Mining the golden opportunity in retail loans

December 17, 2019

An ICICI Bank report powered by CRISIL An ICICI Bank report powered by CRISIL

1 In pursuit of retail growth prospect

Objective Find out the growth prospect of retail loans market in India taking into account consumer financial behavior, technological progress and global trends

Coverage • Likely evolution of asset classes in the retail loans market over the next 5 years • Key drivers and regulatory enablers • Evolving trends

2 In pursuit of retail growth prospect

Sources Proprietary sources Primary sources Public sources •ICICI Bank’s current •Primary research with •Company disclosures portfolio and deep over 200 industry •Annual reports, CRISIL understanding of participants rating reports consumer finance •Consumer research •Credit bureau: Experian, category with 3,100 individuals CRIF-Highmark •CRISIL’s proprietary across 10 cities •Published data: RBI, SLBC, models NHB, SIAM •Global reports on other economies by renowned agencies

Note: These standard sources have been used across the report 3 India treading the China growth path

$ 20,000 65%

55 16,000

45 12,000 35 8,000 25

4,000 15

0 5 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

4 Retail loans The years ahead

5 Retail loans growth in India has topped other major economies in the recent past

20% 17% 16% 15% CAGR FY13 - FY18 10%

5% 3%

0% -1% -1% -5% India* China United States Germany United Kingdom

Note: Retail loans includes – Normal housing loans, low-ticket housing loans, loan against property (LAP), MSME loans of less than Rs 2 crore ticket size, auto

6 loans, personal loans, credit cards, consumer durable loans, gold loans and education loans Retails loans estimated to double-up to Rs. 96 trillion in 5 years

Rs. Trillion 120

100 Retail Advances

80

60 96 40

20 48 22 0 2013-14EFY14 2018-19EFY19 FY242023-24F

Note: Retail loans includes – Normal housing loans, low-ticket housing loans, loan against property (LAP), MSME loans of less than Rs 2 crore ticket size, 7 auto loans, personal loans, credit cards, consumer durable loans, gold loans and education loans Increased demand projected for both consumption and investment-driven loans

• Consumers more open to taking loans Rs. Trillion • Continuing trend of urbanisation and 110 nuclearisation 90 28 • Increased availability of data from traditional 70 and non-traditional sources 50 • Financiers leveraging technology and data 13 68 analytics 30 6 35 • Regulatory and legislative initiatives 10 16

propelling growth in low-cost housing loans -10 FY14 FY19 FY24P and MSME loans Investment Consumption

Note: Investment includes housing, LAP, commercial vehicles, construction equipment, three wheelers, tractors and MSME loans of less than Rs 2 crore ticket size. 8 Consumption includes passenger vehicle, two wheelers, gold, personal, credit cards, consumer durables, education loans Healthy double-digit value growth foreseen across categories (1/3)

Amount outstanding (Rs. Trillion) CAGR FY14E FY19E FY24P (FY19 - FY24)

Normal housing loans 4.8 13 25.4 14%

# Low-ticket housing loans 3.5 5.7 11.5 16%

Loan against Property 1.6 4.7 9.2 15%

Personal loans 1.1 3.9 10.5 22%

Credit cards* 0.3 1.2 3.3 23%

Note: # Average ticket size of low-cost housing loans: Metro less than Rs. 2.5 million, Non-metro less than Rs. 1.5 million; *No of fresh issued cards; 9 Healthy double-digit value growth foreseen across categories (2/3)

Amount outstanding (Rs. Trillion) CAGR FY14E FY19E FY24P (FY19 - FY24)

Commercial Vehicle finance* 2.6 4.8 9.1 14%

# Passenger Vehicle finance 1.8 3.7 7.3 14%

Two wheeler loans 0.2 0.5 1.1 16%

Note: * Commercial vehicle finance includes new commercial vehicle, old commercial vehicle, construction equipment, tractors and three wheelers # Passenger vehicle finance includes new passenger vehicle and old passenger vehicle 10 Healthy double-digit value growth foreseen across categories (3/3)

Amount outstanding (Rs. Trillion) CAGR FY14E FY19E FY24P (FY19 - FY24)

MSME 3.1 6.6 13.2 15%

Consumer durable loans 0.07 0.24 0.62 21%

Gold 2.1 2.8 3.9 7%

Education Loans 0.6 0.9 1.4 10%

11 Volumes to explode across retail asset classes (1/2)

Average annual accounts Contribution to value added (mn) growth in next 5 years (%) FY17-19 FY20-24 Volume Ticket Size

Normal housing loans 1.1 1.6 96% 4%

Low-ticket housing loans# 1.7 2.9 103% -3%

Personal loans 7.1 10 77% 23%

Credit Cards* 7.5 9 77% 23%

Consumer durable loans 21.7 52.7 70% 30%

Note: # Average ticket size of low-cost housing loans: Metro less than Rs. 2.5 million, Non-metro less than Rs. 1.5 million; *No of fresh issued cards; 12 Volumes to explode across retail asset classes (2/2)

Average annual accounts Contribution to value added (mn) growth in next 5 years (%) FY17-19 FY20-24 Volume Ticket Size

MSME 0.6 1.8 77% 23%

Passenger vehicle finance# 3.6 4.7 77% 23%

Commercial vehicle 1.1 50% finance* 0.8 50%

Two wheeler loans 16.0 23.9 60% 40%

Total 60.1 107.7

Note: * Commercial vehicle finance includes only new commercial vehicle | # Passenger vehicle finance includes new passenger vehicle and old passenger vehicle 13 Systemic profitability to remain steady over the next 5 years

Retail Loans RoA RoA in retail loans will remain steady 2.0% considering that: 1.7% 1.6% • Unsecured lending would grow 1.6%

• Expansion into newer markets 1.2% where spreads would be better due to lower competition 0.8% • Adoption of technology would 0.4% lower TAT & Opex

0.0% FY19E FY24P

14 Five pillars driving the expansion

Newer data sources Increasing Regulatory and Increase in digital Greater usage of to progressively competition could government lending to lower tech and data reduce risk in result in lower costs initiatives to drive costs for analytics to lower lending for consumers growth financiers opex

15 Newer data sources to progressively reduce risk in lending and aid volume growth; benefiting the companies • Access to a plethora of data points for credit assessment and process innovations brought about by technology • Lenders would be able to take instant decisions using data-driven automated lending models that have built-in checks and validations

Income, assets and liabilities data

Basic demographic data Data from GST filings

Legal data PF contribution data

Travel-related data Online purchases

Mobile data Utility bill payments

Health records PoS data 16 Increasing competition, resulting in lower costs; consumers will benefit • The consumers benefit with innovative products, better pricing in certain asset classes and the new found attention to smaller geographies

Yield spread over G-sec rates 8.00% 6.53% 6.50% 6.67% 6.41% 5.90% 5.85% 6.00% 6.70% 5.80% 4.80% 4.90% Passenger vehicle 4.20% 4.00% 4.20% loans - new 3.70% 4.00% 4.50% 4.60% LAP 4.00% 3.40% Normal housing loans 2.90% 2.70% 2.00% 2.40% 2.00% 2.00% 1.50% Personal loans 0.00% FY14E FY15E FY16E FY17E FY18E FY19E

Note: Spread for passenger vehicle loans – new, LAP and normal housing loans are over 10 year g-sec rates; Spread for personal loans are over 3 year G-Sec rates 17 Regulatory and government initiatives to help drive growth (1/2)

• Remarkable success upon the implemented government initiatives in • SME Lending • Housing Loans • Reduction in Corporate Tax • Positive sentiment in the “to be launched/recently launched” regulations like • Reduction in corporate tax rates • The Co-Origination Model • Public Credit Registry

18 Regulatory and government initiatives to help drive growth (2/2)

Digitisation of ownership of land title and legal Reduced TAT and verification documents, providing its access to financial costs institutions

Industry-wide standards in data security, privacy Orderly market development and (PDP Bill), customer protection, shared data access, better customer profiling pricing

Additional data points to lenders Continue thrust on digital payments for credit assessment

Trust and authenticity of customer Enhance Cyber security capabilities data

Scoping out the coverage for Encourage co-lending HFCs and non-PSL lending

Create & test innovative new Innovation hub & environment products/ services

19 Digital lending to account for 16% of retail loans by FY24 - up from 6% currently Share of digital lending to remain higher for banks

• Digital lending – defined as cases where loans 20.0% 19.0% are sourced, underwritten, and sanctioned 15.8% digitally – estimated at Rs. 2.7 trillion as of 16.0% March 2019 • Digital loans forecast to increase to 12.0% 10.3% Rs. 15 trillion (5-year CAGR of 41%), representing ~16% of retail lending in FY24 8.0% 6.4% 5.7% • Banks dominate the market, accounting for 4.4% 77% of total digital loans 4.0%

0.0% Overall Banks NBFCs FY19E FY24P

20 Share of digital lending highest in unsecured segment

Share of digital lending (FY19) • Share of digital lending in overall account Unsecured loans 28% for ~6% in overall retail loans with the highest share in unsecured loans segment Others 7% • Within unsecured loans segment consumer durables has highest share of Auto loans 5% digital lending followed by credit cards and personal loans MSME 4% • Mortgage loans have minuscule share of digital loans Mortgage loans 1%

0% 10% 20% 30%

Note: Unsecured loans includes personal loans, credit card and consumer durable loans; Auto loans includes passenger vehicle, commercial vehicle, two wheelers, three wheelers and tractors; Mortgage includes Normal housing, low-cost hosing and LAP; MSME includes both secured and unsecured loans to the 21 segment; Others includes gold loans and education loans Greater usage of technology and data analytics to lower opex, despite lenders tapping smaller geographies

Retail MSME • Lenders are reimagining the lending value chain by leveraging technology to Acquisition and on-boarding enhance efficiency and efficacy of the Credit assessment decision making process Loan structuring and design • Insights from multiple data sources for credit decision-making and increased Monitoring usage of digital channels for customer Collection acquisition are helping control opex better

Medium High

22 Evolving trends

Smaller markets to witness faster growth

New private banks to gain share

Cumulative share of top 5 players within asset classes will remain steady

Lenders with strong funding, distribution, superior underwriting will lead

23 Share of cities beyond top 50 to increase at a rapid pace

• Intense competition in metros and tier-1 100% cities, 80% Beyond top 50 • Lenders focusing more on smaller 44% 46% cities geographies, Population 60% • Smaller cities to grow at a faster pace <1 million 7% 7% Next 22 cities <1.5 million • Costs likely to move up slightly, which 40% 14% 13% Next 20 cities will be more than compensated by lower opex owing to usage of technology 20% 35% 33% Top 8 cities

0% FY19E FY24P Outside top 50 Other cities in top 50 Next 20 cities Top 8 cities

24 New private banks to gain share

• Market share of banks in the retail consumer lending space to remain consistent. Within banking, market share of new private banks to increase from 37% to 42% over the next five years

Share of retail advances

34% 36% 36%

NBFCs

Banks 66% 64% 64%

FY14E FY19E FY24P

Note: New PVBs like ICICI Bank, HDFC Bank, AXIS Bank, Kotak Bank, IndusInd Bank etc. 25 Top 5 lenders expected to continue to account for high share

• Despite rising competition, top five players across most retail asset class segments expected to continue to account for high market share. This can be attributed to their large balance sheet size, distribution network and relatively lower funding costs.

Share of top 5 lenders across loan categories (FY19E)

Personal Loans

26 Lenders with strong funding, distribution franchise and superior underwriting skills to be ahead of the pack

Strong funding franchise Well entrenched Reasonable share of distribution network relatively higher-margin Access to a variety of retail loans sources of funds at Strong ability to engage competitive costs with customers through Secured loans lend greater multiple channels stability, however, unsecured loans tend to be more profitable Superior underwriting Adequate focus on skills technology

Enhanced focus on analytics, Increased spend to offer customer segmentation and customers a seamless geographical diversification experience across channels

27 Housing loans

28 Healthy double-digit value growth foreseen across categories

Amount outstanding (Rs. Trillion) CAGR (FY19 - FY24) FY14E FY19E FY24P

Normal housing loans 4.8 13 25.4 14%

Low-ticket housing loans# 3.5 5.7 11.5 16%

Loan against Property 1.6 4.7 9.2 15%

Note: # Average ticket size of low-cost housing loans: Metro less than Rs. 2.5 million, Non-metro less than Rs. 1.5 million 29 Mortgage-to-GDP ratio to cross 15% by fiscal 2024

Penetration to rise by 300 bps over …Faster growth will require concrete action next 5 years…

Incentivize people to 16% 15.2% Increase supply of move towards formal affordable homes in 12.4% employment, making locations seeing 12% credit appraisal relatively economic activity easier

8% 6.5% 6.8% Increase 5.3% transparency by Strengthen legal Improve supply digitising and regulatory of long-term 4% property infra to enforce sources of records and liens better funding 0% valuation FY05 FY09 FY14 FY19E FY24P

30 Unsecured loans

31 Healthy double-digit value growth foreseen across categories

Amount outstanding (Rs. Trillion) CAGR (FY19 - FY24) FY14E FY19E FY24P

Personal loans 1.1 3.9 10.5 22%

Credit cards* 0.3 1.2 3.3 23%

Consumer durable loans 0.07 0.2 0.6 21%

Note: *No of fresh issued cards; 32 Unsecured Personal loans: Key growth drivers

Sharper focus on Tier 2 and Tier 3 Greater use of technology to enable regions, which are still largely untapped lenders provide customised product offerings at lower turnaround times

FY14E 33% 14% 5% 49% Modest penetration, headroom for growth Personal loan account holders as FY19E 29% 9% 6% 56% percentage of formal sector employees

FY14E 11% FY24P 23% 6%6% 66% FY19E 15%

FY24P 20% 0% 50% 100%

Top 8 cities Next 20 cities Other cities in top 50 Outside top 50 33 Credit Cards: Key growth drivers

Rising issuance of new cards Growth in organized retail beyond larger cities and e-commerce penetration Organized retail penetration (including e-com)

16% 15.10% 22% 24% 28% Number of POS in the country has more than 10% 10% 13% 12% 10.60% doubled in the past 5 years

8% 69% 5.60% 66% 59% Growth in credit card 4% issuances to new customers, fueled by rising consumer 0% aspirations and popularity of FY17E FY19E FY24P FY09 FY19 FY24 co-branded cards Outside top 50 Next 42 cities Top 8 cities

34 Consumer Durable Finance: Key growth drivers

Increasing footprints of Manufacturers continuing Rising access to credit financiers at mom and to provide subvention on for new-to-credit pop stores consumer durables customers

Players are expanding Entry of several new Proportion of new to their footprints to mom players will ensure a credit customers in & pop stores to competitive consumer durable strengthen their environment: loans to increase (from distribution network • subvention around 25% currently) • easy finance schemes • offers and discounts

35 Technology usage in unsecured lending

Personal Loans Credit Cards & Consumer Durables

Client acquisition and on- • Online/offline retail customers, • Web aggregators boarding: Tie-ups rewards, offers

• Non-traditional data to assess Credit assessment • APIs and internal data models credit worthiness

Documentation • Tablets for sales force • User friendly digital platform

• Pre-approved loans by Loan structuring and leveraging internal customer data • Pre approved amount using EMI design • Customized products like OD card to credit worthy customers limits on salary

Low Medium High 36 37