioMart are bundled: in order to receive B2C orders from JioMart’s portals, a retailer also needs to have a B2B partnership with JioMart.

10 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 14: Tie-up with JioMart for distribution is necessary in order to receive orders via JioMart Breakdown of retailers’ responses (% of respondents)

Retailer count % of total Response on tie-up as distributor to receive orders via Jiomart (#) retailers Mandatory 100 100 Not mandatory - - Don’t Know - -

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 On an average, nearly three orders of the 22 daily orders are received via JioMart by the retailers/kiranas. This implies that JioMart contributes ~12% of overall orders received by kiranas.

Exhibit 15: JioMart contributes 12% in share of total orders received by the retailer Breakdown of average daily orders received by retailer (#) Average daily orders (#) Average daily orders received (total) 22.1 Average daily orders received (other than Jiomart) 19.4 Average daily orders received from Jiomart 2.7 Share of orders received from Jiomart (%) 12.2

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 100% of respondents mentioned that orders received by JioMart were both packed and sent by kiranas for last-mile doorstep delivery to customers. This is in contrast to findings in Dec’20 Mumbai survey which indicated that 82% of the orders were packed by JioMart and kiranas were used only for last-mile delivery.

 Per the survey, 100% of the retailers are doing both order packing and delivery and JioMart is paying them an average amount of Rs17 per order as delivery fees to enable last-mile delivery fulfillment on JioMart orders.

Exhibit 16: An average of Rs17 per order is earned by kirana for delivery of JioMart orders Breakdown of responses on fees charged by kirana on JioMart order delivery (% of respondents)

Fees earned on delivery of JioMart orders (Rs/order) %age of respondents 10-15 63 16-20 19 21-25 - 26-30 17 30 onwards 1 Average fees earned on delivery for Jiomart order (Rs/order) 17

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 JioMart’s strategy around its PoS machines remains unclear. Only 14% of the retailers we surveyed use or had used the PoS machine. As per the survey findings, ~7% of the retailers have returned the Jio PoS devices back to the company after using it for some time and ~86% of the respondents have not used it even once. This indicates that JioMart is either taking back its devices or has paused the PoS initiative.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 11

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 17: 86% of retailers have not used Jio’s PoS devices Breakdown of retailers’ responses on usage of PoS machines (% of respondents)

Yes, 7% Used earlier, but stopped and gave Jio PoS back to company, 7%

No, 86%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 Retailers had paid Rs3,000 as a deposit to JioMart for the PoS devices. 86% of the 7 respondents who use Jio PoS primarily use it for billing customers and 14% use it for receiving payments. 43% of respondents use the Jio PoS for maintaining inventory and barcoding while none use the device for ordering products.

Exhibit 18: Jio PoS machines usage mainly for inventory bar coding and billing Chart on retailers’ responses on usefulness of Jio PoS machines (% of respondents)

Yes No

Use Jio POS for receiving payments (card swipe, QR code scan, 14 86 Tap & Pay)

Use Jio POS for ordering products for your outlet - 100

Use Jio POS for maintaining inventory/ bar coding 43 57

Use Jio POS for billing to customers 86 14

- 20 40 60 80 100 120 Note: (1) Only seven of the total retailers used PoS devices

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 Our Bengaluru and Mumbai surveys suggest that there is plenty of confusion around the usage of PoS machines. All eligible respondents were unaware of Jio withdrawing these devices.

 Retailers are less skeptical on JioMart’s B2C business intentions and its attempt to bring retailers under its coverage. Some retailers believe that JioMart will help kirana stores scale their business and some speculate JioMart wants to fend off competition as it captures kiranas’ customer base and grows in scale.

12 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 19: Qualitative responses on intentions of JioMart entering the food and grocery business Key reasons regarding intention of JioMart behind partnership with small retailers (% of respondents)

Increasing daily revenue of their business 15

Helping small scale businesses to reach next level 12

Growing own business and fight competition 11

Build brand awareness/advertisement 10

Grow business and increase customer base 10

Kirana stores gives them good profit and sales 10

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 13

Oil, Gas & Consumable Fuels Reliance Industries

APPENDIX I: DETAILS OF OUR SAMPLE SET

We discuss below a brief profile of the retailers we surveyed.

 100 retailers from Bengaluru were surveyed, all of whom use JioMart as one of the distributor. 32 of them use Amazon as a distributor as well. The average days of operations of the shop across cities was 30 days with average daily sales of Rs12,140.

Exhibit 20: Details of surveyed retailers with tie-ups with JioMart and Amazon

Location Bengaluru Jiomart retailers 100 Amazon retailers 32 Total retailers surveyed 100 Average daily kirana sales (Rs/day) 12,140 Average days of operation (in a month) 30

Notes: (1) Amazon retailers form an overlapping set with JioMart retailers. For instance, any Amazon retailer surveyed is a JioMart retailer as well.

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 13% of the retailers surveyed have reported consistent growth in sales during and post lockdown and only 9% say that sales increased in the initial three months of lockdown. For 78% of retailers, sales have either remained flattish or declined compared to pre- lockdown levels.

Exhibit 21: 30% of retailers reported a decline in average daily sales during/post-Covid lockdowns Breakdown of average daily sales growth of retailers (% of respondents)

Witnessed growth 13%

Increased in initial 3 months 9%

Remained same 48%

Declined 30%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 Only 26% of the surveyed retailers said that customers are down-trading post-Covid lockdown. This is in stark contrast versus 77% retailers saying that customers were down- trading in Mumbai post-lockdown in December 2020. This may imply that customer spends are gradually normalizing post-Covid.

14 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

Exhibit 22: 26% of retailers said that the customers were down trading post-Covid lockdown Responses on customers’ down-trading post-lockdown (% of respondents)

Yes 26%

No 74%

Source: E2G Survey-JioMart (Feb'21), Kotak Institutional Equities

 Home-delivery customer orders form 21% of average daily sales for these retailers. Rest is still in-store purchases. The retailers pointed out that 76% of average daily sales happen through cash.

Exhibit 23: 79% of customers prefer to shop in-store Breakdown by customers order type (% of average daily sales)

Home delivery 21%

Walk-in customers 79%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 15

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 24: We note that 76% of customers transact in cash Breakdown by customers’ payment method (% of average daily sales)

Credit 24%

Cash 76%

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

 Retailers also mentioned that unlike JioMart, Amazon is not forcing them to become its pick-up partners. All retailers working with Amazon agreed that the company is not forcing them to stock its own private labels. Only 22% of them stock private labels of Amazon vis-à-vis 100% for JioMart. This could be either due to higher brand acceptance and trust for Reliance among retailers in general or higher push from JioMart.

16 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

APPENDIX II: DETAILS ON SURVEY OBJECTIVES, METHODOLOGY AND TARGET GROUP

Key objectives

 Key reasons for kirana shops to partner with JioMart.

 What is JioMart’s overall share in kiranas’ overall product purchase?

 What proportions of retailers are using JioMart for services other than product procurement (inventory management, B2C sales on JioMart, receiving payments)?

 What are the most important attributes that determine the order of preference of retailers for selecting their distributor partners?

 How does JioMart’s distributor service stack up against others?

 Overall satisfaction levels of retailers with JioMart. How many retailers are happy with JioMart’s service? What can JioMart do better in order to serve its customers better?

 How do retailers perceive JioMart? What, in their opinion, is the reason for JioMart to seek their partnership?

Methodology

 Quantitative methodology was used for the survey.

 Structured questionnaire was developed for the study & pilot phase of few interviews were covered in Bengaluru.

 Post pilot phase, the questionnaire was finalized, which was used for primary interviews among target groups.

 Primary face-to-face interviews were conducted among target groups by experienced field teams across different locations in Bengaluru.

Research approach and target groups

 We selected Bengaluru for the survey.

 Sample size of 100 was chosen which also included 32 retailers who also procured from Amazon.

 Standalone grocery shops (selling primarily staples, packaged food, snacks and beverages, HPC etc.) were covered for the survey

 Shop owners who are the primary decision makers of procurement and merchandising were interviewed for the survey.

 All retailers who were surveyed were shops that were JioMart partners. Additionally, we also tried to identify retail shops who were also buying from Amazon from the same sample set.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 17

Oil, Gas & Consumable Fuels Reliance Industries

Survey execution

 Before the rollout of primary survey, telephonic briefings were given to field teams on objectives, questionnaire, conducting of interviews and sampling.

 Primary face-to-face interviews were outsourced to a field agency and conducted by experienced field executives.

 Purposive sampling methodology was used to recruit and interview target groups that fit the recruitment criteria.

 Respondents were screened basis recruitment criteria and only interviewed when they met all the criteria.

 Post completion of face-to-face interviews, quality checks were done and any outliers in data were removed and additional interviews were conducted to minimize the shortfall.

Analysis and report

 Post completion of face-to-face interviews, data entry of completed interviews done in excel format.

 Analysis of data and report preparation based on findings.

Sample size covered for the study

 All retail shops covered for the survey were JioMart partners.

 Additionally, we also identified and interviewed kirana shops who were also buying from Amazon from the same sample set of kirana shops

Exhibit 25: Sample size covered for the study Break-up of sample size covered in Bengaluru Location Bengaluru Jiomart retailers 100 Amazon retailers 32 Total retailers surveyed 100 Average daily kirana sales (Rs/day) 12,140 Average days of operation (in a month) 30

Notes: (a) In the survey, Amazon retailers form an overlapping set with JioMart retailers. For instance, any Amazon retailer surveyed is also JioMart retailer as well.

Source: E2G Survey-JioMart (Feb’21), Kotak Institutional Equities

18 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Reliance Industries Oil, Gas & Consumable Fuels

APPENDIX III: A BRIEF SNAPSHOT OF JIOMART’S KIRANA DIGITIZATION PROGRAM JioMart envisaged its kirana digitization strategy with an aim to: (1) use the vast kirana network to fulfill and deliver to customers for orders generated on its JioMart online platform, and (2) become a distributor partner to these shops who could benefit from Reliance Retail’s size and price bargaining power. JioMart launched its B2C operations in 1QCY20 in 200 cities, though its business model is still in a state of flux.

JioMart’s kirana digitization strategy to supplement digital commerce

 We believe JioMart seeks to not only become a meaningful grocery retailer by providing customers the convenience of shopping online, it also seeks a slice of the large B2B market, which hitherto has been driven by traditional distributors. While the proportion of modern trade has been on the rise, we believe RIL would want to integrate its Reliance Market offering with its network of kirana stores, thereby disintermediating the existing value chain (company – distributor – wholesaler – stockist – retailer). We believe this business can be an important feeder to the digital commerce business and can significantly aid supply aggregation in a fragmented market.

 JioMart’s intent to launch its distribution service on a large scale can help it amass sizeable revenues. It will need to establish a virtuous cycle by offering consistently low- priced products to shops, the widest variety while at the same time negotiating for best prices with FMCG companies and other large producers. JioMart has several private labels in its grocery retail business. It can push these private labels on a large scale through this channel and ultimately to customers ordering products online.

JioMart: partnership with kiranas can create large cross-sell opportunities in the future

 After piloting its operations in parts of Mumbai, Reliance Retail commenced operations of JioMart, its online groceries delivery portal. Besides B2C operations, JioMart has also sought to build a network of small stores by offering them a PoS device for refundable deposit of Rs3,000, with the idea of: (1) connecting these stores with its own B2B supply chain, (2) getting these chains to use JioPay on the PoS machine, and (3) garnering precious data on revenue potential of the shop, SKUs sold, etc. It can offer stores benefits such as cheaper procurement price of products (vs traditional distributors), lower turnaround times leading to higher fill rates (aided by enhanced data availability via PoS), and additional customers via WhatsApp pay.

 The social commerce interface combining WhatsApp pay and JioPay can create a vast fintech space – potentially representing ways for: (1) providing working capital loans to shop owners with little or no credit history, and (2) potentially earning margins on transactions originating on JioPay. Note JioPay could be a currency of transaction not only in the Reliance-PoS enabled kirana shops, but all across the RIL ecosystem and can be used by vendors and customers alike. Most importantly, these kiranas can act as supply aggregators and delivery agents for the nascent JioMart online business.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 19

Oil, Gas & Consumable Fuels Reliance Industries

Exhibit 26: JioMart is steadily increasing product assortment available online Key usage and other metrics of leading e-commerce players in India

JioMart Dmart Tata Cliq Amazon Flipkart Monthly visits in mn (desktop+mobile web) 6.8 0.6 6.9 252.5 145.5 App downloads (mn) 10.0 5.0 10.0 100.0 100.0 Country rank 241 3,113 442 6 11 Average visit duration (h:mm:ss) 0:02:07 0:05:14 0:02:48 0:05:12 0:04:51 Pages per visit (#) 8.1 6.5 2.9 7.0 6.3 Bounce rate (%) 44.2 37.6 65.6 47.9 49.6 Traffic sources (%) -Direct 61.7 43.3 28.3 51.9 59.7 -Referrals 3.2 1.1 1.4 2.0 1.1 -Search 27.2 55.6 60.2 39.0 36.2 -Others 8.0 0.0 10.1 7.1 3.1 Cities with grocery delivery (#) 200 5 na 300 50 Product categories available online 1 Fruits & vegetables Fruits & vegetables na na na 2 Staples Staples na Staples Staples 3 Dairy & bakery Dairy & beverages na Dairy & beverages Dairy & beverages 4 Packaged foods Packaged foods na Packaged & gourmet Packaged & gourmet foods foods 5 Hygiene & personal Hygiene & personal Beauty & personal Hygiene & personal Hygiene & personal care care care care; beauty care; beauty 6 Apparel; clothing Home, kitchen and Apparel; all Apparel; all Apparel; all accessories like personal care accessories accessories accessories handbag, belt (own appliances brands only) 7 na Basic footwear All footwear All footwear All footwear 8 na na Home furnishings Home furnishing; Home furnishing; furniture furniture 9 na School supplies na School supplies School supplies 10 na na TV & all appliances TV & all appliances TV & all appliances 11 na na Electronics (mobiles, Electronics (mobiles, Electronics (mobiles, tablets etc) tablets) tablets) Notes: (a) Other traffic sources include social, mail and display. (b) Amazon and Flipkart data for monthly visits, app downloads and related data pertains to their complete marketplace.

Source: Similarweb (data representative of Feb'21), Google Playstore, Media articles, Kotak Institutional Equities

How large has JioMart become?

In August 2020, RIL had mentioned that JioMart was averaging daily order run-rate of 0.25 mn. This further scaled up to 0.5 mn orders a day in December 2020 per comments made by Kiran Thomas, President RIL at Facebook’s Fuel for India 2020 event.

20 KOTAK INSTITUTIONAL EQUITIES RESEARCH ADD L&T Technology Services (LTTS) https://ultraviewer.et/en/own IT Services MARCH 18, 2021 load.html UPDATE Sector view: Attractive

LTTS – Deputy CEO’s perspectives. We interacted with LTTS Deputy CEO, Amit CMP (`): 2,589 Chadha, to get perspectives on growth outlook and industry trends. LTTS is confident Fair Value (`): 2,700 of strong growth and is well-positioned to benefit from spending acceleration in digital BSE-30: 49,802 engineering. Account mining is a big priority. The focus is to sustain the growth trajectory in the longer term by staying ahead of technology trends and remaining relevant to clients. High growth characteristics of the stock keep us positive. Maintain ADD.

L&T Technology Services Stock data Forecasts/valuations 2021E 2022E 2023E CMP(Rs)/FV(Rs)/Rating 2,589/2,700/ADD EPS (Rs) 63.6 88.5 106.3 52-week range (Rs) (high-low) 2,858-995 EPS growth (%) (18.2) 39.2 20.1 Mcap (bn) (Rs/US$) 273/3.8 P/E (X) 40.7 29.3 24.4 ADTV-3M (mn) (Rs/US$) 960/13 P/B (X) 8.4 7.0 5.8 Shareholding pattern (%) EV/EBITDA (X) 25.5 19.1 15.9 Promoters 74.3 RoE (%) 22.3 26.2 26.2 FPIs/MFs/BFIs 8.9/5.8/0.2 Div. yield (%) 0.6 0.9 1.0 Price performance (%) 1M 3M 12M Sales (Rs bn) 55 65 77 Absolute (2.9) 31.9 109.5 EBITDA (Rs bn) 10 13 16 Rel. to BSE-30 0.8 24.2 28.6 Net profits (Rs bn) 7 9 11

Well-positioned to tap digital engineering opportunity Engineering spend on digital and new technologies is a large opportunity for LTTS. The company indicated that it sufficiently invested in hardware, software products and services to benefit from the opportunity. LTTS is continuing to invest in major opportunities which include—(1) electric vehicles, a huge opportunity in the next 2-3 years, (2) medical technology driven by remote healthcare and greater leverage of patient data, (3) digital manufacturing, which involves aggregating data across procurement, operations, field engineering, engineering design and manufacturing and using insights for automation, improving efficiency, improving productivity, etc. It also includes digitizing aspects beyond the shop floor. Client spending on digital manufacturing has increased. For example, uptake of technologies such as digital twins is better compared to lip service earlier. LTTS expects further acceleration in spending, (4) artificial intelligence, which is yet to be leveraged in a big way in engineering, (5) 5G – LTTS expects the 5G opportunity to play out within the next three years, and (6) sustainability.

Accounts can be scaled to U$50-75 mn by offering multiple services Large accounts are a must for scale. LTTS believes it can grow client accounts in certain verticals such as auto, medical devices and oil & gas segment. LTTS had already scaled a couple of accounts in hi-tech to US$50 mn; however, they ramped down due to client-specific issues. The account mining strategy is to offer services across multiple divisions, technologies, functions and product lines within the same client. Primary focus is on top-30 clients, which generate 55% of revenues. Focus on multiple services has reduced client-specific risks. For example, LTTS worked with three divisions in one of its top-2 accounts. LTTS lost business when the client shut down Kawaljeet Saluja one of its divisions but has retained work and is growing in the other two divisions. Sathishkumar S Maintain ADD rating; LTTS is a strong player in a high-growth space LTTS stands out for its multi-vertical expertise, full spectrum of offerings, a quality client base, and track record of engineering prowess. These positives are likely to power 24.2% three-year earnings CAGR by FY2024E, after a contraction in FY2021. We believe that the long runway for growth justifies premium valuations. We maintain ADD rating, valuing the stock at 25X [email protected] FY2023E earnings. 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. IT Services L&T Technology Services

Covid has led to acceleration of a few trends and reprioritization of investments

LTTS indicated that Covid has brought about a few changes in industry spending trends—

 Spending on the shop floor has opened up to make shop floors safe and to operate with absenteeism. Companies are spending more on remote management of factory operations. Companies are also investing in making a few other processes remote such as fault repair and aftersales services.

 Work from home trend will lead to higher spending on HVAC and lighting systems in residential real estate and spaces compared to commercial or industrial real estate.

 Autonomous, vehicle electrification and green energy have received a lot more focus.

 Companies are more focused on reliability of the supply chain and are rejigging the supply chain to become more localized.

 Companies have turned more cost conscious on legacy engineering due to push to reduce expenditures and conserve cash.

 Defense spending by countries can accelerate, partially offsetting slowdown in aerospace.

 Relevance of cyber security has increased, which can lead to higher spends. LTTS indicated that clients in all verticals barring aerospace and oil & gas (increase in oil prices can lead to turnaround in prospects) have not reduced budgets with the company, supporting outlook of strong growth in the next 2-3 years. LTTS continues to win large deals even in impacted segments such as aerospace and oil & gas. Companies continue to be focused on new product development, which is a positive. Cost pressure in legacy engineering can translate to higher outsourcing. Clients are clearly differentiating between digital engineering and legacy. They are willing to pay premium prices for digital engineering, but will optimize spend on legacy engineering.

Boosting presence in ISVs and cloud hyperscalers

LTTS acknowledged that it has a weak presence in ISVs. Software engineering for ISVs is a large and fast-growing space dominated by Tier-1 companies. LTTS is taking corrective measures and is growing business aided by lateral hires from marquee companies. The company indicated that one of the cloud hyperscalers is a top account. At the same time, LTTS is consciously avoiding low value work such as annotation even if revenue potential is high. The company is confident that business with ISVs and cloud hyperscalers will grow gradually over time.

Remaining relevant amid changing technology landscape key to maintaining growth trajectory

The LTTS Deputy CEO indicated that the number one challenge for the company is to maintain relevance in a world of rapid technology change. Capturing new disruptive technology trends before they become mainstream is the key to grow and maintain the growth trajectory. The company has demonstrated ability to adapt to a changing technology landscape. Mechanical engineering component of work was ~80% a decade ago but that has reduced to 25% due to higher focus on embedded and software, in line with change in technologies. LTTS has been early to identify and build capabilities in digital engineering; a fast-growing market within engineering spends. This has helped grow revenue contribution from digital engineering and new technologies to 49% of overall revenues.

4 KOTAK INSTITUTIONAL EQUITIES RESEARCH L&T Technology Services IT Services

People aspect is equally important. LTTS focuses on bringing the right team at the right time. L&T group parentage provides a resource pool of experienced talent in multiple domains. The company has also used external hires from Tier-1 IT firms to build strength in verticals. For example, LTTS hired senior leadership from Wipro to help build its medical devices practice. LTTS has also hired senior leadership from other companies to grow the automotive vertical. Recently, the company hired an ex-Cognizant executive as its Europe Chief Business Officer.

Other highlights

 Software vs hardware. LTTS indicated that currently software component is catching up to hardware and hence increased relevance of software over hardware. The Deputy CEO indicated that there can also be a time in the future when software component is at a peak and hardware plays catch up.

 Prudent approach to deals. LTTS indicated that it will not sign deals where (1) exiting is tough. The company is cautious of rebadging deals in Europe and (2) profitability is low.

 Tier-1 IT. LTTS indicated that it does not have a significant disadvantage to Tier-1 IT in larger-sized deals. In particular, LTTS has not had to walk away from a deal due to the size of balance sheet. Backing from L&T helps in this regard.

 M&A focus. LTTS has identified M&A opportunities in health tech, ISV and auto tech to help build capabilities. The company does not plan acquisitions to be large in the usual case. However, size is not a hard constraint in evaluation of M&A opportunities.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 5 IT Services L&T Technology Services

Exhibit 1: Condensed consolidated financials for LTTS, March fiscal year-ends, 2016-24E (Rs mn)

2016 2017 2018 2019 2020 2021E 2022E 2023E 2024E Profit model Revenues 30,662 32,483 37,471 50,783 56,191 54,581 65,003 76,683 88,262 EBITDA 5,195 5,847 5,756 9,147 11,105 9,940 13,131 15,527 17,697 Depreciation (589) (625) (888) (1,042) (1,829) (2,194) (2,311) (2,531) (2,763) EBIT 4,606 5,222 4,868 8,105 9,276 7,746 10,820 12,995 14,934 Other income 133 173 784 1,294 1,314 1,312 1,298 1,312 1,473 Forex gain/(loss) 712 418 1,150 934 738 343 916 1,261 1,290 Finance cost (25) (21) (24) (19) (365) (421) (426) (446) (466) Pretax profits 5,426 5,792 6,778 10,314 10,963 8,980 12,608 15,122 17,230 Tax (1,239) (1,542) (1,712) (2,630) (2,778) (2,312) (3,228) (3,871) (4,411) Profit after tax 4,187 4,250 5,066 7,684 8,185 6,667 9,381 11,251 12,819 Diluted earnings per share (Rs) 32.3 39.6 48.2 72.6 77.2 62.9 88.6 106.3 121.1 Balance sheet Total equity 3,161 14,856 19,364 24,791 27,686 32,331 38,875 46,728 55,679 Minority interest (5) (4) 3 31 69 101 133 165 197 Preference capital 7,500 — — — — — — — — Borrowings 1,955 1,019 702 702 303 — — — — Provisions 1,232 1,271 1,206 1,341 1,654 1,654 1,654 1,654 1,654 Other non-current liabilities — — 47 194 5,583 5,783 5,983 6,183 6,383 Other current liabilities 5,580 4,383 5,729 6,579 7,738 7,574 8,730 9,690 10,641 Total liabilities and equity 19,423 21,525 27,051 33,638 43,033 47,443 55,375 64,420 74,555 Cash and bank 834 674 1,542 2,051 2,440 9,377 12,537 16,833 21,640 Fixed assets 1,071 1,190 1,250 1,443 5,589 5,157 5,275 5,419 6,187 Intangible including goodwill 5,137 4,948 5,844 6,357 6,146 6,948 7,743 8,527 9,297 Capital work-in-progress 143 23 1 — 87 87 87 87 87 Receivables 8,729 9,401 11,823 13,063 17,317 14,505 17,809 21,009 24,181 Investments 555 1,946 2,207 5,749 6,420 6,420 6,420 6,420 6,420 Other assets 2,954 3,343 4,384 4,975 5,034 4,948 5,503 6,125 6,742 Total assets 19,423 21,525 27,051 33,638 43,033 47,443 55,375 64,420 74,555 Free cash flow Operating cash flow, excl. working capital 3,603 4,584 4,951 7,637 10,521 8,326 10,104 11,656 13,286 Working capital changes 994 (1,342) (1,701) (739) (4,287) 2,734 (2,703) (2,862) (2,838) Capital expenditure (1,268) (445) (851) (885) (1,511) (1,455) (3,224) (3,459) (4,301) Acquisitions — — (970) (847) (436) (1,110) — — — Other income 716 635 939 1,326 (524) 536 1,588 2,127 2,296 Free cash flow 4,045 3,432 2,368 6,492 3,763 9,030 5,765 7,462 8,444 Key ratios and assumptions Revenue growth (US$ terms) (%) 9.4 3.4 19.8 24.6 8.7 (6.3) 18.9 15.1 13.6 Re/US$ rate 65.5 67.0 64.6 70.2 71.5 74.1 74.2 76.0 77.0 EBITDA margin (%) 16.9 18.0 15.4 18.0 19.8 18.2 20.2 20.2 20.1 EBIT margin (%) 15.0 16.1 13.0 16.0 16.5 14.2 16.6 16.9 16.9 RoAE 31.4 32.4 21.9 24.2 25.5 27.9 28.2 28.8 29.1 RoACE 31.6 31.3 24.6 35.5 37.5 32.1 43.9 44.3 43.2

Source: Company, Kotak Institutional Equities estimates

6 KOTAK INSTITUTIONAL EQUITIES RESEARCH L&T Technology Services IT Services

Exhibit 2: Kotak Institutional Equities: valuation summary of key Indian technology companies

17-Mar-21 Mkt cap. EPS (Rs) P/E (X) EV/EBITDA (X) RoE (%) Company Price (Rs) Rating (Rs m) (US$ m) 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E HCL Technologies 987 ADD 2,679,609 36,940 49.5 52.7 57.8 19.9 18.7 17.1 12.6 11.4 10.1 24.6 21.8 20.3 Infosys 1,387 BUY 5,908,465 81,451 45.6 51.9 59.6 30.4 26.7 23.3 20.3 17.9 15.5 27.8 28.1 28.7 L&T Infotech 4,048 REDUCE 707,224 9,749 108.0 128.4 150.7 37.5 31.5 26.9 25.1 22.4 19.2 31.6 30.6 29.2 L&T Technology Services 2,589 ADD 272,004 3,750 63.6 88.5 106.3 40.7 29.3 24.4 25.5 19.1 15.9 22.3 26.2 26.2 Mindtree 1,999 SELL 329,258 4,539 66.6 76.5 82.0 30.0 26.1 24.4 19.5 17.6 16.2 31.3 29.3 25.9 Mphasis 1,684 REDUCE 314,789 4,340 66.4 76.0 85.1 25.4 22.2 19.8 16.6 14.4 12.7 20.2 20.8 20.8 TCS 3,113 REDUCE 11,514,963 158,739 89.4 106.5 118.8 34.8 29.2 26.2 23.7 20.3 18.2 37.8 39.8 39.5 Tech Mahindra 1,020 BUY 888,542 12,249 51.7 60.0 67.9 19.7 17.0 15.0 11.7 10.1 8.7 19.8 20.7 20.9 Wipro 420 ADD 2,299,277 31,697 18.6 19.1 22.1 22.6 21.9 19.0 14.0 13.0 11.1 19.3 18.4 18.5 KIE universe 155,011,169 2,137,492 29.1 22.3 18.7 14.1 11.4 9.9 11.2 13.1 14.2

Fair O/S shares EPS CAGR (%) EPS growth (%) Net Profit (Rs mn) EBITDA (Rs mn) Sales (Rs mn) Company Value (Rs) (mn) 2021-23E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E 2021E 2022E 2023E HCL Technologies 1,120 2,716 8.0 21.4 6.5 9.6 134,436 143,325 157,134 200,541 212,661 228,987 754,846 841,750 933,358 Infosys 1,530 4,250 14.4 17.0 14.0 14.7 193,590 220,684 253,222 279,288 313,780 356,336 1,007,356 1,174,017 1,349,128 L&T Infotech 3,810 176 18.1 24.7 18.9 17.4 19,017 22,604 26,530 27,130 29,974 34,293 123,791 146,537 173,758 L&T Technology Services 2,700 106 29.3 (18.2) 39.2 20.1 6,710 9,343 11,218 10,067 13,202 15,567 54,589 65,054 76,668 Mindtree 1,410 165 11.0 73.7 14.9 7.2 10,969 12,604 13,513 16,104 17,489 18,511 79,017 90,050 100,371 Mphasis 1,480 187 13.2 4.5 14.4 12.1 12,386 14,166 15,880 18,081 20,382 22,555 97,485 110,017 122,261 TCS 3,070 3,744 15.3 3.8 19.0 11.6 334,809 393,796 439,412 465,419 539,412 598,315 1,638,153 1,869,214 2,103,385 Tech Mahindra 1,135 880 14.5 12.8 16.1 13.0 45,493 52,803 59,688 68,048 76,698 86,156 379,470 418,243 467,480 Wipro 450 5,662 9.1 11.7 3.0 15.5 105,123 105,289 121,645 146,973 160,944 180,336 620,140 724,451 814,639 KIE universe 34.1 30.3 19.4 5,328,777 6,942,452 8,292,092 9,126,080 11,014,726 12,391,867 55,843,008 65,966,623 72,619,329

Source: Companies, Kotak Institutional Equities estimates

KOTAK INSTITUTIONAL EQUITIES RESEARCH 7 CAUTIOUS Automobiles & Components India MARCH 17, 2021 UPDATE BSE-30: 49,802

Electric scooter segment at an inflection point. We believe the electric scooter segment is set to grow exponentially led by (1) favorable government policies, (2) increase in competitive intensity and (3) an aggressive pricing strategy. We believe HMSI and TVS Motor portfolios will get impacted the most if they do not maintain market share in the electric scooter segment followed by Hero MotoCorp. Bajaj Auto will have to step up its game in order to make inroads into the electric scooter segment.

Domestic electric scooter segment is reaching an inflection point in electric mobility space

We believe the domestic electric scooter segment is ready to explode in the medium term led by (1) favorable government policies towards electrification (FAME-II, Make in India and PLI scheme for advanced chemistry cells), (2) increase in competitive intensity with entry of newer players and (3) aggressive pricing in comparison to ICE scooters. While incumbents in the ICE scooter segment have not been aggressive in their approach, newer players are looking to aggressively expand capacity over the next few years. Recently, Ola Electric has earmarked an investment of Rs24 bn to set up the world’s largest e-scooter factories with an initial annual capacity of 2 mn units, which can be extended to an annual capacity of 10 mn units (15% of global 2W production). This investment is comparable to Hero MotoCorp’s Rs16 bn capital expenditure for setting up a greenfield plant in Andhra Pradesh for ICE two-wheelers with total annual capacity of 1.8 mn units. Also, players like Ather Energy (increased its annual capacity from 25k units to 135k units), Okinawa (planning to increase its annual capacity from 90k units to 1 mn units over the next few years), Ampere (planning to increase its annual capacity from 50k units to 1 mn units over the next few years) and Hero Electric (will increase its annual capacity to 250k units from 70k units over the next few years) are expanding their capacities.

Aggressive pricing, favorable policy and localization to aid transition towards electrification

Currently the shift towards electric scooters is not significant because of limited production capacity of existing players like Hero Electric, Ather Energy and Okinawa, etc. while the bigger players like Bajaj Auto and TVS Motor are not aggressively marketing the electric scooters due to lower profitability. Our current cost of analysis for Bajaj e-Chetak versus Honda Activa FI implies breakeven of ~5.3 years (assuming 10 years of running). Post 50,000 km of running, there will be battery degradation due to which the range of an electric scooter will come down and the customer will need to incur additional cost to buy a new battery. However, we estimate battery prices will drop from US$250/kW-hr currently led by scale benefits and higher specific and volumetric energy density as battery chemistry improves, which will significantly reduce prices of e-scooters. Also, we believe Ola Electric will follow an aggressive pricing strategy as it has an appetite to burn cash. Ola Electric will also have high level of localized content, which includes setting up of battery plant (battery costs around 40-50% of the total vehicle cost) in India and help them further bring down the cost of manufacturing. The Indian government has approved a Rs180 bn production-linked incentive scheme for advanced chemistry cells in order to boost local manufacturing. Hence, we estimate that 50% of scooters will shift to electric by FY2030E. By FY2036E, we expect 60% of the scooter segment to shift towards electric. Hitesh Goel

Honda and TVS Motor scooter portfolios at risk if EV shift accelerates Rishi Vora

We believe HMSI and TVS Motor two-wheeler portfolios will get impacted the most given the higher mix of ICE scooters if the shift towards electric scooter accelerates followed by Hero MotoCorp if they do not up their game. Also, we believe margins for these companies will get negatively impacted as we believe newer players will aggressively price their products. Bajaj Auto does not have any offering in the ICE scooter segment; however, there is an opportunity for [email protected] the company to make inroads into the e-scooter segment, which has not been the case to date. 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. Automobiles & Components India

Exhibit 1: At current battery cost of US$250/kW-hr, breakeven for e-Chetak comes around ~5.3 years Comparison of the cost of ownership of an e-Chetak with Honda Activa FI

Bajaj e-Chetak Honda Activa FI (Premium) Battery prices (in $ per kW-hr) 250 On road price (Rs) 137,000 83,651 Incentives 22,000 — Cost to consumer (Rs) 115,000 83,651 Battery size (Kwh) 3.0 — Electricity cost (Rs/kwh) 10.0 — Range at full charge (km) 70 — Electricity cost (Rs/km) 0.4 — Electricity cost (Rs) 42,857 — Fuel cost (Rs) — 250,000 Maintenance cost (Rs) 5,000 15,000 Replacement value of battery 83,250 — Total cost of ownership of vehicle over 100,000 kms (Rs) 246,107 348,651 Break-even (km) 52,776 Break-even (years) 5.3

Key assumptions: (1) We have assumed two-wheeler runs 10,000 kms per year (2) We have assumed fuel cost of Rs100 per litre in our calculations (3) We have taken replacement cost of battery at current market price of $250 per kW-hr and it will be replaced twice during 10-year period. Price for second replacement cost of battery is assumed 50% lower than first replacement cost of battery

Source: Company, Kotak Institutional Equities estimates

Exhibit 2: We expect electric scooters to form 60% of the total scooter volumes by FY2036E Annual volume forecasts for scooters, March fiscal year-ends, 2020-36E (mn units, %)

Scooter ICE Electric Electric fleet proportion in 2-Wh (%) 2020 5.6 5.5 0.1 1.4 ` 2023E 6.3 5.5 0.8 12.6 2025E 7.7 6.1 1.5 20.0 2030E 12.1 6.0 6.0 50.0 2036E 20.0 8.0 12.0 60.0

CAGR (%) 8.3 2.4 36.8

Source: SIAM, Kotak Institutional Equities estimates

Exhibit 3: We expect electric scooters to form 47% of the total scooter population by FY2036E Annual population forecasts for scooters, March fiscal year-ends, 2020-36E (mn units, %)

Scooter ICE Electric Electric fleet proportion in 2-Wh (%) 2020 47.9 47.8 0.1 0.2 2023E 59.5 57.9 1.6 2.7 2025E 68.7 64.4 4.3 6.2 2030E 94.3 70.1 24.2 25.7 2036E 155.5 82.4 73.1 47.0 CAGR (%) 7.0 3.9 77.0

Source: SIAM, Kotak Institutional Equities estimates

KOTAK INSTITUTIONAL EQUITIES RESEARCH 9 Company Report Banks ATTRACTIVE Sector March 17, 2021 UPDATE The retail show goes on. Our broad understanding is that the dominance of retail in BSE-30: 49,802 overall loan growth, which was briefly interrupted due to Covid, is likely to resume. Several interesting trends have emerged in retail across countries in recent decades, which have implications on the loan composition within retail loans. Mortgages would continue to be the prime driver of growth. We believe that these trends would be well- captured by the large private banks and SBI.

Optimistic on retail for loan growth – extant drivers still remain the best bet

Within the loan segments that are likely to resume growth, we are still optimistic on the retail segment. The corporate loan book will grow but significant consolidation in the asset-heavy industries towards a few strong players limits this opportunity. A strong manufacturing-led economy could imply higher corporate loan growth but companies are likely to be a lot careful than before in credit consumption. The brunt of the Covid impact is being borne by MSMEs and we see this segment to remain the slowest in recovery.

Levers for growth in retail appear to be attractive; mortgages to dominate share of business

Despite a lot of discussions on corporate capex led recovery in loan demand for India, we still see merit to back the retail segment as the runway is as attractive as it was pre-Covid. We see the share of retail loans to steadily move upwards from current levels, which has been discussed in our previous reports. Within retail, we see the share of short-term consumption-linked products to grow faster but mortgages would retain the largest share within the retail segment. In this regard, we have discussed the credit card book in fair detail. We build our thesis looking at other countries that have experienced these cycles.

Mortgages, homeownership and refinancing show interesting traits

We looked at several countries to understand the broad trends in housing ownership and mortgages. While home ownership rate provides insights into the opportunity segment, we have M B Mahesh, CFA delved deeper looking at age of the buyer profile, which has increased and average number of persons per household, which has declined. We looked at the refinancing market and the Nischint Chawathe borrowers’ behavior across cycles and understand that contrary to expectations, borrowers are pro-cyclical in their refinancing decisions. Abhijeet Sakhare Frontline banks are well-positioned Ashlesh Sonje We maintain our positive view on the frontline banks as we expect their growth rates to be higher than the industry average. The customer segments targeted by these banks appear to be less exposed to Covid and hence, showing the highest promise for accelerated recovery to Dipanjan Ghosh normalized levels of business performance. These banks have the best-in-class liability franchise led by a strong acquisition model that is built on superior products. Along with a tailwind of coming out of Covid, we believe their valuations have further room for expansion. Within this, we like ICICI Bank, Axis Bank, HDFC Bank and SBI as our preferred plays. We expect these banks to have a better revenue profile that has granular revenue streams as compared to the mid and small tier banks.

[email protected] Contact: +91 22 6218 6427

For Private Circulation Only. In the US, this document may only be distributed to QIBs (qualified institutional buyers) as defined under rule 144A of the Securities Act of 1933. This document is not for public distribution and has been furnished to you solely for your information and may not be reproduced or redistributed to any other person. The manner of circulation and distribution of this document may be restricted by law or regulation in certain countries, including the United States. Persons into whose possession this document may come are required to inform themselves of, and to observe, such restrictions.

Sector Banks

RETAIL LOANS LIKELY TO CONTINUE DOMINATION OF CREDIT CONSUMPTION We forecast contribution of retail loans to overall loans to keep rising in the medium to long term despite the impact of Covid. We are less optimistic that the share of corporate credit would increase meaningfully even if there is a bounce-back from current levels. History shows that the segments that are most affected by a crisis are reluctant to consume credit as aggressively as they have done in the previous cycle.

Consolidation as a theme would continue

We have explained in our August 24, 2020 note ‘Changing directions’ (link) where we looked at the lending environment during the Savings and Loans Crisis and the impact it had on banking in the subsequent decade. We discussed the consolidation theme that emerged post this banking crisis and the unmistakable repetition that is emerging in our country as well. The lending market post 1990s saw concentration increasing for the frontline banks not only in the US but in most countries. The frontline banks offered a different revenue structure as it was built on non-lending metrics like wealth, payment or other capital market allied activities. This resulted in a superior RoE structure. We see a broadly similar trend emerging for the frontline banks in India as well, as these banks have explored different routes in the past two decades but are now gradually converging on their business models.

The key challenge would be for mid-tier private banks, which are attempting to build scale but are behind the frontline banks as they have either a cost disadvantage, lack of differentiation or a risky revenue profile. Despite the overwhelming feature of market dominance by the larger players, lending is unlikely to establish ‘a winner takes all’ outcome. Availability of deposit insurance has its own merits and challenges as it allows lenders to offer higher rates and build a business model on the same. Smaller banks/NBFCs have survived despite the consolidation theme picking up. Small-ticket lending needs customization and a different skillset of monitoring that large banks would find challenging. Massive consolidation in public banks shows that the smaller banks/NBFCs have challenged the large banks over time.

The theme to back retail loan for growth to continue

We believe that the retail loan growth, which partly slowed down on account of Covid-19, is likely to resume. While the timing and pace of acceleration is far from clear, it appears to be the segment that has the highest probability to recover. Corporate India has shown greater resilience from an asset quality standpoint but we are not yet convinced that a capex cycle led recovery in loan growth is around the corner. We shall explain this in subsequent sections. Lending to SMEs was showing great promise till Covid-19 reversed this trend. Two issues unfolding for SMEs: (1) Borrowers’ income profile that was affected is yet to recover, which implies lenders would need a few more years to firmly establish trends in business. Lenders are likely to move up on the quality curve of borrowers to reduce risk. (2) The highly leveraged SME borrowers are likely to prune down debt till business stabilizes.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 3

Banks Sector

Exhibit 1: Share of mortgage and other retail credit has Exhibit 2: Growth in corporate credit has been poor over the increased by ~1,500 bps over the past decade past few years Breakup of non-food bank credit in India, March fiscal year-ends, Growth across bank credit segments in India, March fiscal year-ends, 2005 onwards (%) 2005 onwards (%)

Mortgages Other retail Mortgages Other retail Industry Services Industry Services Agri and allied activities Agri and allied activities 100 80 12 12 13 12 13 14 13 13 12 12 13 13 14 13 13 13 13 80 60 20 23 24 24 23 25 25 24 24 24 24 24 25 27 28 28 28 60 40

42 39 39 30 40 40 41 43 44 45 46 46 44 42 38 35 33 32 20

13 14 20 12 12 13 11 11 12 12 - 11 9 9 9 9 9 9 10 13 13 13 12 11 10 10 9 9 10 10 11 12 13 13 15 15

- (20)

2005 2006 2007 2008 2013 2014 2015 2016 2017 2018 2019 2020 2009 2010 2011 2012

2006 2007 2009 2010 2011 2013 2014 2016 2017 2019 2020 2005 2008 2012 2015 2018 Jan-21 Jan-21

Source: RBI Source: RBI

Retail loan growth has two contrasting trends: mortgage and consumption loans

Covid-19 slowed down growth in retail loan, which was in one of its longest expansions since 2010-11. This segment, in our view, offers the highest probability for growth to recover at the earliest. The share of retail loan in the overall loans is currently at ~29% and we expect this to steadily increase from current levels.

 Housing loans would dominate retail loan growth from a size perspective. The underlying factors for this growth are healthy and appear to have accelerated post Covid- 19 as evidenced. After a long time, we note that the stuck inventory (both high-cost and closer-to-finish) is seeing healthy sales traction partly aided by relief from state governments on house registration charges. Our discussion with our real estate analyst broadly corroborates a similar view. We see new launches from builders, which is giving comfort on the resumption of the mortgage cycle. Several discussions with lenders suggest that the affordability metrics that they are tracking is fairly comfortable. House prices have not appreciated and salaried segment has seen a broadly unchanged income levels. Savings level appears to have increased within this segment which is aiding this decision-making process.

Age dynamics: the ominous writing signals that are currently on the wall. We see a change in the savings behavior with each passing generation. The younger generation is probably a lot more comfortable to own financial assets over physical assets. Consequently, the time to buy a property is getting longer over time. There could be a lot of drivers behind this development such as job stability. Earlier generations found it easier to work in one or a few companies throughout their working career, which may not be the case today. A house with a mortgage makes it harder to move, which is probably critical when there needs to be flexibility in location/roles. It is possible that the price appreciation of a house is far lower than the financial assets, leading to a deferred decision. We are also not sure of the nature of the houses that is getting built and if it is making it harder for the younger generation to get into this asset at an early age. In our view, the traditional reasons to own a house still probably remain unchanged.

 Unsecured loans would be much smaller in size but would play a critical role in building profit levers. We have discussed the critical contribution of this business to overall profits for several banks that are quite active in this product. Covid-19 has allowed lenders to work through their weaker borrowers and restart disbursements. We expect

4 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

this to gain traction in the next few months as the underlying credit costs appear to be largely within the lenders initial estimates. With unsecured loans, we like the credit card business as we believe that the steady shift to digital payments would lead to best-in-class growth rates among all product categories. Consumption-led loan growth such as credit cards are likely to be good lead indicators of a recovery or otherwise. The change in loan growth is the highest in this segment of the loan book. The repayment tends to be higher immediately after the crisis and the spend trends tend to slow down just ahead of the slowdown.

Look to the west and the east, which broadly gives the same outcome

We looked at various markets across the world to understand the composition of loan book and overlaying their growth or loan book composition with the underlying economic conditions. However, we do admit that collating data has not been easy and our interpretation may not necessarily be accurate. The structure of each economy is not similar and we are less certain of the development of the local bond markets. Further, consumption patterns and policies undertaken to build the economy are likely to be different or not necessarily comparable. However, the unmistakable trend that we see is the dominance of retail loans in these markets.

Some of the striking features in these studies are that (1) retail assets are usually much faster to liquidate as it is usually sectors that goes into slowdown, which results in most corporate borrowers coming under stress though the intensity of these stress is contingent on various factors which include the capital structure or the operating leverage of the business etc., (2) leverage tends to be a lot more uniform in the corporate sector while retail borrowers lifestyle preferences are dissimilar, (3) the age distribution of borrowers is quite wide, which results in different levels of savings and income that helps to mitigate the risk, and (4) borrowers come from a wide range of employment and the mobility of employment allows them to quickly work through their bad loan problem, if any.

USA: a secular growth in housing loans

The overall share of retail loans had seen a secular growth for the period beginning in 1985 and ending in 2009. In this period, we saw a steady increase in retail loans with the bulk of the loan growth driven by the housing loan segment. The share of loans nearly doubled to 60% from 30% levels (see Exhibit 3).

KOTAK INSTITUTIONAL EQUITIES RESEARCH 5

Banks Sector

Exhibit 3: Share of retail loans doubled from ~30% between 1970s to 2010 Break-up of loans in US across segments, calendar year-ends, 1973-2021

Commercial and industrial Other retail loans Mortgages Others 100

80

37

32

35

29 39

41

30

29

43

42

29

42

29

42

44

44

28

24

42

29

44 27

42

44

25

28

25

47

26

51

53

47

52

47

50

48 47

46

55

53

55

46

55

45

56

45

59 58 60 56

40

20

0

1975 1979 1981 1985 1989 1991 1995 1999 2001 2005 2009 2011 2015 2017 2019 2021 1977 1983 1987 1993 1997 2003 2007 2013 1973

Source: US Federal Reserve, Kotak Institutional Equities

Exhibit 4 shows that the corporate segment did recover in terms of loan growth in the early 1990s after a long period of slowdown that began in the 1980s. However, in terms of contribution to overall loan growth, it did not sustain. Note that we are not sure if this could be replicated in India given that we are attempting to refocus the corporate sector towards credit consuming manufacturing sector as compared to a more services-driven economy in countries like the US.

Exhibit 4: Corporate loan growth bounced back after the S&L crisis followed by the oil shock Break-up of loans in US across segments, calendar year-ends, 1973-2021

Commercial and industrial Retail loans 15.0

10.0

5.0

-

(5.0)

(10.0)

(15.0)

1978 1980 1984 1986 1988 1992 1994 2000 2002 2008 2010 2014 2016 2018 1976 1982 1990 1996 1998 2004 2006 2012 2020 1974

Source: US Federal Reserve, Kotak Institutional Equities

6 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 5 shows a fresh perspective on the outstanding debt levels at the household level. This broadly corroborates with the loan book of lenders as well. ~80% of the overall debt for a typical US household is driven by a residential property. This could be through a regular mortgage or a line of credit against a residential property. The installment loans are primarily dominated by auto loans and education loans. The highly profitable and exciting credit card book is <5% of the overall debt for the borrower. We bring a long dated series to show that the importance of mortgage lending has largely remained unchanged in this period.

Exhibit 5: Mortgages is ~80% of the overall debt in US while auto/education loans is ~15% and credit card balances is ~3-4% Amount of debt of all families, distributed by type of debt, 1989–2019 surveys (%)

Type of debt 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 Secured by residential property Primary residence 69.0 72.1 73.1 71.4 75.2 75.2 74.7 74.1 73.8 69.4 70.6 Other 7.7 10.3 7.6 7.5 6.2 8.5 10.1 9.8 9.0 9.4 8.9 Lines of credit not secured by residential property 1.4 .8 .6 .3 .5 .7 .4 1.0 .7 1.1 .6 Installment loans 16.8 11.4 12.0 13.1 12.3 11.0 10.2 11.1 13.1 16.0 16.1 Credit card balances 2.8 3.2 3.9 3.9 3.4 3.0 3.5 2.9 2.4 2.6 2.6 Other 2.2 2.3 2.9 3.7 2.3 1.6 1.1 1.1 1.1 1.5 1.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Source: US Federal Reserve, Kotak Institutional Equities

Exhibits 6 and 7 show the break-up of loans in the household segment from a lender’s perspective. This is broadly similar to what we have seen in the previous exhibit which looks at the debt levels from a borrower’s perspective. The growth trajectory shows that the short- term lending products offer strong insights of recovery or slowdown in the economy as compared to long-duration products like mortgages.

Exhibit 6: Mortgages contribute 70% of retail loans Exhibit 7: Unsecured loans show better signs of change Break-up of loans across segments for US banks, calendar year-ends, Growth in mortgages, retail and credit cards, calendar year-ends, 2003-20 (%) 2003-20 (%)

Mortgage HE Revolving Auto Loan Mortgage Retail loan Credit Card Credit Card Student Loan Other 30 100

20 80

10 60

0

40

73

73

73

74

72

72

71

71

70

70

70

69

69

68

68

68

67 67 -10 20

-20

0

2004 2005 2006 2007 2008 2009 2011 2012 2013 2014 2016 2017 2018 2019 2010 2015 2020

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2003

Source: US Federal Reserve, Kotak Institutional Equities Source: US Federal Reserve, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 7

Banks Sector

Australia: mortgages dominate lending and have been frequent causes for concern

A detailed note on the credit cycles in Australia has been well documented in the note from Bureau of International Settlements (link). While most of the banks’ loan growth is dominated by housing, it is interesting to note that the share of corporate loans was higher than retail loans until ~1990. The share of corporate loans had been on a declining trend since the peak in the mid-1980s.

Exhibit 8: Retail loans has been steadily rising since 1990s Exhibit 9: Contribution of mortgage witnessed a steady increase Break-up of retail and corporate loan book in Australia, calendar year- Share of mortgage in total loans and mortgage loan growth in ends, 1976-2020 (%) Australia, calendar year-ends, 1976-2020 (%)

Corporate Retail Share of housing to total loans Growth 85 70

68 56

51 42

34 28

17 14

0 0

1979 1982 1985 1988 1976 1991 1994 1997 2000 2003 2006 2009 2012 2015 2018

2010 1992 1994 1996 1998 2000 2002 2004 2006 2008 2012 2014 2016 2018 2020 1990

Source: Reserve Bank of Australia, Kotak Institutional Equities Source: Reserve Bank of Australia, Kotak Institutional Equities

Canada: growth in mortgage credit slowing down

Housing credit (mortgages and HELOCs combined) is a major segment in Canada as it makes up ~78% of retail credit (Exhibit 10). However, this large share has been broadly stable over the past ~5 years. Growth in mortgage credit in Canada has slowed down significantly post the Global Financial Crisis (Exhibit 11) – down from ~13% in 2007 to <5% in 2QCY20. While mortgage lending rates were cut meaningfully by lenders, they have had limited success in restoring mortgage credit growth to pre-GFC levels.

Exhibit 10: Breakup of retail credit has been broadly stable over the last four years Breakup of retail credit balances by segment in Canada (%)

Mortgages HELOCs Auto loans LOCs Credit cards All other credit 100 9 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 80 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 11 11 11 11 11 11 11 11 11 11 11 11 10 10 10 10 60

40 66 67 67 67 66 67 67 66 66 67 67 67 67 67 68 68

20

0

1QCY17 2QCY17 4QCY17 1QCY18 2QCY18 3QCY18 1QCY19 2QCY19 4QCY19 2QCY20 3QCY20 3QCY17 4QCY18 3QCY19 1QCY20 4QCY16

Source: Equifax and Canada Mortgage and Housing Corporation (CMHC) calculations

8 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 11: Growth in mortgage credit peaked out at ~13% in 2007 and slipped to <5% in 2QCY20 Residential mortgage credit in Canada (US$ bn) and conventional mortgage lending rate (5-year tenor, %)

Residential mortgage credit (US$ bn) Yoy growth (%) Mortgage interest rate (%) 2,000 15

1,600 12

1,200 9

800 6

400 3

0 0

2002 2005 2006 2007 2008 2009 2010 2013 2014 2015 2016 2017 2003 2004 2011 2012 2018 2019

2QCY20

Notes: (1) Annualized growth rate for 2QCY20. (2) As of 2019, 74% of mortgages outstanding in Canada were based on a fixed rate, 21% were variable- linked and 5% were of a hybrid nature.

Source: Canada Mortgage and Housing Corporation (CMHC) calculations, Statistics Canada

Consumption loans can offer to be a good lead indicator when we see Spain, Ireland and UK

We looked at Spain, Ireland and the UK and the trends are not too different. These countries too show that the mortgages are a much larger proportion of the loan book. The corporate and the retail cycles were deeply impacted post the Global Financial Crisis. However, lending in these countries provides two interesting highlights that are noteworthy: (1) Corporate deleveraging, unlike retail deleveraging, appears to be a much longer cycle from a duration perspective. (2) Within retail, the amplitude of slowdown is a lot more in consumption loans over housing loans. This exhibit essentially tells us that the recovery of the consumption- linked loan is likely to be faster and higher.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 9

Banks Sector

Exhibit 12: Share of corporate credit has declined from 56% to Exhibit 13: Consumption loans saw robust growth over the past 47% over the past decade; mortgages have gained share 5 years Credit breakup across segments in Spain, 3QCY07 – 3QCY20 (%) Credit growth across segments in Spain, 3QCY07 – 3QCY20 (%)

Loans for house purchase Consumption loans Home loans Consumption Other retail credit Total corporate credit Other retail Total retail 100 30

80 20 48 48 46 45 47 54 55 55 55 55 54 51 49 50 60 10

40 0

43 43 43 43 20 36 36 36 36 37 38 42 42 43 42 (10)

0 (20)

3QCY07 3QCY08 3QCY09 3QCY11 3QCY12 3QCY14 3QCY16 3QCY17 3QCY19 3QCY20 3QCY11 3QCY12 3QCY13 3QCY14 3QCY15 3QCY16 3QCY17 3QCY18 3QCY19 3QCY20 3QCY13 3QCY15 3QCY18 3QCY07 3QCY08 3QCY09 3QCY10 3QCY10

Source: Banco de Espana Source: Banco de Espana

Exhibit 14: Share of housing in retail credit has been broadly Exhibit 15: Consumption loan growth has a much higher stable in the range of 80-85% since 2003 changes to growth trajectory as compared to mortgages Breakup of credit to private Irish households across various segments, Growth in mortgages and other consumption loans, 3QCY07- 2003-19 (%) 3QCY20 (%)

Mortgages Investments Others Mortgages Others/consumption

100 45

12

13

13

13

13

17

14

15

14

14

14 15

17 16

17

16 17

80 30

60 15

86

86

85

85

84

84

84

84

83

83

83 82 82 0

40 81

81

80 80

20 -15

0 -30

2004 2006 2008 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2005 2007 2009

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2015 2016 2017 2018 2019 2014

Source: Central Bank of Ireland Source: Central Bank of Ireland

10 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 16: Non-mortgages growth has had a much higher change in growth and a good lead indicator Growth in mortgages and non-mortgages, calendar year-ends, 1994-2019 (%)

Mortgages Non mortgages 20.0

15.0

10.0

5.0

-

(5.0)

(10.0)

1995 1997 1999 2001 2003 2005 2007 2008 2009 2010 2011 2012 2013 2014 2016 2018 1996 1998 2000 2002 2004 2006 2015 2017 2019 1994

Source: Bank of England

KOTAK INSTITUTIONAL EQUITIES RESEARCH 11

Banks Sector

AGE TO OWN A HOUSE HAS INCREASED: A CROSS-COUNTRY STUDY There has been a marked change in house ownership in recent decades with the younger generation preferring to delay owning a housing asset. Job stability, rising prices and alternative sources of wealth creation have delayed the purchase decision. However, we note that house acts as a significant source of wealth for borrowers and mortgage continues to play a critical role in building this asset across countries. We look at select markets that give us information on the borrowers’ buying behavior. We broadly break them into three buckets: the first-time buyer, repeat buyer and second home buyer or investor.

The time-to-buy is not getting younger in most countries

Owning a house represents an important decision in most countries. Household wealth is primarily dominated by this physical asset. While this condition is still true across markets, we notice that there is a perceptible change in ownership pattern across various countries with one unmistakable trend of the age to own a house. We have no clear evidence if this would have changed due to Covid-19 as we are seeing a recovery in housing and mortgages demand faster than consumption loans.

We explain in subsequent sections that this has played a critical role in shaping the mortgage loan industry as well. The average age of the mortgage, the size of the house that is being bought, the income and the net worth of the borrower have changed over this period.

USA: solid insights into homeownership trends across decades

Since 1960, the US has seen an increase in population at ~1% CAGR while the overall households have increased by 1.5% CAGR. The average number of persons per household has declined to 2.5X from a peak of 3.3X in 1960. For now, this trend seems to have stabilized in recent decades. We do notice that the share of single-person household has been on the rise but the impact is still quite negligible as compared to the overall size of households in the US.

The four exhibits below show the most of the important trends that are needed to understand home ownership pattern in the US. Exhibit 17 shows that the median age of a homeowner has progressively increased to 52 from a low of 45 prior to 1990. Exhibit 6 shows that the homeownership rate in the US peaked just prior to the Global Financial Crisis at 70% levels and declined to ~65% levels but had started to recover in recent years.

12 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 17: Median age has progressively increased to 52 from a Exhibit 18: Homeownership rate in US peaked in 2005 at ~70% low of 45 in 1985 levels Median age – US homeowner, calendar year-ends, 1960-2020 (%) Homeownership rate in US, calendar year-ends, 1960-2020 (%)

55 70

52 68

49 66

46 64

43 62

40 60

1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 2014 2017 2020

1987 2008 1963 1966 1969 1972 1975 1978 1981 1984 1990 1993 1996 1999 2002 2005 2011 2014 2017 2020 1960

Source: US Census Bureau, Kotak Institutional Equities Source: US Federal Reserve, Kotak Institutional Equities

The most striking feature is the exhibit below. We broke the median age of ownership each year in various median age buckets. We have not included >65 years and below 25 years to help explain this chart better. The ownership of below 25 years is quite negligible but there is a marked increase in proportion of ownership of >65 years. The exhibit below shows that the over the past few decades, the median age of house owners has seen a few decadal shifts. In the 1970s, house ownership started much earlier with the proportion of 25-35 years playing a significant role in buying a house. However, by 1990 this age population was replaced by 35-44 years. The 45-54 years played a much important role by 1997 and by 2005 this was replaced by 55-64 years of age. Today, it is the >65 years who dominate the ownership of houses in the US at 27% as compared to 20% in 2005.

Exhibit 19: The preference to own a house has progressively increased across time (the chart says something else) Proportion of homeownership based on median age, calendar year-ends, 1962-2020

Population Median age 25 to 34 years Population Median age 35 to 44 years Population Median age 45 to 54 years Population Median age 55 to 64 years 25

22

19

16

13

10

1966 1968 1970 1976 1978 1980 1982 1988 1990 1992 1998 2000 2002 2004 2010 2012 2014 2020 1962 1964 1972 1974 1984 1986 1994 1996 2006 2008 2016 2018

Source: US Census Bureau, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 13

Banks Sector

The exhibit below shows that the average size per household had been on a declining trend since 1960s. This would help explain the faster growth in houses as compared to population. However, this trend has stabilized in recent decades. However, recent studies indicate that there is an increase in single household. While it is currently a smaller subset, it could provide further room for a reduction in the average size per household in the medium term. From a mortgage opportunity perspective, the counter balance would be these houses are likely to be smaller as compared to the current size of houses.

Exhibit 20: The average size per household appears to have been maximized Average number of people per household, 1960-2020 (%)

4.0

3.6

3.2

2.8

2.4

2.0

1960 1962 1964 1966 1968 1970 1972 1974 1984 1986 1988 1990 1992 1993 1995 1997 1999 2011 2012 2014 2016 2018 2020 1978 1980 1982 2001 2003 2005 2007 2009 1976

Source: US Census Bureau, Kotak Institutional Equities

Mortgages are the default source of purchase of a housing loan in US as seen in the exhibit below. The contribution of the traditional mortgage is ~95% though the nature of these loans has changed over time. Cash purchase despite an ageing buyer profile is quite low. We are not sure where the Indian borrower on this topic is. We understand discussing with various builders that the penetration of mortgages is higher in South and within this the tendency to maximize the loan amount is higher for salaried individuals.

Exhibit 21: Purchases through cash is quite low at 5% levels Nature of financing a new housing purchase

Conventional mortgage Insured/guaranteed Cash 100

80

60

90 90

89

87 84

40 81

80

79 79

78 78

76

75

74 74 74

73

72 72

71 71 71

69 69 69 69

67 67

66 66

65

64

62 62 62

61

59

58 58

57 57 20 50

0

1978 1984 1988 1990 1994 1996 2000 2006 2012 2016 2018 1982 1986 1992 1998 2002 2004 2008 2010 2014 1980

Source: US Census Bureau

14 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

From the survey of consumer finance we looked at the mortgage behavior of borrowers. Note that the delay in house-ownership has implications to the overall mortgage market. The income, net worth and quality of houses that is likely to be under mortgage at the time of origination are likely to be different with a changing demographic profile. Exhibits 22 and 23 confirm this trend. We note that the borrowers who have a mortgage below 35 years have been on a declining trend while this has increased for borrowers who are at 65-74 years of age. However, most of the mortgage book is between 35-64 years of age.

Exhibit 22: Age profile of holders of mortgage debt has Exhibit 23: 60% of “couple with children” have a mortgage increased in recent decades debt followed by “couple with no child” Break-up of age profile of mortgage debt, calendar year-ends, 1989- Family structure of a mortgage debt holder, calendar year-ends, 2019 (%) 1989-2019 (%)

1989 1992 1995 1998 2001 2004 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 70 2007 2010 2013 2016 2019 70

56 56

42 42

28 28 14 14 0 Single with Single, no Single, no Couple with Couple, no 0 child(ren) child, age child, age child(ren) child Below 35 35–44 45–54 55–64 65–74 >75 <55 >55

Source: Survey of Consumer Finance US Source: Survey of Consumer Finance US

From an income or net worth perspective, the access to mortgage credit has been a lot more challenging at the middle to lower income segment. A tightening of credit standards could probably be the most plausible explanation as the conditions deteriorated in the portfolio that were of higher risk after the Global Financial Crisis. Exhibits 24 and 25 confirm this underlying trend in the US.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 15

Banks Sector

Exhibit 24: Mortgage debt ownership has reduced the most in Exhibit 25: Mortgage debt ownership has reduced the most in the 40-60% percentile of income the 25-50% percentile of net worth Percentile of income of mortgage debt, calendar year-ends, 1989- Net worth distribution of a mortgage debt holder, calendar year-ends, 2019 (%) 1989-2019 (%)

1989 1992 1995 1998 2001 2004 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2007 2010 2013 2016 2019 80 70

64 56

48 42

32 28

16 14

0 0 Below 20 20–39.9 40–59.9 60–79.9 80–89.9 90–100 Below 25 25–49.9 50–74.9 75–89.9 90–100

Source: Survey of Consumer Finance US Source: Survey of Consumer Finance US

Home Equity Line of Credit

One of the key challenges with the housing market is that it is highly illiquid. Hence, the ability of borrowers or investors to extract equity from the asset has been quite challenging. The US overcame this challenge through the Home Equity Line of Credit (HELOC). There have been several variations to this product which include the most common reverse mortgage program which was done through the Home Equity Conversion Mortgage (HECM), which is insured by the Federal Housing Administration (FHA) and constituted a significant portion of the US reverse mortgage market. A detail work of this program is available in this link to the article.

HELOC, unlike a regular mortgage is not well penetrated as <5% of the overall households use this product. The penetration of the mortgage book is at 40% levels. This product usage had maximum acceptance (9% of households) between 2004 and 2007 or till the economy was impacted by the Global Financial Crisis. Since then, it has been on a decline. The usage of this product has declined the maximum in the 40-60% percentile of income. The maximum acceptance of the product is with families with children though here too there are definite signs of it declining. We note that the decline is higher with the higher income segments. It would appear that the product allowed borrowers to leverage a lot more than desired during times when there was strong property price appreciation.

16 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 26: The debt ownership has reduced the most in the 40- Exhibit 27: 60% of “couple with children” have a HELOC debt 60% percentile of income followed by “couple with no child” Percentile of income of HELOC debt, calendar year-ends, 1989-2019 Family structure of a HELOC debt holder, calendar year-ends, 1989- (%) 2019 (%)

1989 1992 1995 1998 2001 2004 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2007 2010 2013 2016 2019 25 16

13 20

10 15

6 10 3

5 0 Single with Single, no Single, no Couple with Couple, no 0 child(ren) child, age child, age child(ren) child Below 20 20–39.9 40–59.9 60–79.9 80–89.9 90–100 <55 >55

Source: Survey of Consumer Finance US Source: Survey of Consumer Finance US

Exhibit 28: Reduction in HELOC debt is the highest in the 90- Exhibit 29: Nearly all segments have seen a reduction in HELOC 100% of income population utilization Percentile of income of HELOC debt, calendar year-ends, 1989-2019 Net worth distribution of a HELOC debt holder, calendar year-ends, (%) 1989-2019 (%)

1989 1992 1995 1998 2001 2004 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2007 2010 2013 2016 2019 25 20

20 16

15 12

10 8

5 4

0 0 Less than 2020–39.9 40–59.9 60–79.9 80–89.9 90–100 Below 25 25–49.9 50–74.9 75–89.9 90–100

Source: Survey of Consumer Finance US Source: Survey of Consumer Finance US

Disbursements can lead to a false sense of comfort

We have seen a marked increase in disbursements in the US for housing loans. However, the overall data shows that the loan growth has not been that strong as one would have expected when we hear the headline growth on disbursements.

Exhibit 30 shows that the overall housing loan growth was at 5% yoy and this has remained in relatively tight band for the past few years. Exhibit 31 shows another interesting trend where we have seen that the overall repayment rate has increased to the highest level in the previous few decades and matches closely to what was seen in the highest refinancing period, which was around CY2003-04.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 17

Banks Sector

Exhibit 30: Housing loan growth in the US has grown at ~5% Exhibit 31: US Housing loan repayment rates have shot up to an CAGR in recent years all-time high as refinancing hits a new high Housing loan growth rate, calendar year-ends, 2004-20 (%) Housing loan repayment rate, calendar year-ends, 2004-20 (%)

20 40

16 35 15 33 32 31 12 12 11 10 26 26 24 24 22 5 5 20 5 5 20 19 20 20 18 3 3 16 16 16 16 2 2 1 0 0 14 -2 -3 8 -5 -4 -4

-10 0

2018 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2019 2020 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2004

Source: US Federal Reserve Source: US Federal Reserve

Exhibit 32 shows that the disbursement for CY2020 was closer to the highest levels seen in CY2003-04. Exhibit 33 shows that the disbursements can be further broken into two parts: (1) disbursements for purchase of new houses and (2) refinancing of existing loans. We note that the sharp increase in refinancing is partly led by lower interest rates. Note that the fixed rate loans are quite popular in the US which implies that the borrowers don’t benefit from the decline in rates that is offered on new borrowers. The cost-benefit advantage needs to be in favor of the borrower to see an increase in refinancing.

Exhibit 32: Disbursements hit a new high in CY2020 Exhibit 33: Refinancing drove a lot of this disbursement Disbursement of loans in mortgages, calendar year-ends, 2002-20 Disbursement of loans for refinancing and fresh purchase, calendar (US$ bn) year-ends, 2002-20 (US$ bn)

4,500 Refinance Purchase 3,000

3,600 2,500

2,000 2,700

1,500 1,800 1,000

900 500

- -

2005 2015 2005 2015 2003 2004 2006 2007 2008 2009 2010 2011 2012 2013 2014 2016 2017 2018 2019 2020 2002 2003 2004 2006 2007 2008 2009 2010 2011 2012 2013 2014 2016 2017 2018 2019 2020 2002

Source: New York Fed Consumer Credit Panel/Equifax Source: New York Fed Consumer Credit Panel/Equifax

18 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

We break down disbursements for purchase of houses into three broad categories of home loan borrowers: (1) first-time buyer, (2) repeat buyer and (3) investor or a buyer who is taking an additional loan for a new house. Exhibit 34 shows that the major change in home loan borrower is the resurgence in the second and third category of borrowers. The growth in first-time buyers has not been too different from the trend levels that we have seen in earlier years.

Exhibit 34: Sharp increase in repeat buyer and investors has led to growth in loan for fresh purchases Loan disbursements across buyer segments, calendar year-ends, 2002-20 (US$ bn)

First Time Buyer Repeat Buyer 2nd homes/investors 1,750

1,400

1,050

700

350

-

2002 2003 2005 2006 2008 2010 2011 2013 2014 2016 2018 2019 2007 2009 2012 2015 2017 2020 2004

Source: New York Fed Consumer Credit Panel/Equifax

Australia shows a broadly similar age characteristics as of the US

Australia’s homeownership data is not too different from the US at 67% levels as of 2016 and has remained in this region since the 1960s. Homeownership peaks at 80% levels from the data that is available in the table below.

However, we see a similar pattern emerging in Australia that we discussed in the US. There is a marked difference in homeownership over long periods in time. Progressively, we see that the younger generation is taking a much longer time to own a house as compared to its previous generation. However, ownership of 30-34 years was 64% in 1971 while the same in 2016 was at 50%.

Exhibit 35: The share of younger population that is looking to buy a house has progressively declined Home ownership by birth cohort and age group, calendar year-ends, 1947-2018 (%)

Year 25–29 30–34 35–39 40–44 45–49 50–54 55–59 60–64 65–69 1947–1951 54.2 68.0 72.3 75.1 77.8 79.6 81.1 81.3 81.7 1952–1956 53.1 64.8 69.1 73.3 76.1 78.3 78.9 79.4 1957–1961 51.1 59.1 67.2 71.7 75.0 76.0 76.8 1962–1966 49.8 58.6 66.0 70.7 72.3 73.7 1967–1971 43.5 57.3 65.2 67.7 69.8 1972–1976 43.2 57.1 62.2 65.3 1977–1981 43.4 53.5 58.9 1982–1986 41.3 50.0 1987–1991 37.4

Source: Australian Bureau of Statistics

Exhibit 36 shows the break-up of homeowners and the nature of encumbrances on this asset. As per the survey, there is a progressively higher number of owners who carry a mortgage on these loans as compared to earlier years.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 19

Banks Sector

Exhibit 36: 55% of home owners carry a mortgage today as compared to 40% in 1990s Proportion of owners by type, calendar year-ends, 1995-2018 (%)

Owner with a mortgage Owner without a mortgage Renter private landlord Renter state or territory housing authority 45

36

27

18

9

0

1995 1996 1997 1998 2001 2004 2006 2008 2010 2014 2018 2000 2003 2012 2016

Source: Australian Bureau of Statistics

We looked at the surveys that are conducted periodically by the Reserve Bank of Australia to understand the mortgage market. These surveys give more insight between owners and investors as well. The data given below broadly gives a similar interpretation from what is available through the census data. Exhibit 37 gives the mortgage penetration based on income levels. The penetration levels has remained broadly stable across most income levels for owners though the borrowers who have looked at house purchase from an investment perspective is a lot more leveraged for the upper half of the income segment. In both the instances (owners or investors), the bottom two decile of income population has seen a decline in recent surveys. While the borrower profile is broadly similar when we look at it from a net worth perspective, it is only interesting for the investment property where we see borrowers with substantially lower net worth showing a higher inclination to take a loan from an investment perspective (Exhibit 39 and 40).

Exhibit 37: Penetration levels of mortgage loans stable across Exhibit 38: Mortgages for investment property is preferred with three decades by income profile higher income segment Households with mortgage loans based on income in Australia, Households with mortgage loans (investment property) based on calendar year-ends, 2002-18 (%) income in Australia, calendar year-ends, 2002-18 (%)

2002 2006 2010 2014 2018 2002 2006 2010 2014 2018 70 30

56 24

42 18

28 12

14 6

0 0 Below 20 20-39.9 40-59.9 60-79.9 80-100 Overall Below 20 20-39.9 40-59.9 60-79.9 80-100 Overall

Source: Reserve Bank of Australia, Kotak Institutional Equities Source: Reserve Bank of Australia, Kotak Institutional Equities

20 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 39: Penetration levels of mortgage loans stable across Exhibit 40: Leverage has increased with borrowers with a much three decades by net worth profile lower net worth than before Households with mortgage loans based on net worth in Australia, Households with mortgage loans based on net worth in Australia, calendar year-ends, 2002-18 (%) calendar year-ends, 2002-18 (%)

2002 2006 2010 2014 2018 2002 2006 2010 2014 2018 60 25

48 20

36 15

24 10

12 5

0 0 Less than 20-39.9 40-59.9 60-79.9 80-100 Less than 20-39.9 40-59.9 60-79.9 80-100 20 20

Source: Reserve Bank of Australia, Kotak Institutional Equities Source: Reserve Bank of Australia, Kotak Institutional Equities

Exhibits 41 and 42 show the age profile of the borrower. Whether we look at the borrower who is a homeowner or borrowing a loan from an investment perspective, the average age of the borrower has only increased. This broadly corroborates with analysis based on age cohorts presented in the earlier exhibits.

Exhibit 41: The share of older aged borrower has increased in Exhibit 42: The distribution of investor property with mortgage the past decade debt has reduced at the lower age segment Share of mortgage debt distributed by age profile, calendar year- Share of mortgage debt (investor property) distributed by age profile, ends, 2002-18 (%) calendar year-ends, 2002-18 (%)

2002 2006 2010 2014 2018 2002 2006 2010 2014 2018 70 30

56 24

42 18

28 12

14 6

0 0 15-24 25-34 35-44 45-54 55-64 65-74 >75 15-24 25-34 35-44 45-54 55-64 65-74 >75

Source: Reserve Bank of Australia, Kotak Institutional Equities Source: Survey of Consumer Finance US

KOTAK INSTITUTIONAL EQUITIES RESEARCH 21

Banks Sector

Canada: a broadly similar trend that is in place

Canada too shows a broadly similar characteristic that we saw with the US and Australia. We observe that the rate of homeownership had increased slowly to ~70% in 2011 from ~60% in 1971, while there was a marginal decline in 2016 (see Exhibit 43). Homeownership characteristics across age groups also reveal a similar trend – the home ownership rate has increased meaningfully for the older age groups (Exhibit 44).

Exhibit 43: Homeownership has increased slowly but steadily Exhibit 44: Homeownership for the younger age groups has and peaked in 2011 been largely flat during 1976-2016 Home ownership rate in Canada, calendar year-ends, 1971-2016 (%) Home ownership rate in Canada across age groups (%)

75 1971 1976 1981 1986 1991 100

60 76 75 80 72 70 70 67

45 60 44 36 30 40

20 15

0

0

>65

1976 1981 1991 1996 2006 2011 2016 1971 1986 2001

20 34to 55 64to 35 54to

Source: Statistics Canada, Kotak Institutional Equities Source: Statistics Canada, Kotak Institutional Equities

We attempt to look at how the household structure has changed in select countries across the world to draw inferences about global societal shifts. We look at Canada and Spain where relatively longer historical data is available. We observe that the number of households in Canada more than doubled from ~6 mn in 1971 to ~13 mn in 2011.

One of the factors driving this increase is the decline in average household size which has shrunk from ~3.5 to ~2.5 over the same period. Households with one or two members constituted >60% in 2011. This is an outcome of social changes that have occurred over the last few decades – including but not limited to (1) children moving out to establish their own independent households, (2) lower fertility, (3) preference towards bearing fewer children and (4) relatively high rates of separation and divorce.

Some of these phenomena can be inferred from the increase in proportion of one person households and couples without children (Exhibit 46). The proportion of households with one or two members has increased to ~60% in Canada and ~56% in Spain. The shift in Spain has been more recent.

22 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 45: Average household size in Canada has declined; Exhibit 46: Households with one or two members accounted for number of households has grown swiftly >60% of Canadian households Average size of a household and number of households in Canada, Distribution of private households in Canada by number of members, calendar year-ends, 1851-2011 (#) calendar year-ends, 1851-2011 (#) (%)

Source: Statistics Canada, Kotak Institutional Equities Source: Statistics Canada, Kotak Institutional Equities

We further explore the breakup of households across different age groups. The key observation here is that the proportion of households headed by young members has declined. In Canada, the proportion of houses headed by members aged less than 45 has declined from ~51% in 1991 to ~24% in 2016 (Exhibit 48). The proportion of households headed by members aged >55 years increased from ~34% in 1991 to ~45% in 2016. This shift in age-wise distribution of household heads has been observed in Spain also – where the proportion of households headed by members aged >55 years increased from ~44% in 2002 to ~50% in 2017.

We believe these trends can be explained by a couple of factors: (1) increase in longevity of life (resulting in higher share of aged people in the population) and (2) adult children moving out from parental homes by passing on the responsibility of household head to older parents. This could be partly explained by the increasing share of Spanish households that have no working members (Exhibit 56). However, this data will likely be impacted by the Spanish Financial Crisis of 2008-14.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 23

Banks Sector

Exhibit 47: Proportion of one person families and couples w/o Exhibit 48: Proportion of households headed by young members children increased over 2001-16 (<44 years) has declined steadily Breakup of Canadian households by household type, calendar year- Breakup of private households by age of primary household ends, 2001-16 (%) maintainer in Canada, calendar year-ends, 1991-16 (%)

One-person Couple without children 15-24 25-34 35-44 45-54 55-64 Over 65 Couple with children Lone-parent family 100 100 19 9.7 9.6 10.3 10.6 21 21 22 25 8.9 8.9 8.9 8.9 80 80 14 14 17 19 29.6 27.6 26.5 20 31.5 60 17 60 22 23 23 20 25.8 40 24 40 24.2 25.1 25.6 24 21 18 17 20 20 22 25.7 26.8 27.6 28.2 15 14 14 14 5 4 4 3

0 0 3

1991 2006 2011 2016 2001

2001 2011 2016 2006

Source: Statistics Canada, Kotak Institutional Equities Source: Statistics Canada, Kotak Institutional Equities

We delve further into the mortgage characteristics of the country to understand it better. We observe that mortgage penetration has not changed significantly over the past ~6 years – it has hovered around the ~28% mark (Exhibit 49). This is lower than that which was seen in the US at 40% levels. However, on a longer horizon (and when measured differently), mortgage penetration in Canada has increased over the period from 1999-2019, but declined marginally thereafter (Exhibit 51).

Exhibit 49: Mortgage penetration in Canada has been in the Exhibit 50: Mobility of household decreases sharply with age as range of 27-29% over the last six years household have a mortgage or home Mortgage penetration in Canada has been in the range of 27-29% Mobility statistics for owner households in Canada by age, 2011 (%) over the last six years All household members living in a different dwelling in 2006 35 At least one member living in the same dwelling in 2006 100 8 17 12 28 23 28 80 42 21 73 60

14 88 92 40 83 77 72 7 58 20 27 0 0

Under 35 to 44 45 to 54 55 to 64 65 to 74 75 and Total

2015 2016 2017 2018 2019 2014 35 above

3QCY20

Source: Equifax and Canada Mortgage and Housing Corporation Source: Equifax and Canada Mortgage and Housing Corporation (CMHC) calculations (CMHC) calculations

24 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 51: Mortgage penetration increased over last two decades, but saw some decline recently Percentage of Canadian families holding different forms of debt (%)

40

32 1999 24 2012 16 2016

8 2019

0

Other Other debt

Line of credit loansVehicle

Student Student loans

estate

Mortgagedebt

residence

Credit cardCreditand

installmentdebt mortgageprincipalon mortgage on other realotheron mortgage

Source: Statistics Canada (Survey of Financial Security, 2019)

We try to deconstruct this further to uncover any ageing-related trends observed in other countries (while we are challenged by the length historical data available). We observe that debt (of any nature) penetration itself has been broadly flat for the youngest age group over the last two decades, while it has increased for the older generation.

Exhibit 52: Proportion of debt-free families in the highest age Exhibit 53: Share of higher age mortgage holders increased group has declined over last 20 years marginally between 2017 and 2020 Percentage of Canadian families that are debt-free, by age group of Share in outstanding mortgage balance by age group of the major income recipient (%) mortgage holder in Canada (%)

1999 2005 2012 2016 2019 Under 25 25-34 35-44 45-54 55-64 65-74 Over 74 75 100 6 6 6 6 6 6 6 6 6 6 6 7 7 16 16 17 17 17 17 17 17 17 17 18 60 80 18 18

60 28 27 27 27 27 27 27 27 27 27 27 27 27 45

40 30 30 30 30 30 30 30 30 30 30 30 30 30 30 20 15 18 18 18 17 17 17 17 17 17 17 17 16 16 0

0

All

3QCY17 1QCY18 3QCY18 1QCY19 3QCY19 1QCY20 4QCY17 2QCY18 4QCY18 2QCY19 4QCY19 2QCY20 3QCY20 <35

>65

35-44 45-54

Source: Statistics Canada (Survey of Financial Security, 2019) Source: Statistics Canada (Survey of Financial Security, 2019)

Spain shows up with similar trends as well on house-ownership

While we are not able to gather extensive data on the Spanish housing bubble, it nevertheless shows a broadly similar trend. Exhibits 54 and 55 show that the number of members in a household has been on a decline and the proportion of ownership by age has progressively increased.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 25

Banks Sector

Exhibit 54: Number of members in a household has declined on Exhibit 55: Proportion of young households has declined average Breakup of number of households by age of household head in Spain Breakup of number of households by count of members, in Spain (%) (%)

One Two Three Four >Five Under 35 35-44 45-54 55-64 65-74 Over 74 100 100 10.6 6.8 6.9 5.9 5.6 5.7 11 10 13 15 14 15 19.7 18.2 16.6 22.6 80 24.9 80 17 17 24.3 15 14 16 16 20.7 21.8 21.1 17 16 17 60 19.4 60 17 18 23.9 19 24.3 20 20 20 21 40 30.3 30.4 40 22 28.7 30.1 23 25.7 27.8 22 22 22 22 20 20 21 20 22.4 23.3 25.2 25.5 15.2 16.6 14 15 13 11 9 8 0 0 2002 2005 2008 2011 2014 2017 2002 2005 2008 2011 2014 2017

Source: 'Survey of Household Finances' by Banco de Espana Source: 'Survey of Household Finances' by Banco de Espana

Exhibit 56: Penetration of mortgages in the under 35 age Exhibit 57: Households with outstanding debt on investment category has declined property has increased over the years across age groups Percentage of households with mortgage debt outstanding on main Percentage of households with debt outstanding on properties other residence, by age of household head, 2002-17 (%) than main residence, by age of household head (%)

2002 2005 2008 2011 2014 2017 2002 2005 2008 2011 2014 2017 60 15

48 12

36 9

24 6

12 3

0 0 Under 35 35-44 45-54 55-64 65-74 Over 74 Under 35 35-44 45-54 55-64 65-74 Over 74

Source: 'Survey of Household Finances' by Banco de Espana Source: 'Survey of Household Finances' by Banco de Espana

26 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 58: Penetration of personal loans increased sharply after Exhibit 59: Penetration of credit cards has seen more consistent the Spanish Financial Crisis increase in the higher age groups Percentage of households with personal loans outstanding, by age of Percentage of households with credit cards outstanding, by age of household head (%) household head (%)

2002 2005 2008 2011 2014 2017 2005 2008 2011 2014 2017 35 15

28 12

21 9

14 6

7 3

0 0 Under 35 35-44 45-54 55-64 65-74 Over 74 Under 35 35-44 45-54 55-64 65-74 Over 74

Source: 'Survey of Household Finances' by Banco de Espana Source: 'Survey of Household Finances' by Banco de Espana

UK shows other interesting insights

While we are not able to give long-term charts of the UK, we do see some interesting trends that we saw in other geographies. The broad trends are quite similar to that we saw in Australia with the share of the owned properties that is under mortgage is ~50% of the overall homeownership rate. The property ownership across various income profiles shows that the ownership has been maintained in the upper income decile.

Exhibit 60: 67% is owned and 50% of these owners continue to Exhibit 61: Ownership maintained in the upper decile while it have a mortgage on it has declined in the middle income segment Ownership of prime residence in UK, calendar year-ends, 2008-18 Property ownership rates, by total household net income decile, (%) calendar year-ends, 2008-18 (%) (%)

Owned without mortgage Owned with mortgage 2012 2014 2016 2018 Rented/ rent free 100 100

80 32 31 32 34 80 34 34 60 60 40 38 37 36 33 33 32 40 20

20 - 30 31 32 32 33 33

0 Overall

Decile 3 Decile 4 Decile 5 Decile 6 Decile 7 Decile 8 Decile 9 Decile 1 Decile 2

2008 2010 2012 2014 2016 2018 Decile 10

Source: Office for National Statistics, Kotak Institutional Equities Source: Office for National Statistics, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 27

Banks Sector

Ireland shows a marginally different trend post the housing impairment cycle

Ireland is probably one of the few countries that we have seen with a different trend. Most of the underlying trends have stabilized or reversed to some extent in recent years. We believe that the experience of a bad housing cycle that they had experienced in the past two decades is playing out in this currently. The broad underlying characteristics remains nevertheless similar to what we have seen in other countries.

Exhibit 62: Average size of a household has trended downward Exhibit 63: Homeownership increased between 1961 and 1991, since 1960s, saw marginal increase over 2006-11 but has declined thereafter Average number of members per household in Ireland (#) Rate of home ownership in Ireland (%)

5 100

4.0 79 3.9 77 75 4 3.7 80 74 3.5 71 70 3.3 68 3.1 3.0 60 3 2.8 2.7 2.8 60

2 40

1 20

0 0

1961 1981 2002 2006 2016 1971 1991 2011

1966 1971 1981 1986 2002 2006 2011 2016 1996 1991

Source: Central Statistical Office, Ireland Source: Central Statistical Office, Ireland

Exhibit 64: Proportion of households renting a house has Exhibit 65: Proportion of households owning a house with a increased between 2006 and 2011 across all age groups >25 mortgage peaks out at the age of 35 to 44 Breakup of Irish households by type of house, 2011 (%) Breakup of Irish households by type of house, 2016 (%)

Owner occupied wo loan Owner occupied with loan Owner occupied wo loan Owner occupied with loan Rented Others Rented Others 100 100 9 9 21 17 15 13 16 14 32 25 5 23 19 6 80 80 29 45 18 40 20 31 56 33 60 67 60 44 45 86 73 54 80 54 60 40 60 81 40 57 81 66 49 63 49 51 48 20 20 32 26 37 33 12 23 4 19 6 9 12 5 5 5 6 10

0 3 3 3 0

30 to to 34 30 to 39 35 to 44 40 to 49 45 to 59 55 25 to to 2529 to 5054 to 6064

30 to to 34 30 to 39 35 to 44 40 to 49 45 to 59 55 25 to to 2529 to 5054 to 6064

Under 25 Under

Above 64 Above Under 25 Under Above64

Note: 'Others' includes households occupying a house free of rent or Note: 'Others' includes households occupying a house free of rent or where data is unavailable. where data is unavailable.

Source: Central Statistical Office, Ireland Source: Central Statistical Office, Ireland

28 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 66: Age at which the number of renting households is highest has increased since 1991 Proportion of householders in Ireland that stay in a rented accommodation, by age (%)

1991 2016 4.5

3.6

2.7

1.8

0.9

0.0

20 30 45 55 60 70 25 35 40 50 65 75 80 >85

Source: Central Statistical Office, Ireland

Hong Kong too shows a broadly similar characteristic

In the past 37 years, Hong Kong has seen a 2% growth in households and the bulk of this growth is probably explained by the decline in average household size. Average household size has declined to <3 individuals per household by 2019 from ~4 in 1982.

Exhibit 67: Average size of households in Hong Kong has declined over the last ~40 years Number of domestic households in Hong Kong and average household size (#)

Number of households Average household size (mn) (#) 3.0 4.5

2.4 4.0

1.8 3.5

1.2 3.0

0.6 2.5

0.0 2.0

1983 1987 1993 1997 2001 2007 2011 2015 2017 1989 1991 1995 1999 2003 2005 2009 2013 2019 1985

Source: Census and Statistics Department (Hong Kong)

KOTAK INSTITUTIONAL EQUITIES RESEARCH 29

Banks Sector

REFINANCING AND THE BORROWER TRAITS Housing loan refinancing allows borrowers to (1) extend duration and reduce EMI, (2) lower interest rates, (3) extract equity. However, depending on the economic cycle and what drove growth prior to the cycle, borrowers tend to use this product differently.

Refinancing show interesting traits depending on the economic cycle

Refinancing of loans shows that the rationale to undertake a refinancing activity is not uniform and shifts based on the economic conditions that are prevailing at that point in time. However, refinancing appears to be highly contingent based on the nature of the underlying mortgage transaction. Different countries have got different characteristics on housing loans based on the nature of the interest rates whether it is fixed floating or some combination of the two as there is a cost involved in these transactions. For example, the share of fixed rate loans dominates housing loan lending in the US while it is a combination between the two in the UK and several markets in the EU offer different products. This has implication on the refinancing market as the interest rate pass through led argument tends to be a lot lower in the variable interest rate housing market. We looked at the Freddie Mac book to get a perspective of the underlying borrower behavior based on their regular surveys.

Quantum of refinancing shows pro-cyclicality

Exhibit 68 shows the refinancing activity of the borrower where there is a change in loan amount post refinancing. Contrary to our expectation where we believed that borrowers are likely to leverage a bit more immediately post a slowdown, the data shows the opposite. We saw this behavior even in the credit card book when borrowers can actively look to reduce risk immediately post a slowdown and not increase it. The period immediately before the Global Financial Crisis saw borrowers looking to increase the loan limit beyond 5% while the borrowers kept refinancing with no change in loan amount after that period and this continued till 2013.

Exhibit 68: Borrowers tend to be pro-cyclical borrowing more during boom times Nature of refinancing by value, calendar fiscal year-ends, 1994-2019 (%)

5% Higher Loan Amount No Change In Loan Amount Lower Loan Amount 100.0 12 18 15 26 22 80.0 34 35 42 38 41 42 41 44 49 48 45 52 56 62 62 63 60.0 74 78 80 83 83

87 40.0 80 83 72 76 62 62 55 59 56 56 58 52 48 50 52 20.0 46 42 36 35 34 24 19 17 14 15

-

1995 1997 1999 2002 2004 2006 2008 2010 2013 2015 2017 2019 1996 1998 2000 2001 2003 2005 2007 2009 2011 2012 2014 2016 2018 1994

Source: Freddie Mac, Kotak Institutional Equities

As housing prices stabilized and probably has started to increase, which could perhaps explain more confidence to leverage, we saw that the past few years have seen borrowers looking to refinance a much higher amount than the loans outstanding. Exhibit 69 shows that the median ratio of new to old value of the housing loans tends to drop despite there being higher equity for the borrower to refinance a higher quantum.

30 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 69: Property appreciation leads to lower LTV compared to the new property price Median ratio of new interest rate to old interest rate, calendar fiscal year-ends, 1994-2019 (%)

Median Ratio of New to Old Rate 1.20

0.96

0.72

0.48

0.24

0.00

Source: Freddie Mac, Kotak Institutional Equities

Median age to refinance changes to reflect the sharp difference in contracted rates and available rates to refinance

The median age to refinance shows the borrowers that are coming in for refinancing are looking for different rationale. During periods of sharp price appreciation or prolonged economic cycle expansion, borrowers are probably looking at the available equity in their housing loan to refinance a loan. However, the conditions to refinance changes when we pass a slowdown. The recent refinancing shows that the borrowers have not only kept the outstanding loan amount unchanged post the global financial crisis but they have also refinanced loans that were older indicating that the interest rate differential was substantial to take this benefit.

Exhibit 70: Property price appreciation results in older loans getting refinanced Nature of refinancing by value, calendar year-ends, 1994-2019 (%)

Median Age of Refinanced Loan (years) 8.0

6.4

4.8

7 7 3.2 6 6 6 5 5 5 5 5 4 4 1.6 3 4 3 4 3 3 3 3 3 3 3 3 2 2

0.0

1994 1995 1996 1997 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 1998 1999 2000 2001 2002 2003 2004 2005

Source: Freddie Mac, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 31

Banks Sector

Exhibit 71: Visible correlation between repayment rates and property price growth Relationship between property price growth, mortgage repayments and disbursements in Hong Kong, calendar year-ends, 1998-2020 (%)

Repayment rate (%) Disbursement rate (%) Property price growth 55 45

44 30

33 15

22 0

11 (15)

0 (30)

1998 1999 2002 2003 2007 2008 2011 2012 2016 2017 2001 2004 2005 2006 2009 2010 2013 2014 2015 2018 2019 2020 2000

Note: As of December 2020, >97% of mortgages in Hong Kong were linked to Hong Kong Inter-bank Offered Rate (HIBOR) or Best Lending Rate (BLR)

Source: Hong Kong Monetary Authority

Tenor of loans show that borrowers are pro-cyclical as well

Exhibits 72, 73 and 74 show the borrowers’ tenor preference during various stages in the economic cycle. The US borrowers show a higher preference for 30-year loan for mortgages. However, when we look at the refinancing preference, we note that borrowers tend to shift their tenor preference to a longer option during periods of economic expansion. The borrower exhibits a greater confidence to accept not only a higher quantum of loans (as the refinancing amount is higher) but is willing to service for a much longer time as well. The contrary behavior is seen immediately after a slowdown. Borrowers tend to lower down their tenor period as we see immediately after the Global Financial Crisis (post 2008) and after the tech boom (post 2000).

Exhibit 72: Post the economic slowdown in 2000 and 2008, consumers lowered tenor in 30-year loan Tenor transition matrix of 30-year loans, calendar year-ends, 1994-2019 (%)

1-Year ARM1 ARM - Hybrid2 Balloon3 FRM 15yr4 FRM 20yr5 FRM 30yr6

100%

80%

60%

40%

20%

0%

1994 1998 1999 2000 2001 2005 2006 2007 2011 2012 2013 2014 2018 2019 1996 1997 2002 2003 2004 2008 2009 2010 2015 2016 2017 1995

Source: Freddie Mac, Kotak Institutional Equities

32 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 73: Post the economic slowdown in 2000 and 2008, consumers lowered tenor in 20-year loans Tenor transition matrix of 20-year loans, calendar year-ends, 1994-2019 (%)

1-Year ARM1 ARM - Hybrid2 Balloon3 FRM 15yr4 FRM 20yr5 FRM 30yr6

100%

80%

60%

40%

20%

0%

1994 1998 1999 2000 2001 2005 2006 2007 2011 2012 2013 2014 2018 2019 1996 1997 2002 2003 2004 2008 2009 2010 2015 2016 2017 1995

Source: Freddie Mac, Kotak Institutional Equities

Exhibit 74: Tenor transition is the lowest here immediately post a slowdown Tenor transition matrix of 15-year loans, calendar year-ends, 1994-2019 (%)

100% 1-Year ARM1 ARM - Hybrid2 Balloon3 FRM 15yr4 FRM 20yr5 FRM 30yr6

80%

60%

40%

20%

0%

1994 1995 1999 2000 2001 2002 2003 2007 2008 2009 2010 2011 2012 2015 2016 2017 2018 2019 1996 1997 1998 2004 2005 2006 2013 2014

Source: Freddie Mac, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 33

Banks Sector

ASSET QUALITY: LOOKING BEYOND THE TRADITIONAL SAFETY ARGUMENT It is reasonably well documented that the riskiness of this product segment is the lowest. However, borrower behavior in Canada offers better insight into a borrower with mortgage and otherwise. Also, Ireland provides an interesting perspective between an owner-occupied borrower and investment mortgage borrower.

The exhibits below show the delinquency behavior of the mortgage book in the US, Spain, Canada, Hong Kong and Ireland. As expected, the share of delinquency in the mortgage book is lower as compared to the other retail or household lending products when we look at most of the data on a through-the-cycle basis.

Exhibit 75: Delinquencies spiked sharply after the Global Financial Crisis 90+ DPD by loan type, calendar year-ends, 1998-2020 (%)

Mortgage Auto Credit card All 16

13

10

6

3

0

1QCY99 4QCY99 1QCY02 4QCY02 1QCY05 4QCY05 3QCY06 4QCY08 3QCY09 3QCY12 2QCY13 3QCY15 2QCY16 2QCY19 1QCY20 2QCY01 3QCY03 2QCY04 2QCY07 1QCY08 2QCY10 1QCY11 4QCY11 1QCY14 4QCY14 1QCY17 4QCY17 3QCY18 4QCY20 3QCY00

Source: New York Fed Consumer Credit Panel/Equifax

Exhibit 76: Delinquencies spiked sharply after the Asian Financial Crisis Delinquency ratio and rescheduled loans ratio on mortgage credit in Hong Kong, December calendar year- ends, 1998-2020 (%)

Delinquency ratio (%) Rescheduled loans ratio (%) 1.5

1.2

0.9

0.6

0.3

0.0

Dec-96 Dec-99 Dec-00 Dec-02 Dec-03 Dec-06 Dec-09 Dec-10 Dec-13 Dec-16 Dec-19 Dec-20 Dec-98 Dec-01 Dec-04 Dec-05 Dec-07 Dec-08 Dec-11 Dec-12 Dec-14 Dec-15 Dec-17 Dec-18 Dec-97

Source: Hong Kong Monetary Authority

34 KOTAK INSTITUTIONAL EQUITIES RESEARCH

Sector Banks

Exhibit 77: Housing credit saw doubtful loans rise to ~6% at the peak of the Spanish Financial Crisis Proportion of doubtful loans across segments in Spain, 3QCY99-3QCY20 (%)

House purchase Consumption Other retail Corporate 25

20

15

10

5

0

3QCY99 3QCY01 3QCY03 3QCY05 3QCY07 3QCY09 3QCY11 3QCY13 3QCY15 3QCY17 3QCY19 3QCY02 3QCY04 3QCY06 3QCY08 3QCY10 3QCY12 3QCY14 3QCY16 3QCY18 3QCY20 3QCY00

Source: Banco de Espana

Canada provides an interesting analysis on the delinquent behavior from an age perspective as well as borrower with multiple lending products which includes and does not include a mortgage loan. While we would have expected delinquency to be higher at lower ages, the data for Canada shows that it is not necessarily true though we admit that the difference across ages is not too material. The data shows that the net worth or income which should be higher than borrowers in the lower ages is not translating into lower delinquencies.

Exhibit 78: Delinquencies on mortgages have been below 0.5% Exhibit 79: Delinquencies have been highest for borrowers over the last 13 years; HELOC has been even better above age of 65; lowest for borrowers in age 25-34 90+ DPD delinquencies across credit segments in Canada (%) Mortgage delinquency rate (90+ DPD) by age of the mortgage holder, 3QCY13-3QCY20 (%) Mortgage HELOC Credit card Auto LOC 25-34 35-44 45-54 2.5 55-64 65 and over 0.45 2.0 0.36 1.5 0.27 1.0 0.18 0.5 0.09 0.0

0.00

3QCY07 3QCY12 3QCY13 3QCY14 3QCY15 3QCY16 3QCY17 3QCY18 3QCY19 3QCY20 3QCY09 3QCY10 3QCY11

3QCY08

3QCY13 3QCY14 3QCY16 3QCY17 3QCY18 3QCY19 3QCY20 3QCY15 Note: 90+ DPD data on mortgages prior to 3QCY12 comes from a different annual series. Gaps are front-filled. Source: Equifax and Canada Mortgage and Housing Corporation (CMHC) calculations Source: Equifax and Canada Mortgage and Housing Corporation (CMHC) calculations, Canadian Housing Observer

Exhibits 80-81 show interesting trends on delinquency behavior across lending products when the borrower has a mortgage as compared to non-mortgage borrowers. Despite a higher incidence of indebtedness caused by mortgage, borrower delinquency actually has turned out to be lower as compared to higher which would have been the most common view. Further, borrowers with mortgage have a lower tendency to go bankrupt individually.

KOTAK INSTITUTIONAL EQUITIES RESEARCH 35

Banks Sector

Exhibit 80: Delinquencies on other segments are lower for Exhibit 81: Mortgage holders have shown lower propensity to borrowers who also have an outstanding mortgage go bankrupt Delinquency rates on other loan segments for mortgage holders in Share of consumers with recent bankruptcy, mortgage holders vs Canada, 3QCY12 – 3QCY20 (%) consumers without a mortgage, 3QCY12 – 3QCY20 (%)

Auto - wm LOC - wm Consumers without a mortgage with new bankruptcy Credit card - wm Auto - wom Mortgage holders with new bankruptcy LOC - wom Credit card - wom 2.00 3.5

1.60 2.8

1.20 2.1

0.80 1.4

0.7 0.40

0.0 0.00

3QCY12 3QCY13 3QCY15 3QCY16 3QCY18 3QCY19 3QCY14 3QCY17 3QCY20

3QCY16 4QCY16 2QCY17 4QCY17 1QCY18 2QCY18 3QCY18 1QCY19 2QCY19 3QCY19 4QCY19 2QCY20 3QCY17 4QCY18 1QCY20 3QCY20 1QCY17

Source: Equifax and Canada Mortgage and Housing Corporation Source: Equifax and Canada Mortgage and Housing Corporation (CMHC) calculations (CMHC) calculations

Ireland went through a real estate crisis but the following exhibit attempts to look at the differential in performance between an “owner occupier” and “investment mortgage” delinquencies. The delinquency ratio, as expected, is much higher in the investment mortgage as compared to an owner occupied mortgage. However, the pace of change is much faster in the former as compared to the latter.

Exhibit 82: Owner occupier mortgage delinquencies declined Exhibit 83: Investment mortgage delinquencies declined after after 2012 2012 Delinquency ratio on PDH mortgages in Ireland (%) Delinquency ratio on BTL mortgages in Ireland (%)

upto 90 DPD 91 to 180 DPD 181 to 365 DPD upto 90 DPD 91 to 180 DPD 181 to 365 DPD 365 to 735 DPD 2 to 5 years 5 to 10 years 365 to 735 DPD 2 to 5 years 5 to 10 years Over 10 years Over 10 years 20 30

16 24

12 18

8 12

4 6

0

-

3QCY09 1QCY10 3QCY10 1QCY11 3QCY11 1QCY12 3QCY12 1QCY13 3QCY13 1QCY14 3QCY14 1QCY15 1QCY16 1QCY17 1QCY18 1QCY19 1QCY20 3QCY15 3QCY16 3QCY17 3QCY18 3QCY19 3QCY20

3QCY13 3QCY14 3QCY15 3QCY16 3QCY17 3QCY18 3QCY19 3QCY20 3QCY12

Note: 'PDH' stands for ‘Principal Dwelling House’. Note: 'BTL' stands for buy-to-let.

Source: Central Bank of Ireland Source: Central Bank of Ireland

36 KOTAK INSTITUTIONAL EQUITIES RESEARCH ATTRACTIVE Telecommunication Services India MARCH 17, 2021 UPDATE BSE-30: 50,364

Telemeter 3.0—Bharti shines, Jio loses on VLR front; VIL gains majorly in UP (W). TRAI’s January 2021 subscriber data indicates (1) Bharti sustained its lead on net additions gaining 5.9 mn overall and 5.5 mobile BB subscribers, (2) Jio’s wireless net additions remained low at 2 mn with VLR subscriber base declining by 3.4 mn and (3) VIL saw an uptick of 1.7 mn led by a surge of 3.7 mn subscribers in UP (W) alone, while it lost base in 18/22 circles. We prefer Bharti to play the potential recovery or consolidation in the sector, either of which is likely to play out in the medium term.

Bharti continues to lead on net additions; VIL’s uptick attributed to a surge in UP West

 Bharti saw a further acceleration in subscriber additions, as it gained 5.9 mn wireless subscribers on a net basis in January 2021 as compared to the monthly pace of 3-4 mn over the past six months; Bharti has led the pack for the sixth month on a trot now.

 Jio added 2 mn subscribers in January, higher than 0.5 mn addition in the previous month but similar to an average of 1.9 mn monthly additions in the preceding four months.

 VIL added 1.7 mn subscribers in January, its first uptick in 15 months. However, the gain can be attributed to a surge of 3.7 mn subscribers in UP West alone; VIL lost subscribers in 18 out of 22 circles, same as the previous month, while gaining modestly in the remaining three.

 In the mobile broadband segment, Bharti continued to gain good traction adding 5.5 mn subscribers in January 2021 and cumulative 28.5 mn in the past six months, much better than Jio’s 2 mn and 9.9 mn for the respective periods; VIL continues to lag on this front as well, adding 1.9 mn and 7.4 mn for the given periods.

 In the past six months, the wireless subscriber market share for (1) Bharti has risen by 1.7 ppt to 29.6%, (2) Jio has risen by 0.3 ppt to 35.3% and (3) VIL has reduced by 1.8 ppt to 24.6%.

Bharti retains leadership on VLR subscriber base, while Jio loses active subscribers

Bharti’s VLR subscribers print showed further improvement with net gains of 6.9 mn adding up to a base of 336 mn. Jio lost 3.4 mn VLR subscribers, most in the past nine months, to end at a base of 325 mn now. VIL’s loss on VLR subscribers was marginal at 0.3 mn, with its VLR base declining to 256 mn. On a 12-month basis, Bharti’s market share in VLR subscriber base increased by 2.6 ppt yoy to 34.3% in January, while Jio saw a smaller uptick of 1.8 ppt to 33.2% during the given period; VIL has reported a steady erosion of its VLR subscriber base throughout the year with its share declining by 3.9 ppt to 26.2% now.

Pace of subscriber additions in fixed broadband business remains steady

The fixed broadband business for Jio and Bharti gained 0.18 mn and 0.09 mn subscribers respectively in the month of January, at a pace similar to the recent months. We highlight that the pace of additions in fixed broadband business remains slower than expectations despite the attractive entry-level plans by the industry. Jio and Bharti now have 2.3 mn and 2.9 mn fixed Tarun Lakhotia broadband subscribers, respectively; overall fixed BB subscriber base stands at 22.7 mn now. Aniket Sethi Bharti best placed to play sector recovery or consolidation in the medium term

We reiterate our BUY rating on Bharti expecting it to gain the most from a potential recovery in the industry economics and/or plausible consolidation in the medium term. The acquisition of significant spectrum by Bharti and Jio in the recent auction will allow them to enhance their user experience further. It will compound woes for VIL, which continues to lag on investments [email protected] in network infrastructure given persisting delays in its capital raising plan. 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. India Telecommunication Services

Exhibit 1: Bharti continues to lead on net subscriber additions for the sixth month; Jio loses VLR subscriber base Total and VLR wireless subscribers, January 2020 onwards

Jan-20 Feb-20 Mar-20 Arp-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 Total subs (mn) Bharti 328 329 328 323 318 317 320 323 327 330 335 339 345 Voda Idea 329 326 319 315 310 305 301 300 295 293 290 284 286 R-Jio 377 383 388 389 393 397 401 403 404 406 408 409 411 BSNL 119 120 120 120 120 118 119 119 119 119 119 119 119 MTNL 3 3 3 3 3 3 3 3 3 3 3 3 3 Total 1,156 1,161 1,158 1,150 1,144 1,141 1,144 1,148 1,149 1,152 1,155 1,154 1,163 Net total adds (mn) Bharti 0.9 0.9 (1.3) (5.3) (4.7) (1.1) 3.3 2.9 3.8 3.7 4.4 4.1 5.9 Voda Idea (3.6) (3.5) (6.4) (4.5) (4.7) (4.8) (3.7) (1.2) (4.7) (2.7) (2.9) (5.7) 1.7 R-Jio 6.6 6.3 4.7 1.6 3.7 4.5 3.6 1.9 1.5 2.2 1.9 0.5 2.0 BSNL 1.2 0.4 0.1 (0.0) 0.2 (1.7) 0.4 0.2 0.1 (0.0) (0.0) (0.3) 0.1 MTNL (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) (0.0) Total 5.0 4.1 (2.8) (8.2) (5.6) (3.2) 3.5 3.7 0.7 3.2 3.4 (1.4) 9.6 VLR subs (mn) Bharti 313 314 315 307 307 311 310 313 316 320 323 329 336 Voda Idea 297 294 294 280 277 273 269 265 261 260 258 257 256 R-Jio 310 311 314 306 313 310 313 318 318 319 325 328 325 BSNL 65 66 66 64 64 63 63 62 62 61 62 61 61 MTNL 1 1 1 1 1 1 1 1 1 1 1 1 1 Total 986 987 989 958 961 958 956 957 958 961 968 975 979 Net VLR adds (mn) Bharti (1.7) 1.5 0.9 (8.0) (0.2) 3.7 (0.4) 2.3 3.8 3.0 3.9 5.5 6.9 Voda Idea (0.3) (2.8) (0.8) (14.1) (2.8) (3.7) (3.8) (4.5) (3.5) (1.2) (1.9) (1.5) (0.3) R-Jio 4.9 1.3 2.5 (7.2) 6.2 (2.1) 2.5 4.6 0.7 1.1 5.4 3.2 (3.4) BSNL 0.9 0.4 (0.2) (1.8) (0.3) (0.6) (0.4) (0.8) (0.1) (0.4) 0.1 (0.2) 0.1 MTNL 0.0 (0.0) (0.0) (0.2) (0.0) 0.0 (0.1) 0.0 (0.0) 0.0 (0.0) (0.0) 0.0 Total 3.9 0.4 2.2 (31.2) 2.9 (2.8) (2.1) 1.6 1.0 2.5 7.4 7.0 3.3 VLR ratio (%) Bharti 95.4 95.6 96.2 95.3 96.6 98.1 97.0 96.9 96.9 96.7 96.6 97.1 97.4 Voda Idea 90.4 90.5 92.0 88.9 89.3 89.5 89.3 88.2 88.4 88.8 89.0 90.3 89.6 R-Jio 82.3 81.3 80.9 78.8 79.6 78.2 78.1 78.9 78.8 78.6 79.6 80.2 79.0 BSNL 54.9 55.0 54.8 53.3 53.0 53.3 52.8 52.1 51.9 51.6 51.7 51.7 51.7 MTNL 27.4 26.8 25.4 19.7 19.3 19.7 18.1 19.4 19.4 19.5 19.5 19.5 19.9 Total 85.3 85.0 85.4 83.3 84.0 84.0 83.5 83.4 83.5 83.4 83.8 84.5 84.1

Source: TRAI, Kotak Institutional Equities

Exhibit 2: Bharti continues to gain market share Total wireless subscriber market share (%)

Bharti VIL Jio Others 100 10.6 10.6 10.6 10.7 10.8 10.7 10.7 10.7 10.7 10.6 10.6 10.6 10.5

80 32.6 33.0 33.5 33.8 34.3 34.8 35.0 35.1 35.2 35.3 35.3 35.4 35.3 60

40 28.4 28.0 27.6 27.4 27.1 26.7 26.3 26.1 25.7 25.4 25.1 24.6 24.6

20 28.4 28.4 28.3 28.1 27.8 27.8 28.0 28.1 28.4 28.7 29.0 29.4 29.6

0

Jul-20

Jan-21 Jan-20

Jun-20

Feb-20 Oct-20

Arp-20 Sep-20

Dec-20

Nov-20

Mar-20 Aug-20 May-20

Source: TRAI, Kotak Institutional Equities

12 KOTAK INSTITUTIONAL EQUITIES RESEARCH Telecommunication Services India

Exhibit 3: Bharti builds on its market leadership in VLR subscriber base VLR subscriber market share (%)

Bharti VIL Jio Others 100 6.6 6.7 6.6 6.7 6.6 6.6 6.6 6.5 6.4 6.4 6.4 6.3 6.3

80 31.4 31.5 31.7 32.0 32.5 32.4 32.7 33.2 33.2 33.2 33.5 33.6 33.2

60

30.1 29.8 29.7 29.2 28.8 28.5 28.2 27.6 27.3 27.1 26.7 26.3 26.2 40

20 31.7 31.9 31.9 32.1 32.0 32.4 32.5 32.7 33.0 33.3 33.4 33.7 34.3

0

Jul-20

Jan-20 Jan-21

Jun-20

Oct-20

Feb-20

Sep-20 Arp-20

Dec-20

Nov-20

Mar-20 Aug-20 May-20

Source: TRAI, Kotak Institutional Equities

Exhibit 4: VIL’s subscriber addition in January can be entirely attributed to surge in UP (W) Circle-wise addition in VIL’s wireless subscriber base, January 2020 onwards (mn)

Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 Net additions (mn) Andhra Pradesh (0.09) (0.21) (0.46) (0.43) (0.43) (0.31) (0.15) (0.14) (0.02) (0.10) (0.09) (0.29) (0.13) Assam (0.09) 0.12 (0.47) (0.01) (0.18) (0.10) (0.15) (0.03) (0.14) (0.08) (0.07) (0.08) (0.07) Bihar (0.61) (0.26) 0.03 (1.06) 0.44 (0.32) (0.70) 0.37 (0.46) (0.22) (0.16) (0.11) (0.14) Delhi (0.05) 0.10 (0.41) (0.35) (0.37) (0.20) (0.26) (0.09) 0.03 0.02 (0.08) (0.44) (0.07) Gujarat (0.15) (0.98) 0.70 (0.50) (0.41) (0.28) (0.26) 0.31 (0.47) (0.08) (0.21) (0.16) (0.02) Haryana (0.07) (0.03) (0.26) (0.14) (0.15) (0.14) (0.17) 0.04 (0.14) (0.01) (0.05) 0.03 0.01 Himachal Pradesh (0.03) (0.02) (0.03) (0.01) (0.03) (0.02) (0.02) 0.05 (0.08) (0.01) (0.01) (0.01) (0.01) J&K 0.09 (0.04) 0.00 0.01 (0.01) (0.02) (0.02) 0.01 (0.04) (0.01) (0.02) 0.01 (0.02) Karnataka (0.27) (0.10) (0.37) (0.24) (0.15) (0.05) (0.43) (0.01) (0.13) (0.12) (0.26) (0.31) (0.37) Kerala (0.03) (0.08) (0.40) (0.36) 0.02 (0.05) (0.10) 0.24 (0.36) (0.04) (0.01) 0.00 0.03 Kolkata (0.08) (0.03) (0.20) (0.08) (0.15) (0.12) 0.29 0.08 (0.20) (0.06) (0.09) (0.09) (0.09) Madhya Pradesh (0.78) (0.88) 0.61 (0.20) (0.22) (0.39) 0.26 (0.36) 0.13 (0.13) 0.07 (1.65) 0.04 Maharashtra (0.13) (0.51) (0.91) (1.13) (0.42) (0.65) (0.71) (0.10) (1.09) (0.31) (0.21) (0.65) (0.23) Mumbai (0.18) (0.16) (0.41) (0.23) (0.40) (0.14) (0.51) 0.05 (0.24) (0.27) (0.73) (0.91) (0.42) North East (0.05) (0.01) (0.14) (0.02) (0.03) (0.05) (0.09) 0.02 (0.02) (0.02) (0.02) (0.03) (0.02) Orissa (0.06) (0.03) (0.18) (0.08) (0.11) (0.12) (0.09) 0.03 (0.09) (0.02) (0.06) (0.08) (0.05) Punjab (0.10) (0.03) (0.25) (0.15) (0.15) (0.19) (0.12) (0.00) (0.04) (0.02) (0.01) 0.07 (0.09) Rajasthan (0.06) 0.04 (0.34) (0.26) (0.15) (0.26) (0.17) (0.03) (0.09) (0.19) (0.14) (0.09) (0.06) Tamil Nadu (0.20) 0.09 (0.71) (0.28) (0.41) (0.24) (0.25) 0.11 (0.04) 0.04 (0.10) (0.11) (0.05) UP (East) (0.22) (0.08) (0.65) 1.46 (0.54) (0.43) 0.92 (1.79) (0.58) (0.62) (0.41) (0.29) (0.17) UP (West) (0.08) (0.25) (0.72) (0.50) (0.54) (0.54) (0.44) 0.18 (0.75) (0.27) (0.09) (0.35) 3.75 West Bengal and A&N (0.37) (0.11) (0.74) 0.05 (0.35) (0.20) (0.56) (0.18) 0.16 (0.14) (0.14) (0.17) (0.11) Total (3.62) (3.47) (6.35) (4.52) (4.73) (4.82) (3.73) (1.23) (4.65) (2.66) (2.89) (5.69) 1.71

Source: TRAI, Kotak Institutional Equities

KOTAK INSTITUTIONAL EQUITIES RESEARCH 13 India Telecommunication Services

Exhibit 5: Bharti gains further on wireless broadband market as well Wireless broadband market subscribers (mn)

Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 EoP subs (mn) Bharti 142 144 146 142 144 149 153 156 163 168 172 176 182 Voda Idea 118 118 117 111 113 116 115 120 120 120 121 121 123 BSNL 17 17 16 14 14 15 15 16 17 18 18 19 19 R-Jio 377 383 388 389 393 397 401 403 404 406 408 409 411 Others 0 0 0 0 0 0 0 0 0 0 0 0 0 Total 654 661 668 657 664 678 685 695 705 713 720 724 734 Net adds (mn) Bharti 4.4 1.3 2.4 (3.8) 1.2 5.3 4.4 3.2 7.0 4.2 4.2 4.4 5.5 Voda Idea (0.5) 0.3 (0.8) (6.1) 1.7 3.4 (1.2) 4.6 (0.1) 0.6 0.5 (0.2) 1.9 BSNL 1.1 (0.1) (0.1) (2.9) 0.6 1.0 0.1 0.7 1.1 1.1 0.3 0.2 0.4 R-Jio 6.6 6.3 4.7 1.6 3.7 4.5 3.6 1.9 1.5 2.2 1.9 0.5 2.0 Others 0.0 (0.0) (0.0) (0.0) 0.1 (0.1) 0.0 (0.0) 0.0 (0.0) 0.0 (0.0) (0.0) Total 11.5 7.7 6.2 (11.2) 7.3 14.0 6.9 10.4 9.5 8.1 6.9 4.9 9.8

Source: TRAI, Kotak Institutional Equities

Exhibit 6: Jio and Bharti continue to gain steadily in fixed BB market Fixed broadband market subscribers (mn)

Jan-20 Feb-20 Mar-20 Apr-20 May-20 Jun-20 Jul-20 Aug-20 Sep-20 Oct-20 Nov-20 Dec-20 Jan-21 EoP subs (mn) BSNL + MTNL 8.9 8.8 8.7 8.6 8.5 8.5 8.4 8.4 8.3 8.3 8.2 8.2 8.1 Bharti 2.4 2.5 2.5 2.4 2.4 2.5 2.5 2.5 2.6 2.7 2.7 2.8 2.9 Atria Convergence 1.5 1.6 1.6 1.6 1.6 1.7 1.7 1.7 1.7 1.7 1.8 1.8 1.8 R-Jio 0.8 0.8 0.9 0.9 1.0 1.1 1.2 1.3 1.5 1.7 1.9 2.1 2.3 Others 5.4 5.5 5.5 5.5 5.8 6.1 6.4 6.6 7.0 7.2 7.3 7.5 7.6 Total 19.1 19.1 19.2 19.0 19.4 19.8 20.1 20.5 21.1 21.5 21.9 22.3 22.7 Net adds (mn) BSNL + MTNL (0.19) (0.13) (0.04) (0.14) (0.05) (0.05) (0.06) (0.02) (0.07) (0.07) (0.04) (0.06) (0.02) Bharti 0.01 0.02 0.02 (0.03) (0.03) 0.06 0.02 0.04 0.07 0.07 0.06 0.08 0.09 Atria Convergence 0.02 0.02 0.05 (0.02) 0.05 0.04 0.01 0.01 0.03 0.01 0.02 0.02 0.02 R-Jio (0.02) — 0.03 0.03 0.07 0.09 0.10 0.09 0.27 0.18 0.17 0.20 0.18 Others 0.12 0.08 0.05 0.00 0.32 0.30 0.24 0.22 0.35 0.20 0.17 0.16 0.11 Total (0.06) (0.01) 0.11 (0.16) 0.36 0.44 0.31 0.34 0.65 0.39 0.38 0.40 0.38

Source: TRAI, Kotak Institutional Equities

14 KOTAK INSTITUTIONAL EQUITIES RESEARCH Telecommunication Services India

Exhibit 7: Bharti has delivered superior performance on several parameters in the recent quarters India wireless KPIs, quarterly data

Dec-18 Mar-19 Jun-19 Sep-19 Dec-19 Mar-20 Jun-20 Sep-20 Dec-20 Wireless subs, EOP (mn) Bharti 284 283 281 279 283 284 280 294 308 Vodafone Idea 387 334 320 311 304 291 280 272 270 R-Jio 280 307 331 355 370 388 398 406 406 Wireless revenues (Rs bn) Bharti 102 106 109 110 112 130 129 138 148 Vodafone Idea 118 118 113 108 111 118 107 108 109 R-Jio 104 111 124 131 140 148 166 175 185 Wireless ARPU (Rs/sub/month) Bharti 104 123 129 128 135 154 157 162 166 Vodafone Idea 89 104 108 107 109 121 114 119 121 R-Jio 130 126 129 128 128 131 140 145 151 Wireless EBITDA (Rs bn) (a) Bharti 19 26 39 40 40 51 52 59 65 Vodafone Idea 11 16 37 33 34 44 41 42 43 R-Jio 41 43 47 51 56 62 70 75 81 Wireless costs (Rs bn) (a) Bharti 82 81 70 70 72 79 77 79 83 Vodafone Idea 106 102 76 75 77 74 66 66 66 R-Jio 63 68 77 80 84 87 96 100 104 Wireless EBITDA margin (%) Bharti 19.1 24.1 35.7 36.3 35.9 39.2 40.6 42.6 43.7 Vodafone Idea 9.7 13.5 32.4 30.9 30.8 37.3 38.4 38.5 39.3 R-Jio 39.0 39.0 37.7 39.1 40.0 41.6 42.3 42.9 43.9 Wireless EBIT (Rs bn) Bharti (19.0) (13.8) (12.4) (11.4) (8.2) 0.3 1.6 6.8 11.0 Vodafone Idea (36.4) (30.8) (24.8) (29.6) (24.6) (16.6) (18.8) (18.8) (15.4) R-Jio 23.7 25.8 30.1 33.6 37.9 40.1 42.7 46.3 52.0 Voice traffic (bn min) Bharti 703 731 737 717 759 822 820 861 925 Vodafone Idea 712 703 676 631 624 616 579 555 547 R-Jio 634 725 786 813 826 876 891 936 975 Data traffic (bn MB) Bharti 3,217 3,705 4,192 4,829 5,547 6,453 7,240 7,640 8,454 Vodafone Idea 2,705 2,947 3,222 3,492 3,790 4,090 4,523 4,340 4,489 R-Jio 8,847 9,789 11,162 12,308 12,646 13,486 15,043 15,606 16,241 Data traffiic share (of top-3 composite, %) Bharti 21.8 22.5 22.6 23.4 25.2 26.9 27.0 27.7 29.0 Vodafone Idea 18.3 17.9 17.3 16.9 17.2 17.0 16.9 15.7 15.4 R-Jio 59.9 59.5 60.1 59.7 57.5 56.1 56.1 56.6 55.7 Data subs (mn) Bharti 108 115 120 124 138 149 149 162 175 Vodafone Idea 146 146 143 140 142 140 136 138 138 R-Jio 280 307 331 355 370 388 398 406 406 Mobile broadband subs (mn) Bharti 100 107 113 120 137 144 145 158 169 Vodafone Idea 108 110 111 112 118 117 116 120 121 R-Jio 280 307 331 355 370 388 398 406 406 Data usage per data sub (MB/month) Bharti 10,452 11,093 11,882 13,177 14,078 14,988 16,215 16,363 16,727 Vodafone Idea 6,324 6,716 7,417 8,209 8,951 9,686 10,956 10,591 10,878 R-Jio 11,079 11,122 11,663 11,953 11,626 11,869 12,762 12,942 13,262 Blended churn (% per month) Bharti 7.3 2.8 2.6 2.1 2.6 2.6 2.2 1.7 1.9 Vodafone Idea 5.0 7.2 3.7 3.5 3.3 3.3 2.0 2.6 2.3 R-Jio 0.6 0.7 1.0 0.7 2.1 0.6 0.4 1.7 1.6

Source: Companies, Kotak Institutional Equities estimates

KOTAK INSTITUTIONAL EQUITIES RESEARCH 15 Kotak Institutional Equities: Valuation summary of KIE Universe stocks India

KOTAK INSTITUTIONAL EQUITIES RESEARCH EQUITIES INSTITUTIONAL KOTAK Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3M Company Rating 17-Mar-21 (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 Daily Summary Amara Raja Batteries SELL 866 770 (11) 148 2.0 171 37 46 51 (4) 25 11 23 19 17 12.9 10.5 9.2 3.6 3.1 2.7 16.3 17.9 17.4 1.1 1.3 1.5 14 Apollo Tyres REDUCE 224 210 (6) 142 2.0 638 5 13 17 (45) 183 29 49 17 13 7.0 6.6 5.4 1.3 1.2 1.1 2.8 7.1 8.7 0.6 1.2 1.2 47 Ashok Leyland REDUCE 117 125 7 344 4.7 2,936 (1) 2 7 (208) 230 284 NM 68 18 104.4 23.5 10.4 5.0 4.8 4.0 NM 7.2 25 0.0 0.4 1.7 57 Bajaj Auto BUY 3,570 4,400 23 1,033 14 289 158 191 222 (10) 21 16 23 19 16 17.2 13.4 11.1 4.7 4.3 3.9 22 24 25 2.7 3.2 3.7 51 Balkrishna Industries SELL 1,627 1,320 (19) 315 4.3 193 54 60 73 9 12 21 30 27 22 18.2 15.7 13.0 5.6 5.0 4.4 19.6 19.5 21 1.4 1.5 1.6 22 Bharat Forge SELL 591 375 (37) 275 3.8 466 (5) 11 19 (164) 319 76 NM 56 32 44.1 25.6 17.6 5.5 5.1 4.5 NM 9.5 15.2 0.0 0.5 0.5 27 CEAT ADD 1,532 1,500 (2) 62 0.9 40 99 107 124 59 8 16 15 14 12 8.0 7.2 6.4 1.9 1.7 1.5 13.1 12.7 13.1 0.8 0.8 0.8 11 Eicher Motors SELL 2,660 2,200 (17) 727 10.0 272 50 80 106 (25) 60 32 53 33 25 36.9 25.9 20.0 7.7 6.5 5.5 15.5 21 24 0.5 0.5 0.5 62 Endurance Technologies SELL 1,389 1,200 (14) 195 2.7 141 38 52 65 (7) 39 24 37 27 21 18.3 13.9 11.4 5.7 4.8 4.1 15.1 18.1 18.9 0.4 0.6 0.8 3 Escorts BUY 1,329 1,700 28 118 2.5 101 77 89 100 42 15 12 17 15 13 9.3 8.0 6.7 2.6 2.3 2.0 15.1 15.1 14.8 0.9 1.0 1.1 32 Exide Industries REDUCE 193 180 (6) 164 2.3 850 8 10 11 (17) 24 10 23 19 17 12.3 10.4 9.4 2.5 2.3 2.1 10.9 12.7 12.9 2.3 2.3 2.3 15 -

Hero Motocorp SELL 3,191 3,000 (6) 637 8.8 200 144 179 206 (10) 24 15 22 18 16 14.4 11.1 9.4 4.2 3.8 3.5 19.6 23 24 2.9 3.4 3.9 57 March 18, March2021 18, Mahindra CIE Automotive SELL 171 135 (21) 65 0.9 378 3 10 13 (70) 252 32 61 17 13 15.3 8.5 6.4 1.3 1.2 1.1 2.2 7.4 9.0 ——— 1 Mahindra & Mahindra BUY 837 1,000 19 1,040 14.3 1,138 33 48 55 38 45 16 25 18 15 15.6 11.9 10.0 2.6 2.3 2.1 10.5 14.1 14.5 0.4 0.9 1.0 74 Maruti Suzuki SELL 7,065 5,700 (19) 2,134 29.4 302 160 230 299 (15) 44 30 44 31 24 30.2 19.0 13.8 4.1 3.8 3.4 9.6 12.8 15.0 0.8 0.8 1.1 122

Motherson Sumi Systems ADD 221 200 (9) 696 9.6 3,158 4 9 11 (1) 139 23 60 25 21 14.4 7.4 5.8 5.6 4.3 3.3 9.7 19.3 18.3 0.4 0.6 0.7 57 MRF SELL 85,425 78,000 (9) 362 5.0 4 3,155 3,735 4,321 (6) 18 16 27 23 20 11.1 9.7 8.1 2.7 2.4 2.2 10.4 11.1 11.5 0.1 0.1 0.1 55 Schaeffler India SELL 5,235 4,050 (23) 164 2.3 31 93 149 179 (21) 60 20 56 35 29 28.2 19.1 15.7 5.2 4.7 4.2 9.5 14.1 15.1 ——— 1 SKF REDUCE 2,209 1,450 (34) 109 1.5 49 43 54 67 (26) 26 23 51 41 33 37.6 28.6 23.2 7.4 6.5 5.6 14.4 15.9 16.9 4.9 0.4 0.5 2 Tata Motors SELL 306 185 (40) 1,100 14.9 3,829 (12) 11 28 45 195 155 NM 28 11 7.2 5.5 4.0 2.2 2.0 1.7 NM 7.5 16.9 ——— 429 Timken SELL 1,256 830 (34) 94 1.3 75 22 36 43 (34) 65 20 58 35 29 33.3 21.4 17.8 6.9 5.9 5.0 11.1 18.1 18.4 0.1 0.1 0.1 1 TVS Motor SELL 582 360 (38) 277 3.8 475 11 17 21 (19) 65 22 55 33 27 21.8 16.3 14.0 7.1 6.2 5.4 13.4 19.9 21 0.8 0.7 0.9 29 Automobiles & Components Cautious 10,253 141.9 (1) 105 39 51 25 18 14.3 10.4 8.0 3.6 3.3 2.8 7.2 13.2 16.0 0.9 1.1 1.3 1,170

Banks AU Small Finance Bank SELL 1,170 720 (38) 365 5.0 304 39 27 34 75 (29) 23 30 43 35 ——— 7.1 5.9 5.0 23.7 14.0 14.8 ——— 18 Axis Bank BUY 728 675 (7) 2,230 30.7 3,060 23 42 51 294 85 22 32 17 14 ——— 2.3 2.1 1.9 7.5 12.2 13.3 0.5 0.9 1.1 182 Bandhan Bank ADD 336 375 12 541 7.5 1,610 16 20 25 (17) 30 21 21 17 14 ——— 3.3 2.7 2.2 15.3 16.9 17.2 ——— 59 Bank of Baroda ADD 75 80 7 387 5.3 4,627 8 17 21 572 120 18 9 4 4 ——— 0.6 0.6 0.5 5.4 11.1 12.0 2.1 4.7 5.5 72 Canara Bank REDUCE 150 115 (23) 247 3.4 1,647 11 9 18 150 (15) 99 14 16 8 ——— 0.7 0.7 0.7 3.4 2.7 5.2 ——— 65 City Union Bank REDUCE 169 160 (5) 125 1.7 737 8 8 11 21 2 32 22 21 16 ——— 2.5 2.3 2.0 10.4 9.8 11.9 0.8 0.8 1.1 8 DCB Bank BUY 110 150 36 34 0.5 310 11 12 16 (2) 15 33 10 9 7 ——— 1.1 1.0 0.8 9.9 10.4 12.5 1.0 1.1 1.5 3 Equitas Holdings BUY 87 100 16 30 0.4 342 8 8 16 30 5 97 11 10 5 ——— 1.0 1.0 0.8 9.2 8.8 15.4 ——— 3 Equitas Small Finance Bank BUY 57 50 (13) 65 0.9 1,138 3 4 5 27 23 36 20 16 12 ——— 2.0 1.8 1.6 11.0 11.5 13.8 ——— - Federal Bank BUY 80 90 12 160 2.2 1,993 7 9 12 (3) 14 45 11 9 6 ——— 1.1 1.0 0.9 9.9 10.5 13.9 2.1 2.4 3.5 34 HDFC Bank ADD 1,495 1,550 4 8,241 113.6 5,483 55 65 76 16 18 17 27 23 20 ——— 4.3 3.8 3.3 16.6 17.2 17.6 0.7 0.8 1.0 202 ICICI Bank BUY 590 650 10 4,076 56.2 6,893 25 31 35 102 26 13 24 19 17 ——— 3.0 2.7 2.4 13.1 14.0 14.2 0.8 1.1 1.2 204 IndusInd Bank ADD 1,009 950 (6) 764 10.5 756 34 63 81 (47) 85 29 30 16 13 ——— 2.0 1.8 1.6 7.1 11.4 13.2 0.5 0.9 1.2 163 Karur Vysya Bank BUY 59 65 10 47 0.7 799 4 7 11 34 84 58 15 8 5 ——— 0.9 0.8 0.7 4.7 8.2 12.1 1.7 3.2 5.0 3 Punjab National Bank REDUCE 38 36 (6) 402 5.5 10,481 2 5 6 369 106 29 16 8 6 ——— 0.7 0.7 0.6 3.4 5.7 6.9 ——— 95 RBL Bank BUY 223 270 21 134 1.8 597 10 24 31 (2) 146 29 23 9 7 ——— 1.1 1.0 0.9 5.0 10.8 12.7 0.7 1.6 2.1 63 SBI Cards and Payment Services ADD 978 1,030 5 920 12.7 939 13 20 30 (2) 53 52 75 49 32 ——— 14.3 11.2 8.5 20.7 25 30 0.1 0.1 0.2 22 State Bank of India BUY 368 450 22 3,286 45.3 8,925 23 36 45 45 52 26 16 10 8 ——— 1.7 1.4 1.2 8.6 11.9 13.2 0.1 0.1 0.1 254 Ujjivan Financial Services BUY 230 345 50 28 0.4 121 34 44 - 25 32 (100) 7 5 - ——— 1.1 0.9 — 17.0 19.3 NM 1.8 2.6 0.0 3 Ujjivan Small Finance Bank ADD 33 37 12 57 0.8 1,928 (0) 2 3 (118) 575 85 NM 21 11 ——— 2.1 1.9 1.6 NM 9.2 14.8 0.0 0.0 0.0 2 Union Bank REDUCE 35 27 (23) 225 3.1 6,407 3 1 5 136 (83) 789 12 69 8 ——— 0.6 0.6 0.6 3.4 0.6 4.9 1.3 0.2 1.9 8 YES Bank SELL 15 11 (27) 378 5.2 25,055 (0) (1) (0) 96 (96) 74 NM NM NM ——— 1.4 1.5 1.5 NM NM NM 0.0 0.0 0.0 40 Banks Attractive 22,742 313.5 122 37 26 24 17 14 2.0 1.8 1.6 8.4 10.5 11.9 0.6 0.7 0.9 1,503

Source: Company, Bloomberg, Kotak Institutional Equities estimates

16 KOTAK INSTITUTIONAL EQUITIES RESEARCH 16

Kotak Institutional Equities: Valuation summary of KIE Universe stocks 17 Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3M

Company Rating 17-Mar-21 (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) Building Products Astral Poly Technik SELL 2,456 985 (60) 370 5.1 151 24 26 32 46 10 21 102 93 77 61.4 54.7 45.3 20.4 17.3 14.8 22 20 21 0.1 0.2 0.3 8 Building Products Cautious 370 5.1 46 10 21 102 93 77 61.4 54.7 45.3 20.3 17.3 14.8 19.9 18.6 19.2 0.1 0.2 0.3 8 Capital goods ABB SELL 1,440 1,170 (19) 305 4.2 212 9 22 28 (50) 146 29 164 67 52 108.1 45.4 34.7 8.5 7.8 7.1 5.2 12.1 14.3 0.3 0.4 0.5 4 Ashoka Buildcon BUY 110 145 32 31 0.4 281 12 12 13 (14) 1 9 9 9 8 7.4 6.3 5.3 1.1 1.0 0.9 12.2 11.2 11.2 1.7 1.7 1.9 3 Bharat Electronics BUY 134 140 5 326 4.5 2,437 7 8 8 (1) 7 3 18 17 16 11.5 10.3 9.5 2.9 2.7 2.5 17.0 16.6 15.7 2.1 2.2 2.3 32 BHEL SELL 50 31 (38) 174 2.4 3,482 (4) 2 3 (4) 149 42 NM 23 16 (10.3) 9.5 7.3 0.6 0.6 0.6 NM 2.6 3.7 (3.9) 1.7 2.2 51 Carborundum Universal ADD 497 450 (9) 94 1.3 189 15 19 22 5 23 19 33 27 22 19.5 15.4 12.9 4.6 4.1 3.7 14.7 16.3 17.3 0.8 1.0 1.2 2 Cochin Shipyard BUY 363 520 43 48 0.7 132 35 43 43 (27) 20 1 10 9 8 5.3 5.2 4.8 1.2 1.1 1.0 12.0 13.4 12.5 3.3 3.5 3.8 3 Cummins India REDUCE 844 900 7 234 3.2 277 25 32 39 (4) 32 22 34 26 21 35.2 25.1 19.8 5.4 5.1 4.7 15.9 19.9 23 1.6 2.1 2.6 19 Dilip Buildcon BUY 617 600 (3) 84 1.2 137 26 46 63 (14) 75 39 24 14 10 7.9 6.3 5.3 2.1 1.8 1.5 9.4 14.6 17.2 0.1 0.1 0.2 3 IRB Infrastructure BUY 113 145 29 40 0.5 351 7 10 11 (65) 45 7 16 11 10 6.3 5.7 4.6 0.6 0.6 0.5 3.7 5.3 5.4 3.4 1.3 2.0 2 Kalpataru Power Transmission BUY 378 500 32 56 0.8 153 26 38 46 2 46 20 15 10 8 5.3 4.5 3.8 1.5 1.2 1.1 11.0 13.5 13.7 2.4 1.1 1.4 2 KEC International BUY 457 410 (10) 117 1.6 257 22 29 36 1 31 24 21 16 13 11.5 9.1 7.5 3.6 3.0 2.5 18.7 21 21 0.5 0.7 0.8 2 L&T BUY 1,438 1,720 20 2,019 27.8 1,403 50 81 99 (21) 60 24 29 18 14 20.0 14.6 13.1 2.9 2.6 2.4 11.1 15.5 17.3 1.1 1.7 2.1 91 Siemens SELL 1,821 1,540 (15) 648 8.9 356 37 43 50 73 17 17 50 42 36 34.7 30.4 25.6 6.1 5.6 5.0 13.0 13.7 14.6 0.8 0.7 0.8 11 Thermax SELL 1,367 1,080 (21) 163 2.2 113 25 33 43 34 29 32 54 42 32 38.1 30.5 23.6 38.1 30.5 23.6 9.3 11.6 14.5 0.9 1.2 1.5 2 Capital goods Attractive 4,340 59.8 (15) 67 21 35 21 17 2.8 2.5 2.3 7.9 12.2 13.5 0.9 1.4 1.7 228 Commercial & Professional Services SIS BUY 412 460 12 61 0.8 149 23 21 25 51 (9) 19 18 20 17 12.0 11.1 9.7 3.6 3.1 2.6 22 16.7 17.0 0.3 0.3 0.3 1 TeamLease Services ADD 3,373 3,775 12 58 0.8 17 53 84 113 161 56 35 63 40 30 56.5 35.3 26.3 8.7 7.2 5.8 14.8 19.4 21 — — — 2 Commercial & Professional Services Attractive 119 1.6 66 5 24 27 26 21 19.0 16.2 13.6 5.0 4.2 3.5 18.2 16.1 16.8 0.1 0.1 0.2 3 Commodity Chemicals Asian Paints SELL 2,423 2,550 5 2,324 32.0 959 32 41 48 19 26 19 75 60 50 48.3 40.1 34.3 19.7 16.8 14.4 28 30 31 0.6 0.8 1.0 92 Berger Paints SELL 715 600 (16) 694 9.6 971 8 10 12 11 34 24 95 71 57 59.3 46.0 37.9 22.4 19.1 16.4 25 29 31 0.3 0.5 0.7 15 Kansai Nerolac REDUCE 555 610 10 299 4.1 539 10 12 15 1 21 26 56 46 36 35.8 30.3 24.3 7.2 6.6 6.0 13.6 15.1 17.3 0.5 0.8 1.0 3 Tata Chemicals ADD 733 540 (26) 187 2.6 255 17 33 38 (46) 94 15 43 22 19 11.6 8.4 7.3 1.4 1.4 1.3 3.4 6.3 6.9 0.8 1.6 1.8 64 Commodity Chemicals Neutral 3,504 48.3 4 33 20 73 55 46 41.2 33.0 28.1 10.9 9.8 8.8 14.9 17.8 19.2 0.6 0.8 1.0 173 Construction Materials ACC REDUCE 1,728 1,775 3 324 4.5 188 75 95 97 4 26 2 23 18 18 10.7 9.1 8.1 2.6 2.3 2.1 11.7 13.4 12.5 0.8 1.4 1.4 30 Ambuja Cements ADD 281 300 7 558 7.7 1,986 13 13 16 28 (3) 20 21 22 18 9.1 7.6 6.2 2.5 2.2 2.0 11.3 10.8 11.9 6.4 0.9 1.1 31 Dalmia Bharat BUY 1,563 1,500 (4) 292 4.0 187 40 48 68 189 20 41 39 32 23 11.5 10.0 8.1 2.7 2.5 2.2 7.0 8.0 10.3 — — — 4 Grasim Industries ADD 1,367 1,375 1 899 12.4 657 64 93 114 21 46 23 21 15 12 10.1 7.3 6.0 1.5 1.4 1.2 7.2 9.6 10.7 0.2 0.4 0.5 37 India Daily Summary Daily Summary India J K Cement ADD 2,870 2,300 (20) 222 3.1 77 87 127 140 35 47 10 33 23 20 15.7 12.3 11.5 6.1 4.9 4.0 20 24 22 0.3 0.3 0.3 6 JK Lakshmi Cement BUY 421 400 (5) 50 0.7 118 26 30 35 10 16 16 16 14 12 7.0 6.6 6.3 2.5 2.2 1.9 16.7 16.6 16.7 0.9 1.1 1.2 3 Orient Cement ADD 101 90 (10) 21 0.3 205 8 6 9 82 (18) 37 13 16 12 6.1 6.7 6.0 1.7 1.6 1.4 13.4 10.1 12.7 2.0 2.0 2.0 1 Shree Cement SELL 26,900 18,250 (32) 971 13.4 36 595 800 933 37 34 17 45 34 29 24.8 19.4 16.6 6.6 5.7 4.8 15.6 18.1 18.0 0.4 0.4 0.4 23 The Ramco Cements SELL 953 750 (21) 225 3.1 236 34 36 46 34 4 30 28 27 21 16.7 14.5 11.5 3.9 3.5 3.0 15.1 13.7 15.6 0.4 0.4 0.5 10 UltraTech Cement ADD 6,519 5,800 (11) 1,882 25.9 289 187 243 292 41 30 20 35 27 22 18.1 14.5 12.4 4.3 3.7 3.2 13.0 14.8 15.4 0.2 0.3 0.4 62 Construction Materials Attractive 5,443 75.0 32 27 20 29 23 19 13.8 10.9 9.2 3.1 2.7 2.4 10.4 11.8 12.6 0.9 0.5 0.5 206

Source: Company, Bloomberg, Kotak Institutional Equities estimates KOTAK INSTITUTIONAL EQUITIES EQUITIES INSTITUTIONAL KOTAK -

March 18, March2021 18, RESEARCH

KOTAK INSTITUTIONAL EQUITIES RESEARCH 17

Kotak Institutional Equities: Valuation summary of KIE Universe stocks India

Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3M

KOTAK INSTITUTIONAL EQUITIES RESEARCH EQUITIES INSTITUTIONAL KOTAK Company Rating 17-Mar-21 (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 387 285 (26) 243 3.3 627 8 10 11 1 24 15 49 39 34 36 30 26 13.4 10.6 8.4 31 30 28 0.8 0.6 0.6 15 Daily Summary Havells India SELL 1,062 820 (23) 665 9.2 626 18 21 24 49 17 18 61 52 44 41 36 30 13.4 11.7 10.1 24 24 25 0.6 0.7 0.8 50 Page Industries REDUCE 28,600 28,500 (0) 319 4.4 11 308 504 594 0 63 18 93 57 48 60 39 33 35.4 29.0 24.4 40 56 55 0.9 1.2 1.5 23 Polycab ADD 1,352 1,300 (4) 202 2.8 149 49 57 63 (4) 16 10 27 24 21 18 15 13 4.5 3.9 3.4 17.7 17.8 16.8 0.5 0.6 0.6 9 TCNS Clothing Co. REDUCE 497 390 (22) 31 0.4 66 (7) 11 15 (162) 269 37 NM 44 32 101 15 12.2 5.0 4.3 3.6 NM 10.4 12.2 — — — 1 Voltas SELL 1,000 785 (22) 331 4.6 331 15 23 28 (10) 57 24 69 44 35 60 36 29 7.2 6.4 5.7 10.8 15.5 17.1 0.4 0.6 0.7 31 Whirlpool SELL 2,390 1,930 (19) 303 4.2 127 26 48 63 (30) 85 30 91 49 38 57 34 26 11.0 9.9 8.9 12.5 21 25 0.3 0.8 1.3 5 Consumer Durables & Apparel Cautious 2,093 28.9 1 38 19 61 44 37 41 31 25 10.4 9.0 17.1 20 21 0.6 0.7 134 Consumer Staples Bajaj Consumer Care ADD 258 300 16 38 0.5 148 15 16 18 22 7 8 17 16 15 13.4 12.2 10.8 5.0 4.3 3.8 32 29 27 3.1 3.1 3.5 6 Britannia Industries ADD 3,468 3,875 12 835 11.5 240 79 73 86 33 (6) 17 44 47 40 33 34 30 26.4 18.0 16.7 49 45 43 3.1 2.0 2.2 35

Colgate-Palmolive (India) ADD 1,595 1,680 5 434 6.0 272 35 38 43 24 9 13 45 42 37 29.7 27.3 24.3 26.4 25.3 24.0 59 62 67 2.1 2.3 2.6 14 -

Dabur India ADD 527 555 5 931 12.8 1,767 10 11 13 13 13 14 54 47 41 44 38 33 12.8 11.6 10.5 25 26 27 1.1 1.3 1.5 27 March2021 18, Godrej Consumer Products ADD 661 795 20 676 9.3 1,022 16 18 21 18 12 15 41 36 32 28 25 22 7.4 6.7 6.1 19.5 19.4 20 1.1 1.4 1.7 17 Hindustan Unilever ADD 2,226 2,625 18 5,231 72.1 2,343 34 41 49 9 20 20 65 55 46 45 38 32 12.2 11.8 11.4 31 22 25 1.5 1.7 2.1 75 ITC BUY 211 265 26 2,592 35.7 12,318 10 12 13 (10) 19 8 20 17 16 14.6 12.0 11.0 4.0 3.9 3.8 19.1 22 24 4.7 5.0 5.4 118

Jyothy Laboratories ADD 147 170 16 54 0.7 367 6 6 7 28 4 14 24 23 21 17.3 16.5 14.7 4.1 3.8 3.6 17.3 16.9 18.0 2.4 2.7 3.1 1 Marico ADD 391 450 15 504 7.0 1,290 9 10 11 12 12 11 43 38 35 31 27 24 15.1 13.9 12.7 37 38 38 1.8 2.0 2.2 14 Nestle India ADD 16,468 17,150 4 1,588 21.9 96 216 251 295 6 16 17 76 66 56 50 44 38 78.6 53.0 38.4 105 97 80 1.2 0.9 1.1 31 Tata Consumer Products ADD 603 610 1 556 7.7 922 10 12 14 25 19 21 60 51 42 34 30 26 3.8 3.7 3.5 6.5 7.4 8.5 0.6 0.7 0.8 37 United Breweries ADD 1,187 1,375 16 314 4.3 264 4 26 33 (74) 513 28 285 47 36 83 26 21 8.7 7.4 6.3 3.1 17.2 18.8 0.1 0.5 0.7 11 United Spirits ADD 538 680 26 391 5.4 727 6 14 17 (48) 136 22 91 38 31 41 24 20 9.0 7.3 6.2 10.3 21 21 — — 0.9 22 Varun Beverages BUY 1,007 1,100 9 291 4.0 289 14 29 36 (16) 110 25 73 35 28 27 16 14 8.2 6.5 5.4 11.5 21 21 0.1 0.3 0.3 5

Consumer Staples Attractive 14,433 199.0 2 20 14 44 37 32 31 26 23 8.9 8.3 7.8 20 23 24 2.0 2.1 2.4 414 Diversified Financials Aavas Financiers ADD 2,209 2,400 9 173 2.4 78 33 44 55 5 32 26 67 51 40 — — — #DIV/0! #DIV/0! #DIV/0! 11.6 13.5 14.7 0.0 0.0 0.0 3 Aditya Birla Capital ADD 126 145 15 304 4.2 2,414 4 6 8 4 36 43 30 22 15 — — — #DIV/0! #DIV/0! #DIV/0! 7.8 9.7 12.4 44.8 49.4 55.9 8 Bajaj Finance SELL 5,358 4,000 (25) 3,228 44.5 600 77 144 191 (13) 87 33 70 37 28 — — — 8.8 7.3 5.9 13.4 21 23 0.1 0.3 0.4 224 Bajaj Finserv ADD 9,525 10,050 6 1,516 20.9 159 276 437 566 30 58 29 35 22 17 — — — 4.8 4.1 3.5 14.0 20 22 0.1 0.1 0.1 85 Cholamandalam BUY 528 540 2 433 6.0 820 24 33 35 88 35 7 22 16 15 — — — 4.6 3.7 3.1 22 24 21 0.5 0.7 0.7 41 HDFC ADD 2,516 2,750 9 4,537 62.5 1,789 66 73 87 (36) 11 20 38 35 29 — — — 4.1 3.8 3.5 11.7 11.5 12.8 0.9 1.0 1.2 161 HDFC AMC SELL 2,914 2,175 (25) 621 8.6 213 63 72 82 7 15 13 46 40 36 — — — 13.4 11.6 10.1 31 31 30 1.2 1.4 1.5 15 IIFL Wealth ADD 1,185 1,250 5 104 1.4 90 38 45 58 61 17 30 31 27 20 — — — 4.0 3.8 3.5 12.1 14.6 17.9 6.8 2.4 2.9 1 L&T Finance Holdings ADD 102 105 3 251 3.5 2,005 5 10 12 (45) 104 27 22 11 8 — — — 1.3 1.2 1.1 6.3 11.9 13.5 1.4 1.5 1.5 29 LIC Housing Finance ADD 417 430 3 210 2.9 505 53 71 79 12 33 12 8 6 5 — — — 1.3 1.1 0.9 14.0 16.5 16.1 2.2 2.9 3.2 40 Mahindra & Mahindra Financial BUY 203 195 (4) 251 3.5 1,232 8 14 18 (49) 89 25 27 14 11 — — — 1.8 1.7 1.5 7.0 11.0 12.6 0.6 1.4 1.8 29 Muthoot Finance REDUCE 1,279 1,250 (2) 513 7.1 401 90 106 112 20 17 6 14 12 11 — — — 3.6 2.9 2.4 28 27 23 1.4 1.7 1.8 34 Shriram City Union Finance BUY 1,476 1,500 2 97 1.3 66 145 180 193 (5) 24 7 10 8 8 — — — 1.3 1.1 1.0 12.5 13.9 13.3 1.3 1.8 2.0 1 Shriram Transport BUY 1,322 1,525 15 334 4.6 253 103 134 161 (7) 30 20 13 10 8 — — — 1.6 1.4 1.2 13.1 14.7 15.5 1.2 1.5 1.8 70 Diversified Financials Attractive 12,637 174.2 (10) 36 19 33 24 20 4.0 3.5 3.2 12.1 14.6 15.8 0.7 0.8 0.9 744

Source: Company, Bloomberg, Kotak Institutional Equities estimates

18 KOTAK INSTITUTIONAL EQUITIES RESEARCH 18

Kotak Institutional Equities: Valuation summary of KIE Universe stocks 19 Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3M

Company Rating 17-Mar-21 (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 612 815 33 81 1.1 133 96 106 117 (3) 11 10 6 6 5 5.1 4.2 3.8 0.6 0.6 0.5 11.2 10.3 10.4 7.3 2.3 2.7 6 JSW Energy REDUCE 84 70 (16) 137 1.9 1,640 6 6 7 (11) 0 24 15 15 12 7.1 6.3 5.8 1.1 1.0 0.9 7.6 7.1 8.2 — — — 6 NHPC ADD 24 27 12 242 3.3 10,045 4 3 4 26 (2) 1 7 7 7 10.1 9.5 8.9 0.7 0.7 0.7 11.1 10.4 10.0 8.2 8.2 8.3 3 NTPC BUY 107 125 17 1,033 14.2 9,697 15 15 17 32 4 8 7 7 6 8.5 6.5 5.5 0.9 0.8 0.7 12.2 11.8 11.8 3.7 4.3 4.7 44 Power Grid BUY 220 240 9 1,153 15.9 5,232 24 27 28 21 9 5 9 8 8 7.1 6.3 5.8 1.6 1.5 1.4 19.0 19.0 18.1 5.5 6.0 6.3 39 Tata Power ADD 103 95 (8) 330 4.6 3,196 4 5 6 (20) 46 12 29 20 18 9.3 9.4 8.7 1.5 1.4 1.3 5.7 7.3 7.6 — — — 65 Electric Utilities Attractive 2,977 41.0 21 7 7 9 8 8 1.1 1.0 0.9 12.5 12.4 12.2 4.3 4.6 4.8 164 Fertilizers & Agricultural Chemicals Bayer Cropscience SELL 5,132 4,250 (17) 231 3.2 45 126 158 179 (2) 25 13 41 33 29 28 23 20 7.9 6.6 5.6 21 22 21 0.5 0.6 0.7 2 Dhanuka Agritech SELL 723 680 (6) 34 0.5 48 43 41 45 43 (3) 10 17 17 16 12.7 12.6 11.0 4.0 3.5 3.0 26 21 20 1.5 1.7 2.2 1 Godrej Agrovet SELL 481 455 (5) 92 1.3 192 15 18 21 29 24 15 32 26 23 18 15 12 3.8 3.4 3.0 12.2 13.7 14.2 1.1 1.3 1.5 1 PI Industries SELL 2,242 1,825 (19) 340 4.7 148 51 61 73 53 20 20 44 37 31 31 25 20 6.4 5.7 4.9 19.1 16.5 17.2 0.3 0.5 0.6 12 Rallis India ADD 258 310 20 50 0.7 195 12 15 18 30 26 21 22 17 14 15.5 12.2 10.0 3.2 2.8 2.4 15.3 16.9 17.8 1.1 1.2 1.3 3 UPL SELL 609 430 (29) 465 6.4 765 34 39 43 46 15 10 18 16 14 8.7 7.9 7.1 2.6 2.3 2.0 15.0 15.4 15.2 1.4 1.7 1.8 74 Fertilizers & Agricultural Chemicals Cautious 1,212 16.7 38 18 13 26 22 20 12.9 11.4 10.1 3.9 3.4 3.0 14.8 15.4 15.3 0.9 1.1 1.2 93 Gas Utilities GAIL (India) BUY 138 160 16 624 8.6 4,510 10 12 12 (24) 19 4 14 12 11 10.9 8.5 7.8 1.3 1.3 1.2 10.0 11.1 10.9 2.9 3.6 4.3 53 GSPL SELL 265 200 (24) 149 2.1 564 13 12 8 (23) (11) (32) 20 22 33 9.0 9.6 12.9 2.0 1.9 1.8 10.6 8.7 5.6 0.7 0.9 0.8 5 Indraprastha Gas ADD 501 575 15 351 4.8 700 16 23 26 (4) 43 11 31 22 20 22.0 15.7 13.8 6.0 5.0 4.3 21 25 24 0.6 1.0 1.4 27 Mahanagar Gas BUY 1,145 1,350 18 113 1.6 99 64 98 104 (14) 52 6 18 12 11 11.2 7.4 6.6 3.4 2.9 2.5 20 27 24 2.2 3.4 4.1 15 Petronet LNG BUY 229 300 31 343 4.7 1,500 20 21 23 16 4 9 11 11 10 6.2 5.9 5.5 2.9 2.8 2.7 27 26 28 6.7 7.4 8.6 18 Gas Utilities Attractive 1,581 21.8 (12) 17 5 16 13 13 10.4 8.6 8.0 2.1 2.0 1.8 13.5 14.6 14.3 2.9 3.6 4.3 117 Health Care Services Apollo Hospitals ADD 2,992 2,860 (4) 430 5.9 144 5 48 65 (71) 785 36 554 63 46 39.4 23.7 19.8 9.4 8.7 7.8 2.0 14.4 17.8 0.1 0.6 0.9 46 Aster DM Healthcare BUY 137 220 60 69 0.9 500 3 10 12 (52) 245 21 48 14 12 8.6 5.9 5.1 2.0 1.8 1.6 4.3 13.6 14.5 — — — 1 Dr Lal Pathlabs SELL 2,465 1,520 (38) 205 2.8 83 33 40 43 22 23 7 75 61 57 47.1 37.9 35.2 17.4 15.0 13.1 25 26 25 0.6 0.7 0.8 7 HCG BUY 173 175 1 22 0.3 143 (8) (2) (2) 30 71 21 NM NM NM 17.0 9.7 8.5 2.6 2.7 2.7 NM NM NM — — — 0 Metropolis Healthcare SELL 1,868 1,510 (19) 95 1.3 51 36 41 46 20 14 11 52 45 41 32.3 27.1 24.0 14.7 12.3 10.3 31 30 27 0.6 0.7 0.7 3 Narayana Hrudayalaya BUY 412 540 31 84 1.2 204 (3) 10 13 (152) 421 31 NM 43 33 58.9 16.3 13.6 7.8 6.6 5.5 NM 16.8 18.4 — — — 2 Health Care Services Attractive 906 12.5 (47) 281 25 183 48 38 29.2 18.5 15.9 7.7 6.9 6.1 4.2 14.4 15.9 0.2 0.5 0.7 59 Hotels & Restaurants Jubilant Foodworks BUY 2,870 3,150 10 379 5.2 132 17 43 54 (26) 144 26 164 67 53 46.5 29.2 24.4 29.9 21.6 16.8 19.2 37 36 0.2 0.5 0.6 45

Lemon Tree Hotels REDUCE 38 39 2 30 0.4 790 (2) (0) 1 (1,176) 72 237 NM NM 64 70.5 33.6 13.1 4.3 4.2 3.9 NM NM 6.3 — (1.6) (0.1) 2 Daily Summary India Hotels & Restaurants Attractive 409 5.6 (64) 386 44 376 77 54 48.5 29.6 22.1 20.8 16.5 13.5 5.5 21 25 0.2 0.3 0.6 47

Source: Company, Bloomberg, Kotak Institutional Equities estimates

KOTAK INSTITUTIONAL EQUITIES EQUITIES INSTITUTIONAL KOTAK -

March 18, March2021 18, RESEARCH

KOTAK INSTITUTIONAL EQUITIES RESEARCH 19

Kotak Institutional Equities: Valuation summary of KIE Universe stocks India

Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3M

KOTAK INSTITUTIONAL EQUITIES RESEARCH EQUITIES INSTITUTIONAL KOTAK Company Rating 17-Mar-21 (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) Insurance

HDFC Life Insurance ADD 690 705 2 1,394 19.2 2,010 8 10 12 18 27 24 91 72 58 — — — 18.1 16.2 14.4 21 24 26 0.3 0.3 0.4 36 Daily Summary ICICI Lombard SELL 1,470 1,075 (27) 668 9.2 454 33 34 38 26 3 13 45 43 38 — — — 8.9 7.8 6.7 22 19.9 18.8 0.2 0.4 0.5 16 ICICI Prudential Life BUY 427 560 31 613 8.4 1,436 9 11 13 16 29 16 49 38 33 — — — 7.2 6.2 5.4 15.4 17.4 17.5 0.3 0.4 0.5 19 Max Financial Services BUY 862 1,000 16 298 4.1 343 10 27 16 (6) 180 (40) 90 32 54 — — — — — — 13.5 38 17.5 0.1 0.9 0.4 23 SBI Life Insurance BUY 889 1,250 41 889 12.3 1,001 13 16 19 (7) 23 15 67 55 48 — — — 9.8 8.5 7.4 15.5 16.6 16.6 0.2 0.3 0.3 44 Insurance Attractive 3,861 53.2 13 33 9 65 49 45 10.9 8.8 8.2 16.7 17.9 18.1 0.2 0.3 0.3 138 Internet Software & Services Info Edge SELL 4,762 3,170 (33) 613 8.5 128.3 22 43 53 (19) 98 23 219 111 90 188.5 103.5 82.2 13.5 12.4 11.2 8.0 11.7 13.1 0.1 0.2 0.3 60 Just Dial SELL 861 570 (34) 53 0.7 61.8 27 30 36 (35) 9 20 31 29 24 24.1 22.6 19.4 4.3 3.7 3.2 13.4 13.9 14.4 — — — 29 Internet Software & Services Cautious 667 9.2 (25) 64 22 149 90 74 130.9 84.8 69.1 11.6 10.5 9.4 7.8 11.6 12.7 0.1 0.2 0.3 89 IT Services

HCL Technologies ADD 987 1,120 13 2,680 36.9 2,716 50 53 58 21 7 10 20 19 17 12.6 11.4 10.1 4.4 3.8 3.2 25 22 20 1.0 1.4 1.4 97 -

Infosys BUY 1,387 1,530 10 5,908 81.5 4,250 46 52 60 17 14 15 30 27 23 20.3 17.9 15.5 8.0 7.1 6.3 28 28 29 1.9 2.2 2.5 163 March2021 18, L&T Infotech REDUCE 4,048 3,810 (6) 707 9.7 176 108 128 151 25 19 17 37 32 27 25.1 22.4 19.2 10.7 8.7 7.1 32 31 29 0.8 0.9 1.0 17 L&T Technology Services ADD 2,589 2,700 4 272 3.7 106 64 89 106 (18) 39 20 41 29 24 25.5 19.1 15.9 8.4 7.0 5.8 22 26 26 0.6 0.9 1.0 13 Mindtree SELL 1,999 1,410 (29) 329 4.5 165 67 76 82 74 15 7 30 26 24 19.5 17.6 16.2 8.5 7.0 5.8 31 29 26 1.0 1.1 1.2 27

Mphasis REDUCE 1,684 1,480 (12) 315 4.3 187 66 76 85 5 14 12 25 22 20 16.6 14.4 12.7 4.9 4.4 3.9 20 21 21 2.1 2.1 2.1 11 TCS REDUCE 3,113 3,070 (1) 11,515 158.7 3,744 89 106 119 4 19 12 35 29 26 23.7 20.3 18.2 12.8 10.8 10.0 38 40 40 1.0 2.1 3.1 158 Tech Mahindra BUY 1,020 1,135 11 889 12.2 880 52 60 68 13 16 13 20 17 15 11.7 10.1 8.7 3.7 3.3 3.0 19.8 21 21 2.2 2.3 2.5 60 Wipro ADD 420 450 7 2,299 31.7 5,662 19 19 22 12 3 16 23 22 19 14.0 13.0 11.1 4.4 3.8 3.3 19.3 18.4 18.5 0.5 1.2 1.2 98 IT Services Attractive 24,914 343.5 11 13 13 29 26 23 19.2 16.9 14.9 7.7 6.7 5.9 27 26 26 1.2 1.9 2.4 645 Media DB Corp. REDUCE 95 81 (14) 17 0.2 175 5 14 14 (66) 167 1 18 7 7 5.9 3.0 3.2 1.0 1.0 1.0 5.4 14.3 14.6 2.1 12.7 13.8 1

Jagran Prakashan REDUCE 58 37 (36) 16 0.2 281 4 7 8 (44) 87 NA 15 8 NA 4.1 2.6 NA 0.8 0.8 NA 5.7 10.3 11.5 3.4 8.6 8.6 1 PVR BUY 1,418 1,650 16 86 1.2 55 (93) 40 60 (420) 143 53 NM 36 23 (23.9) 13.6 10.6 3.7 3.4 3.0 NM 10.0 13.7 (0.7) 0.3 0.4 36 Sun TV Network REDUCE 457 465 2 180 2.5 394 38 40 42 7 7 5 12 11 11 8.3 7.5 7.1 3.0 2.9 2.8 26 26 26 5.5 6.0 6.6 24 Zee Entertainment Enterprises REDUCE 203 240 18 195 2.7 960 12 17 18 8 38 11 17 12 11 10.1 7.3 6.3 1.9 1.8 1.6 12.0 15.1 15.1 1.7 2.0 2.2 62 Media Cautious 494 6.8 (24) 65 11 21 13 12 12.2 7.5 6.6 2.3 2.1 2.0 10.8 16.5 16.9 2.8 3.7 4.1 123 Metals & Mining Hindalco Industries BUY 326 400 23 733 10.1 2,220 27 35 37 55 27 4 12 9 9 6.8 6.0 5.4 1.1 1.0 0.9 10.0 11.6 10.9 0.9 1.2 1.5 70 Hindustan Zinc BUY 295 335 14 1,247 17.2 4,225 19 23 24 17 23 3 16 13 12 9.7 7.6 7.4 3.9 3.9 3.9 22 30 31 7.2 7.8 8.0 8 Jindal Steel and Power BUY 309 380 23 315 4.3 1,020 58 36 36 863 (38) (2) 5 8 9 3.8 4.4 4.2 0.8 0.8 0.7 17.2 9.5 8.6 — — — 47 JSW Steel ADD 423 415 (2) 1,021 14.1 2,402 30 29 35 201 (5) 22 14 15 12 7.7 7.2 6.1 2.3 2.0 1.8 18.2 14.8 15.7 0.5 0.5 0.5 44 National Aluminium Co. SELL 56 35 (38) 105 1.4 1,866 3 3 3 362 (13) 5 16 19 18 6.9 7.7 8.1 1.1 1.0 1.0 6.4 5.6 5.7 0.0 2.6 2.8 21 NMDC REDUCE 133 110 (17) 390 5.4 2,931 20 14 8 34 (28) (40) 7 9 16 6.3 12.0 20.9 1.3 1.2 1.2 19.8 13.2 7.5 3.7 5.3 3.2 22 Tata Steel BUY 704 875 24 812 11.2 1,204 84 93 92 139 10 (1) 8 8 8 5.9 5.3 5.4 1.1 1.0 0.9 13.5 13.4 11.8 2.6 2.6 2.3 200 Vedanta REDUCE 224 180 (20) 833 11.5 3,717 24 25 26 262 4 7 9 9 9 4.8 4.1 3.8 1.6 1.5 1.4 16.3 16.8 17.0 12.5 7.6 7.8 69 Metals & Mining Attractive 5,456 75.2 124 1 2 10 10 10 6.2 5.8 5.5 1.6 1.4 1.3 15.1 14.0 13.1 4.4 4.0 4.0 480

Source: Company, Bloomberg, Kotak Institutional Equities estimates

20 KOTAK INSTITUTIONAL EQUITIES RESEARCH 20

Kotak Institutional Equities: Valuation summary of KIE Universe stocks 21 Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3mo

Company Rating 17-Mar-21 (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 432 475 10 937 12.9 1,967 47 38 40 349 (19) 5 9 11 11 7.5 9.0 8.1 2.3 2.1 1.9 26.3 19.2 18.4 5.0 4.4 4.7 80 Coal India BUY 140 185 32 862 11.9 6,163 19 17 18 (31) (8) 4 8 8 8 6.9 6.7 6.0 2.8 2.9 3.1 36.2 34.7 38.1 14.3 14.3 14.3 39 HPCL BUY 236 260 10 351 4.8 1,499 57 34 35 700 (40) 4 4 7 7 5.6 7.9 7.1 1.0 0.9 0.8 26.7 13.8 13.2 4.8 5.1 6.0 27 IOCL BUY 98 115 17 924 12.7 9,181 19 15 15 592 (25) 6 5 7 6 4.9 5.4 5.2 0.9 0.8 0.8 18.1 12.6 12.5 8.1 6.7 7.1 43 Oil India SELL 129 85 (34) 140 1.9 1,084 0 8 9 (100) 8,787 13 1,386 16 14 10.6 6.9 6.6 0.6 0.6 0.5 0.0 3.6 4.0 2.6 2.6 2.9 3 ONGC SELL 109 90 (18) 1,376 19.0 12,580 8 14 15 (42) 85 4 14 8 7 4.9 3.5 3.2 0.6 0.5 0.5 4.2 7.5 7.4 2.3 4.9 5.3 54 Reliance Industries ADD 2,055 2,050 (0) 12,182 167.9 6,032 73 85 101 10 15 20 28 24 20 16.6 11.1 9.0 2.4 2.2 2.0 9.2 9.7 10.3 0.3 0.4 0.4 354 Oil, Gas & Consumable Fuels Attractive 16,772 231.2 35 8 12 17 15 14 10.0 8.0 6.9 1.7 1.5 1.4 10.4 10.0 10.4 2.0 2.1 2.2 601 Pharmaceuticals Aurobindo Pharma REDUCE 839 880 5 492 6.8 586 56 61 65 15 8 7 15 14 13 9.1 8.1 7.2 2.3 2.0 1.8 15.1 14.3 13.7 0.9 1.1 1.3 40 Biocon SELL 388 310 (20) 466 6.4 1,202 6 9 11 0 42 25 62 44 35 26.6 19.6 16.0 4.8 4.4 4.0 7.7 10.1 11.4 0.6 0.8 1.0 29 Cipla BUY 772 950 23 623 8.6 806 32 34 50 66 8 45 24 22 16 13.5 12.6 8.7 3.4 3.1 2.6 14.2 13.6 17.0 0.8 0.8 1.2 57 Divis Laboratories REDUCE 3,378 3,300 (2) 897 12.4 265 75 90 103 44 20 15 45 38 33 31.5 26.5 23.0 10.4 8.8 7.5 23.1 23.4 22.8 (0.8) (0.9) (1.1) 47 Dr Reddy's Laboratories SELL 4,359 4,300 (1) 725 10.0 166 157 194 258 20 24 33 28 22 17 16.0 12.6 9.6 4.3 3.7 3.1 15.3 16.4 18.3 0.6 0.8 0.7 80 Gland Pharma REDUCE 2,533 2,200 (13) 414 5.7 163 61 76 89 22 25 17 42 33 29 29.4 24.6 20.6 7.0 5.8 4.8 16.8 17.3 16.9 — — — - Laurus Labs REDUCE 349 340 (3) 187 2.6 536 19 19 24 287 5 22 19 18 15 13.1 11.8 9.3 6.8 4.9 3.7 35.9 27.4 25.1 — — — 17 Lupin ADD 1,021 1,200 18 463 6.4 450 25 43 52 17 68 23 40 24 19 16.5 11.3 9.2 3.4 3.0 2.7 8.4 12.7 13.7 0.4 0.6 0.8 43 Sun Pharmaceuticals ADD 585 635 9 1,403 19.3 2,406 25 24 29 48 (2) 19 24 24 20 15.2 13.6 11.5 3.0 2.7 2.4 12.6 11.8 12.0 0.4 0.8 1.0 71 Torrent Pharmaceuticals REDUCE 2,415 2,750 14 409 5.6 169 71 84 100 24 18 19 34 29 24 17.1 15.7 13.6 7.3 6.2 5.3 21.4 21.7 22.2 1.0 1.2 1.4 15 Pharmaceuticals Attractive 6,078 83.8 37 14 22 28 25 20 16.7 14.2 11.7 4.0 3.6 3.1 14.3 14.4 15.3 0.3 0.5 0.6 401 Real Estate Brigade Enterprises BUY 272 310 14 57 0.8 204 (4) 14 19 (158) 480 38 NM 19 14 23.3 7.6 6.8 2.6 2.3 2.1 NM 12.7 15.6 0.9 0.9 0.9 1 DLF REDUCE 291 240 (18) 721 9.9 2,475 5 8 9 298 65 14 62 37 33 48.6 35.9 35.6 2.1 2.0 1.9 3.4 5.4 5.9 0.7 0.7 0.7 79 Embassy Office Parks REIT ADD 339 380 12 321 4.4 948 10 11 13 2 12 15 34 30 26 20.1 15.4 13.5 1.2 1.2 1.3 3.8 4.0 4.9 5.8 7.6 8.7 5 Godrej Properties SELL 1,390 810 (42) 350 4.8 252 6 14 32 (48) 156 125 248 97 43 (434) 139.4 62.7 7.1 6.6 5.7 2.9 7.1 14.2 — — — 23 Mindspace REIT ADD 305 340 11 181 2.5 593 14 16 18 69 10 13 21 19 17 17.3 14.0 12.6 1.1 1.1 1.1 9.1 5.7 6.5 2.7 6.7 7.1 2 Oberoi Realty ADD 577 590 2 210 2.9 364 22 28 32 13 31 13 27 21 18 19.8 15.7 14.1 2.2 2.0 1.8 8.7 10.4 10.6 0.3 0.3 0.3 4 Phoenix Mills BUY 781 960 23 134 1.8 172 5 22 33 (78) 373 47 165 35 24 27.7 14.6 11.5 2.7 2.6 2.3 1.9 7.6 10.3 - 0.3 0.4 2 Prestige Estates Projects ADD 276 315 14 111 1.5 401 5 17 27 (48) 246 59 56 16 10 9.4 6.7 5.3 2.0 1.8 1.5 3.7 11.8 16.4 0.5 0.5 0.5 3 Sobha BUY 457 480 5 43 0.6 95 11 38 54 (65) 259 43 43 12 8 7.6 5.1 4.3 1.8 1.6 1.4 4.1 13.8 17.4 1.5 1.5 1.5 2 Sunteck Realty REDUCE 340 345 2 50 0.7 140 8 19 15 9 148 (21) 44 18 22 33.5 13.8 17.2 1.6 1.5 1.4 3.7 8.6 6.4 0.3 0.3 0.3 2 Real Estate Attractive 2,178 30.0 53 69 26 50 30 24 25.7 17.1 14.6 2.0 1.9 1.8 3.9 6.4 7.8 1.4 2.0 2.3 124

Retailing Daily Summary India Aditya Birla Fashion and Retail BUY 205 250 22 189 2.6 915 (6) 3 4 (192) 152 39 NM 64 46 55.9 14.1 11.6 9.1 7.4 6.4 NM 13.0 14.9 — — — 9 Avenue Supermarts SELL 3,001 1,885 (37) 1,944 26.8 648 18 33 43 (15) 87 28 168 90 70 110 60 47 15.9 13.5 11.3 9.9 16.2 17.6 — — — 27 Titan Company ADD 1,473 1,625 10 1,307 18.0 888 10 23 29 (40) 132 25 146 63 50 79 40 33 17.9 14.8 12.2 12.8 25.7 26.5 0.2 0.4 0.5 49 Retailing Attractive 3,441 47.4 (44) 207 28 233 76 59 92 44 35 15.9 13.3 11.1 6.8 17.5 18.7 0.1 0.2 0.2 85

Source: Company, Bloomberg, Kotak Institutional Equities estimates

KOTAK INSTITUTIONAL EQUITIES EQUITIES INSTITUTIONAL KOTAK -

March 18, March2021 18, RESEARCH

KOTAK INSTITUTIONAL EQUITIES RESEARCH 21

Kotak Institutional Equities: Valuation summary of KIE Universe stocks India

Price (Rs) Fair Value Upside Mkt cap. O/S shares EPS (Rs) EPS growth (%) P/E (X) EV/EBITDA (X) P/B (X) RoE (%) Dividend yield (%) ADVT-3mo

KOTAK INSTITUTIONAL EQUITIES RESEARCH EQUITIES INSTITUTIONAL KOTAK Company Rating 17-Mar-21 (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)

Speciality Chemicals Daily Summary Castrol India BUY 125 165 32 123 1.7 989 6 9 10 (28) 50 8 21 14 13 13.3 9.1 8.3 8.7 8.1 7.5 43.0 61.0 61.2 4.4 6.4 6.8 3 Pidilite Industries REDUCE 1,720 1,760 2 874 12.0 508 22 29 35 (5) 30 23 79 60 49 53 41 34 16.9 14.6 12.5 23.1 26.0 27.5 0.4 0.6 0.7 21 S H Kelkar and Company BUY 115 145 26 16 0.2 141 9 9 10 92 2 12 13 13 11 8.9 7.5 6.7 1.7 1.5 1.4 14.0 12.5 12.9 1.3 2.0 2.6 1 SRF ADD 5,405 5,600 4 320 4.4 58 186 225 288 35 21 28 29 24 19 17.0 14.5 11.7 4.7 4.1 3.4 18.7 18.3 19.6 0.3 0.3 0.4 15 Speciality Chemicals Attractive 1,334 18.4 2 30 21 46 35 29 28.6 22.5 18.8 9.4 8.1 6.9 20.6 23.1 23.8 0.7 1.1 1.2 41 Telecommunication Services Bharti Airtel BUY 523 710 36 2,853 39.3 5,456 (5) 12 22 NM NM NM NM 45 24 8.7 6.9 5.7 4.7 4.5 4.0 NM 10.4 18.1 1.1 1.1 1.1 191 Indus Towers ADD 254 250 (2) 685 9.4 2,695 18 18 19 20 (0) 6 14 14 14 5.6 5.3 5.0 4.6 4.5 4.3 34.0 31.9 32.4 9.0 6.3 6.3 21 Vodafone Idea RS 10 — — 283 3.9 28,735 (8) (6) (4) NM NM NM NM NM NM 10.6 8.1 6.6 (0.9) (0.7) (0.5) 176.3 47.4 25.7 — — — 65 Tata Communications BUY 1,141 1,200 5 325 4.5 285 48 55 64 24 13 17 24 21 18 9.8 8.7 7.5 NM 24.0 10.9 NM 245 83.4 0.4 0.5 0.6 8 Telecommunication Services Attractive 4,146 57.2 43 73 213 NM NM 67 8.7 7.0 5.9 10.0 11.5 12.3 NM NM 18.3 2.3 1.9 1.9 285

Transportation -

Adani Ports and SEZ ADD 688 790 15 1,398 19.3 2,112 22 33 40 (15) 52 19 31 21 17 20.3 13.5 11.1 5.0 3.6 3.0 16.9 20.1 18.8 0.5 0.7 0.7 95 March2021 18, Container Corp. SELL 542 455 (16) 330 4.6 609 12 16 20 (27) 27 29 44 35 27 23.6 19.5 15.6 3.2 3.1 3.0 7.4 9.1 11.4 1.2 1.6 2.0 28 Gateway Distriparks BUY 180 150 (17) 22 0.3 125 5 5 7 29 (12) 54 33 37 24 10.1 10.4 8.7 1.5 1.5 1.5 4.9 4.1 6.2 1.7 1.7 1.7 1 GMR Infrastructure BUY 26 26 (1) 158 2.2 6,036 (4) (1) (0) (23) 63 65 NM NM NM 86.5 18.9 13.4 (3.7) (3.4) (4.3) 66.3 18.3 7.4 — — — 9

Gujarat Pipavav Port BUY 100 120 21 48 0.7 483 5 7 8 (19) 36 14 20 15 13 9.5 7.9 6.9 2.3 2.3 2.3 11.4 15.5 17.7 4.6 6.2 7.1 2 InterGlobe Aviation BUY 1,696 2,100 24 653 9.0 383 (142) 66 127 (2,095) 147 91 NM 25 13 154.1 5.5 3.6 41.8 15.8 3.6 NM 90.1 74.6 — — — 32 Mahindra Logistics REDUCE 571 440 (23) 41 0.6 71 7 13 18 (20) 81 37 80 44 32 ------9.1 15.0 18.1 — — — 1 Transportation Attractive 2,651 36.5 (139) 634 44 NM 26 18 26.7 11.6 8.9 6.4 4.8 3.9 NM 18.6 21.6 0.5 0.7 0.8 167 KIE universe 155,011 2,137 34.1 30.3 19.4 29.1 22.3 18.7 14.1 11.4 9.9 3.2 2.9 2.7 11.2 13.1 14.2 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$)= 72.54 Source: Company, Bloomberg, Kotak Institutional Equities estimates

22 KOTAK INSTITUTIONAL EQUITIES RESEARCH 22

India Daily Summary - March 18, 2021

India of of the following trategic transaction As of December 31, 2020 n a merger or s any, noare longer in effect for this stock , if, fair value KOTAK INSTITUTIONAL EQUITIES RESEARCH , any, if for this stock,because is there notsufficient a

fair valuefair

.

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 205 equity securities. luded

r r display is not or applicable. months. . The previous investment and rating

SELL 3.4% 21.0%

fair valuefair

term volatility in stock prices related to movements in the market.Hence, a particular Ratingmay not , if, any,have been suspended temporarily.Such suspension is in compliance with applicable regulation(s) - 0.5% 14.6% fair valuefair +5% returns over the next 12 months. REDUCE

- month horizon basis. 5 - - 15% returns over the next 12 5% returns over the next months.12 The information is not available fo - -

ake into account short ADD 26.8% 3.9% Kotak SecuritiesKotak has suspended coverage of this company.

are also on12 a Kotak SecuritiesKotak Research has suspended the investment and rating

The information is not meaningful and is therefore exc

Kotak SecuritiesKotak does not cover this company.

The investment and rating

The coverage view represents each analyst’s fundamental overall outlook on the Sector.The coverage viewwill consist of one

Attractive, Neutral, Cautious. BUY 1.5% 37.6% We expect this stock to deliver We this expect stock to deliver 5 We expect this to stock deliver < We expect this to stock deliver more than 15% returns over the next months.12

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 and shouldnot be relied upon. = NA AvailableNot or Applicable.Not = NM Meaningful.Not and/or and/or Kotak Securities policies in circumstances when Securities Kotak or its affiliates is acting in an advisory capacity i involving this company and in certain other circumstances. CS = Coverage Suspended. = NC Covered.Not = RatingRS Suspended. fundamental basis for determining an investment rating or Other definitions Other Coverage view. designations: ratings/identifiers Other NR = Rated.Not REDUCE. SELL. Our Our Ratings System notdoes t strictly be in accordance with the Rating System all at times. Ratings other and definitions/identifiers ratings of Definitions BUY. ADD.

23

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 2021 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. Such research analysts may not be associated persons of Kotak Mahindra Inc and therefore, may not be subject to NASD Rule 2711 restrictions on communications with a subject company, public appearances and trading securities held by a research analyst account. 3. Any U.S. recipients of the research who wish to effect transactions in any security covered by the report should do so with or through Kotak Mahindra Inc and (ii) any transactions in the securities covered by the research by U.S. recipients must be effected only through Kotak Mahindra Inc at [email protected]. This report is distributed in Singapore by Kotak Mahindra (UK) Limited (Singapore Branch) to institutional investors, accredited investors or expert investors only as defined under the Securities and Futures Act. Recipients of this analysis / report are to contact Kotak Mahindra (UK) Limited (Singapore Branch) (16 Raffles Quay, #35-02/03, Hong Leong Building, Singapore 048581) in respect of any matters arising from, or in connection with, this analysis / report. Kotak Mahindra (UK) Limited (Singapore Branch) is regulated by the Monetary Authority of Singapore. Kotak Securities Limited and its affiliates are a full-service, integrated investment banking, investment management, brokerage and financing group. We along with our affiliates are leading underwriter of securities and participants in virtually all securities trading markets in India. We and our affiliates have investment banking and other business relationships with a significant percentage of the companies covered by our Investment Research Department. Our research professionals provide important input into our investment banking and other business selection processes. Investors should assume that Kotak Securities Limited and/or its affiliates are seeking or will seek investment banking or other business from the company or companies that are the subject of this material and that the research professionals who were involved in preparing this material may participate in the solicitation of such business. Our research professionals are paid in part based on the profitability of Kotak Securities Limited, which include earnings from investment banking and other business. Kotak Securities Limited generally prohibits its analysts, persons reporting to analysts, and members of their households from maintaining a financial interest in the securities or derivatives of any companies that the analysts cover. Additionally, Kotak Securities Limited generally prohibits its analysts and persons reporting to analysts from serving as an officer, director, or advisory board member of any companies that the analysts cover. Our salespeople, traders, and other professionals may provide oral or written market commentary or trading strategies to our clients that reflect opinions that are contrary to the opinions expressed herein, and our proprietary trading and investing businesses may make investment decisions that are inconsistent with the recommendations expressed herein. In reviewing these materials, you should be aware that any or all of the foregoing, among other things, may give rise to real or potential conflicts of interest. Additionally, other important information regarding our relationships with the company or companies that are the subject of this material is provided herein. This material should not be construed as an offer to sell or the solicitation of an offer to buy any security in any jurisdiction where such an offer or solicitation would be illegal. We are not soliciting any action based on this material. It is for the general information of clients of Kotak Securities Limited. It does not constitute a personal recommendation or take into account the particular investment objectives, financial situations, or needs of individual clients. Before acting on any advice or recommendation in this material, clients should consider whether it is suitable for their particular circumstances and, if necessary, seek professional advice. The price and value of the investments referred to in this material and the income from them may go down as well as up, and investors may realize losses on any investments. Past performance is not a guide for future performance, future returns are not guaranteed and a loss of original capital may occur. Kotak Securities Limited does not provide tax advise to its clients, and all investors are strongly advised to consult with their tax advisers regarding any potential investment. Certain transactions -including those involving futures, options, and other derivatives as well as non-investment-grade securities - give rise to substantial risk and are not suitable for all investors. The material is based on information that we consider reliable, but we do not represent that it is accurate or complete, and it should not be relied on as such. Opinions expressed are our current opinions as of the date appearing on this material only. We endeavor to update on a reasonable basis the information discussed in this material, but regulatory, compliance, or other reasons may prevent us from doing so. We and our affiliates, officers, directors, and employees, including persons involved in the preparation or issuance of this material, may from time to time have "long" or "short" positions in, act as principal in, and buy or sell the securities or derivatives thereof of companies mentioned herein. Kotak Securities Limited and its non US affiliates may, to the extent permissible under applicable laws, have acted on or used this research to the extent that it relates to non US issuers, prior to or immediately following its publication. Foreign currency denominated securities are subject to fluctuations in exchange rates that could have an adverse effect on the value or price of or income derived from the investment. In addition, investors in securities such as ADRs, the value of which are influenced by foreign currencies affectively assume currency risk. In addition options involve risks and are not suitable for all investors. Please ensure that you have read and understood the current derivatives risk disclosure document before entering into any derivative transactions. Kotak Securities Limited established in 1994, is a subsidiary of Kotak Mahindra Bank Limited. Kotak Securities is one of India's largest brokerage and distribution house. Kotak Securities Limited is a corporate trading and clearing member of Bombay Stock Exchange Limited (BSE), National Stock Exchange of India Limited (NSE), Metropolitan Stock Exchange of India Limited (MSE), National Commodity and Derivatives Exchange (NCDEX) and Multi Commodity Exchange(MCX). Our businesses include stock broking, services rendered in connection with distribution of primary market issues and financial products like mutual funds and fixed deposits, depository services and Portfolio Management. Kotak Securities Limited is also a depository participant with National Securities Depository Limited (NSDL) and Central Depository Services (India) Limited (CDSL). Kotak Securities Limited is also registered with Insurance Regulatory and Development Authority as Corporate Agent for Kotak Mahindra Old Mutual Life Insurance Limited and is also a Mutual Fund Advisor registered with Association of Mutual Funds in India (AMFI). Kotak Securities Limited is registered as a Research Analyst under SEBI (Research Analyst) Regulations, 2014. We hereby declare that our activities were neither suspended nor we have defaulted with any stock exchange authority with whom we are registered in last five years. However SEBI, Exchanges and Depositories have conducted the routine inspection and based on their observations have issued advise letters or levied minor penalty on KSL for certain operational deviations. We have not been debarred from doing business by any Stock Exchange / SEBI or any other authorities; nor has our certificate of registration been cancelled by SEBI at any point of time. We offer our research services to primarily institutional investors and their employees, directors, fund managers, advisors who are registered with us Details of Associates are available on website i.e. www.kotak.com Research Analyst has served as an officer, director or employee of subject company(ies): No We or our associates may have received compensation from the subject company(ies) in the past 12 months. We or our associates have managed or co-managed public offering of securities for the subject company(ies) in the past 12 months. YES. Visit our website for more details We or our associates may have received compensation for investment banking or merchant banking or brokerage services from the subject company(ies) in the past 12 months. We or our associates may have received any compensation for products or services other than investment banking or merchant banking or brokerage services from the subject company(ies) in the past 12 months. We or our associates may have received compensation or other benefits from the subject company(ies) or third party in connection with the research report. Our associates may have financial interest in the subject company(ies). Research Analyst or his/her relative's financial interest in the subject company(ies): No Kotak Securities Limited has financial interest in the subject company(ies) at the end of the month immediately preceding the date of publication of Research Report: Reliance Industries - YES Nature of Financial interest: Holding equity shares or derivatives of the subject company. Our associates may have actual/beneficial ownership of 1% or more securities of the subject company(ies) at the end of the month immediately preceding the date of publication of Research Report. Research Analyst or his/her relatives has actual/beneficial ownership of 1% or more securities of the subject company(ies) at the end of the month immediately preceding the date of publication of Research Report: No Kotak Securities Limited has actual/beneficial ownership of 1% or more securities of the subject company(ies) at the end of the month immediately preceding the date of publication of Research Report: No Subject company(ies) may have been client during twelve months preceding the date of distribution of the research report. A graph of daily closing prices of securities is available at https://www.moneycontrol.com/india/stockpricequote/ and http://economictimes.indiatimes.com/markets/stocks/stock-quotes. (Choose a company from the list on the browser and select the"three years" icon in the price chart). Kotak Securities Limited. Registered Office: 27 BKC, C 27, G Block, Bandra Kurla Complex, Bandra (E), Mumbai 400051. CIN: U99999MH1994PLC134051, Telephone No.: +22 43360000, Fax No.: +22 67132430. Website: www.kotak.com / www.kotaksecurities.com. Correspondence Address: Infinity IT Park, Bldg. No 21, Opp. Film City Road, A K Vaidya Marg, Malad (East), Mumbai 400097. Telephone No: 42856825. SEBI Registration No. INZ000200137(Member of NSE, BSE, MSE, MCX & NCDEX). Member Id: NSE-08081; BSE-673; MSE-1024; MCX-56285; NCDEX-1262. AMFI ARN 0164, PMS INP000000258 and Research Analyst INH000000586. NSDL/CDSL: IN-DP-NSDL-23-97. Compliance Officer Details: Mr. Manoj Agarwal. Call: 022 - 4285 8484, or Email: [email protected]. Investments in securities market are subject to market risks, read all the related documents carefully before investing. In case you require any clarification or have any concern, kindly write to us at below email ids: Level 1: For Trading related queries, contact our customer service at ‘[email protected]’ and for demat account related queries contact us at [email protected] or call us on: Toll free numbers 18002099191 / 1860 266 9191 Level 2: If you do not receive a satisfactory response at Level 1 within 3 working days, you may write to us at [email protected] or call us on 022-42858445 and if you feel you are still unheard, write to our customer service HOD at [email protected] or call us on 022-42858208. Level 3: If you still have not received a satisfactory response at Level 2 within 3 working days, you may contact our Compliance Officer (Name: Mr. Manoj Agarwal) at [email protected] or call on 91- (022) 4285 8484. Level 4 : If you have not received a satisfactory response at Level 3 within 7 working days, you may also approach Managing Director / CEO (Mr. Jaideep Hansraj) at [email protected] or call on 91-(022) 4285 8301. First Cut notes published on this site are for information purposes only. They represent early notations and responses by analysts to recent events. Data in the notes may not have been verified by us and investors should not act upon any data or views in these notes. Most First Cut notes, but not necessarily all, will be followed by final research reports on the subject. There could be variance between the First cut note and the final research note on any subject, in which case the contents of the final research note would prevail. We accept no liability for the contents of the First Cut Notes.