mining the golden opportunity in retail loans · note: retail loans includes ... digitisation of...

1

Mining the golden opportunity

in retail loans

December 17, 2019

An ICICI Bank report powered by CRISIL

An ICICI Bank report powered by CRISIL

2

In pursuit of retail growth prospect

Objective

Coverage

Find out the growth prospect of retail loans market in India taking

into account consumer financial behavior, technological progress

and global trends

• Likely evolution of asset classes in the retail loans market over

the next 5 years

• Key drivers and regulatory enablers

• Evolving trends

3

In pursuit of retail growth prospect

Proprietary sources

•ICICI Bank’s current

portfolio and deep

understanding of

consumer finance

category

•CRISIL’s proprietary

models

Primary sources

•Primary research with

over 200 industry

participants

•Consumer research

with 3,100 individuals

across 10 cities

Public sources

•Company disclosures

•Annual reports, CRISIL

rating reports

•Credit bureau: Experian,

CRIF-Highmark

•Published data: RBI, SLBC,

NHB, SIAM

•Global reports on other

economies by renowned

agencies

Sources

Note: These standard sources have been used across the report

4

India treading the China growth path

5

15

25

35

45

55

65

0

4,000

8,000

12,000

16,000

20,000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

$ %

5

Retail loans

The years ahead

6

Retail loans growth in India has topped other major economies in

the recent past

17%16%

3%

-1% -1%

-5%

0%

5%

10%

15%

20%

India* China United States Germany United Kingdom

CAGR FY13 - FY18

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

loans, personal loans, credit cards, consumer durable loans, gold loans and education loans

7

22

48

96

0

20

40

60

80

100

120

2013-14E 2018-19E 2023-24F

Retail Advances

FY14

Rs. Trillion

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 loans, personal loans, credit cards, consumer durable loans, gold loans and education loans

FY19 FY24

Retails loans estimated to double-up to Rs. 96 trillion in 5 years

8

Increased demand projected for both consumption and

investment-driven loans

• Consumers more open to taking loans

• Continuing trend of urbanisation and

nuclearisation

• Increased availability of data from traditional

and non-traditional sources

• Financiers leveraging technology and data

analytics

• Regulatory and legislative initiatives

propelling growth in low-cost housing loans

and MSME loans

Note: Investment includes housing, LAP, commercial vehicles, construction equipment, three wheelers, tractors and MSME loans of less than Rs 2 crore ticket size.

Consumption includes passenger vehicle, two wheelers, gold, personal, credit cards, consumer durables, education loans

16

35

68

6

13

28

-10

10

30

50

70

90

110

FY14 FY19 FY24P

Investment Consumption

Rs. Trillion

9

CAGR

(FY19 - FY24)

Normal housing loans

Low-ticket housing loans#

FY14E

4.8

3.5

Healthy double-digit value growth foreseen across categories (1/3)

FY24P

11.5

25.4

FY19E

13

5.7

Amount outstanding (Rs. Trillion)

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;

14%

16%

Loan against Property 1.6 9.24.7 15%

Personal loans

Credit cards*

1.1

0.3

10.5

3.3

3.9

1.2

22%

23%

10

CAGR

(FY19 - FY24)

Passenger Vehicle finance#

Commercial Vehicle

finance*

FY14E

1.8

2.6

FY24P

9.1

7.3

FY19E

3.7

4.8


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

14%

14%

Two wheeler loans 0.2 1.10.5 16%


11

CAGR

(FY19 - FY24)

Consumer durable loans

FY14E

0.07


FY24P

0.62

FY19E

0.24


21%

MSME 3.1 13.26.6 15%

Gold

Education Loans

2.1

0.6

3.9

1.4

2.8

0.9

7%

10%

12Note: # 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;



FY17-19

1.1

1.7

FY20-24

1.6

2.9

Average annual accounts

added (mn)

Personal loans 7.1 10

Credit Cards*

Consumer durable loans

7.5

21.7

9

52.7

Volume

96%

103%

Ticket Size

4%

-3%

Contribution to value

growth in next 5 years (%)

77% 23%

77%

70%

23%

30%

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

13

MSME

Passenger vehicle finance#

FY17-19

0.6

3.6

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

FY20-24

1.8

4.7

Average annual accounts

added (mn)

Two wheeler loans

Commercial vehicle

finance*

16.0

0.8

23.9

1.1

Volume

77%

77%

Ticket Size

23%

23%

Contribution to value

growth in next 5 years (%)

60%

50%

40%

50%

Note: * Commercial vehicle finance includes only new commercial vehicle | # Passenger vehicle finance includes new passenger vehicle and old passenger vehicle

Total 60.1 107.7

14

Systemic profitability to remain steady over the next 5 years

RoA in retail loans will remain steady

considering that:

• Unsecured lending would grow

• Expansion into newer markets

where spreads would be better due

to lower competition

• Adoption of technology would

lower TAT & Opex

1.6%

1.7%

0.0%

0.4%

0.8%

1.2%

1.6%

2.0%

FY19E FY24P

Retail Loans RoA

15

Increasing

competition could

result in lower costs

for consumers

Five pillars driving the expansion

Regulatory and

government

initiatives to drive

growth

Newer data sources

to progressively

reduce risk in

lending

Increase in digital

lending to lower

costs for

financiers

Greater usage of

tech and data

analytics to lower

opex

16

• 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

Travel-related data

Utility bill payments

Health records

Income, assets and liabilities data

Legal data PF contribution data

Online purchases

PoS data

Mobile data

Basic demographic dataData from GST filings

Newer data sources to progressively reduce risk in lending

and aid volume growth; benefiting the companies

17

• The consumers benefit with innovative products, better pricing in certain asset

classes and the new found attention to smaller geographies

6.70%

5.80% 4.80% 4.90%

4.00%

3.40%

4.20%4.00%

4.50% 4.60%

4.20%

3.70%

2.90%

2.00%

2.40%2.70%

2.00%

1.50%

6.53%

5.90%

6.50%6.67%

6.41%

5.85%

0.00%

2.00%

4.00%

6.00%

8.00%

FY14E FY15E FY16E FY17E FY18E FY19E

Passenger vehicle

loans - new

LAP


Personal loans

Yield spread over G-sec rates

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

Increasing competition, resulting in lower costs; consumers will

benefit

18

• 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

Regulatory and government initiatives to help drive growth (1/2)

19

Reduced TAT and verification

costs

Orderly market development and

better customer profiling

Additional data points to lenders

for credit assessment

Trust and authenticity of customer

data

Scoping out the coverage for

HFCs and non-PSL lending

Create & test innovative new

products/ services

Digitisation of ownership of land title and legal

documents, providing its access to financial

institutions

Industry-wide standards in data security, privacy

(PDP Bill), customer protection, shared data access,

pricing

Continue thrust on digital payments

Enhance Cyber security capabilities

Encourage co-lending

Innovation hub & environment

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

20

5.7%6.4%

4.4%

15.8%

19.0%

10.3%

0.0%

4.0%

8.0%

12.0%

16.0%

20.0%

Overall Banks NBFCs

FY19E FY24P

Share of digital lending to remain

higher for banks

Digital lending to account for 16% of retail loans by FY24 - up

from 6% currently

• Digital lending – defined as cases where loans

are sourced, underwritten, and sanctioned

digitally – estimated at Rs. 2.7 trillion as of

March 2019

• Digital loans forecast to increase to

Rs. 15 trillion (5-year CAGR of 41%),

representing ~16% of retail lending in FY24

• Banks dominate the market, accounting for

77% of total digital loans

21

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

segment; Others includes gold loans and education loans

• Share of digital lending in overall account

for ~6% in overall retail loans with the

highest share in unsecured loans segment

• Within unsecured loans segment

consumer durables has highest share of

digital lending followed by credit cards

and personal loans

• Mortgage loans have minuscule share of

digital loans1%

4%

5%

7%

28%

0% 10% 20% 30%

Mortgage loans

MSME

Auto loans

Others

Unsecured loans

Share of digital lending (FY19)

Share of digital lending highest in unsecured segment

22

• Lenders are reimagining the lending value

chain by leveraging technology to

enhance efficiency and efficacy of the

decision making process

• Insights from multiple data sources for

credit decision-making and increased

usage of digital channels for customer

acquisition are helping control opex better

Retail MSME

Acquisition and on-boarding

Credit assessment

Loan structuring and design

Monitoring

Collection

HighMedium

Greater usage of technology and data analytics to lower opex,

despite lenders tapping smaller geographies

23

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

24

• Intense competition in metros and tier-1

cities,

• Lenders focusing more on smaller

geographies,

• Smaller cities to grow at a faster pace

• Costs likely to move up slightly, which

will be more than compensated by lower

opex owing to usage of technology

35% 33%

14% 13%

7% 7%

44% 46%

0%

20%

40%

60%

80%

100%

FY19E FY24P

Outside top 50 Other cities in top 50

Next 20 cities Top 8 cities

Top 8 cities

Next 20 cities

Next 22 cities

Beyond top 50

cities

<1 million

<1.5 million

Population

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

25

• 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

Note: New PVBs like ICICI Bank, HDFC Bank, AXIS Bank, Kotak Bank, IndusInd Bank etc.

66% 64% 64%

34% 36% 36%

Banks

NBFCs

FY14E FY19E FY24P

Share of retail advances

New private banks to gain share

26

• 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.

Top 5 lenders expected to continue to account for high share

Share of top 5 lenders across loan categories (FY19E)

Personal

Loans

27

Strong funding franchise

Access to a variety of

sources of funds at

competitive costs

Well entrenched

distribution network

Strong ability to engage

with customers through

multiple channels

Superior underwriting

skills

Enhanced focus on analytics,

customer segmentation and

geographical diversification

Adequate focus on

technology

Increased spend to offer

customers a seamless

experience across

channels

Reasonable share of

relatively higher-margin

retail loans

Secured loans lend greater

stability, however,

unsecured loans tend to be

more profitable

Lenders with strong funding, distribution franchise and superior

underwriting skills to be ahead of the pack

28

Housing

loans

29

CAGR

(FY19 - FY24)



FY14E

4.8

3.5

FY24P

11.5

25.4

FY19E

13

5.7


14%

16%

Loan against Property 1.6 9.24.7 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

Healthy double-digit value growth foreseen across categories

30

Increase supply of

affordable homes in

locations seeing

economic activity

Incentivize people to

move towards formal

employment, making

credit appraisal relatively

easier

Increase

transparency by

digitising

property

records and

valuation

Strengthen legal

and regulatory

infra to enforce

liens better

Improve supply

of long-term

sources of

funding

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

next 5 years…

5.3%

6.5%6.8%

12.4%

15.2%

0%

4%

8%

12%

16%

FY05 FY09 FY14 FY19E FY24P

Mortgage-to-GDP ratio to cross 15% by fiscal 2024

31

Unsecured loans

32

FY14E FY24PFY19E

CAGR

(FY19 - FY24)


Note: *No of fresh issued cards;

Personal loans

Credit cards*

1.1

0.3

10.5

3.3

3.9

1.2

22%

23%

Consumer durable loans 0.07 0.60.2 21%

Healthy double-digit value growth foreseen across categories

33

Modest penetration, headroom for

growth

20%

15%

11%

FY24P

FY19E

FY14E

Personal loan account holders as

percentage of formal sector employees

Greater use of technology to enable

lenders provide customised product

offerings at lower turnaround times

Sharper focus on Tier 2 and Tier 3

regions, which are still largely untapped

23%

29%

33%

6%

9%

14%

6%

6%

5%

66%

56%

49%

0% 50% 100%

FY24P

FY19E

FY14E

Top 8 cities Next 20 cities

Other cities in top 50 Outside top 50

Unsecured Personal loans: Key growth drivers

34

Rising issuance of new cards

beyond larger cities

Growth in organized retail

and e-commerce penetration

Growth in credit card

issuances to new customers,

fueled by rising consumer

aspirations and popularity of

co-branded cards

Number of POS in the

country has more than

doubled in the past 5 years

5.60%

10.60%

15.10%

0%

4%

8%

12%

16%

FY09 FY19 FY24

Organized retail penetration

(including e-com)

69% 66%59%

10%10%

13%

22% 24% 28%

FY17E FY19E FY24P

Outside top 50 Next 42 citiesTop 8 cities

Credit Cards: Key growth drivers

35

Increasing footprints of

financiers at mom and

pop stores

Players are expanding

their footprints to mom

& pop stores to

strengthen their

distribution network

Manufacturers continuing

to provide subvention on

consumer durables

Entry of several new

players will ensure a

competitive

environment:

• subvention

• easy finance schemes

• offers and discounts

Rising access to credit

for new-to-credit

customers

Proportion of new to

credit customers in

consumer durable

loans to increase (from

around 25% currently)

Consumer Durable Finance: Key growth drivers

36

Personal Loans Credit Cards & Consumer Durables

Client acquisition and on-

boarding: Tie-ups• Web aggregators

• Online/offline retail customers,

rewards, offers

Credit assessment• Non-traditional data to assess

credit worthiness• APIs and internal data models

Documentation • Tablets for sales force • User friendly digital platform

Loan structuring and

design

• Pre-approved loans by

leveraging internal customer data

• Customized products like OD

limits on salary

• Pre approved amount using EMI

card to credit worthy customers

Low Medium High

Technology usage in unsecured lending

mining the golden opportunity in retail loans · note: retail loans includes ... digitisation of...

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