RETAIL CREDIT OUTLOOK - Anticipating and preparing for the COVID-19 impact on retail credit market - TransUnion CIBIL
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RETAIL CREDIT OUTLOOK
Anticipating and preparing for the
COVID-19 impact on retail credit market
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 1
Key questions that the market is asking, and what we hope to
cover in this presentation
How might the operating
1 Key implications for lenders
environment change for lenders?
What can be the potential impact Future Readiness
2
on retail credit growth?
Lending Strategy
What may be the likely impact on
3 Risk Management
asset quality?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 2
Operating Environment
How COVID-19 and ensuing containment and relief measures might change
the lending ecosystem?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 3COVID-19 has affected more than 6 million people across 210
countries around the world
COVID-19 Confirmed Cases
As on 2nd June 2020
Source: Our World in Data
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 4Spread of COVID-19 in India has been relatively slower
compared to other major countries affected by the pandemic
Number of Confirmed COVID-19 cases
1,000,000 USA
# Confirmed Cases
Brazil
Russia
UK
(Log scale)
India Spain
100,000
10,000
1,000
1 11 21 31 41 51 61 71 81
Days since the 1000th confirmed case
As on 2nd June 2020
Source: Our World in Data
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 5The phased lockdown implemented to curb the spread of
COVID-19 has social, financial and economic implications
• Loss of job for daily wage earners and migrant workers
Social • Migration of labor leaving them struggling to make ends meet
• Anxiety as a result of social distancing, uncertainty, fear of economic recession
• Impact on consumers’ financial position on account of pay cuts / layoffs
• Revenue reduction for companies leading to potential liquidity challenges for
Financial businesses and solvency crises
• Falling stock prices and widening of credit spreads
• Hit on consumption demand – Decrease in consumption, reduction in
discretionary spending, postponement of new investments
Economic
• Impact on supply side – Decrease in labor supply, curtailment of production, hit
on distribution of goods and services
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 6Labor market conditions have been impacted severely
Labor Participation and Unemployment
Labor Participation Rate Unemployment Rate
50%
40% 42.8% 43.0%
Percentage
42.3% 42.6%
38.2%
30%
23.5%
20%
7.0% 8.2% 7.2% 7.8%
10%
0%
May-19
May-20
Jun-19
Jan-20
Aug-19
Sep-19
Nov-19
Dec-19
Apr-20
Mar-20
Jul-19
Oct-19
Feb-20
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 7Consumer sentiment has taken a hit as a result of worsening
economic conditions
Consumer Sentiment Index
120
100 108.3 105.7 105.9 105.3
Index Value
80
60
40
20 30.9
0
May-19
May-20
Jun-19
Jan-20
Apr-20
Aug-19
Sep-19
Nov-19
Dec-19
Mar-20
Oct-19
Jul-19
Feb-20
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 8The pandemic has brought nearly all activity to a standstill,
with the effect more pronounced in the services sector
Purchasing Managers’ Index (PMI)
Manufacturing PMI Services PMI
70
57.5
60 52.7 52.4 52.7
Index Value
50 54.5
50.2 51.4 51.2
40 30.8
30
20
10
12.6
0
May-20
May-19
Nov-19
Feb-20
Jun-19
Aug-19
Jan-20
Apr-20
Sep-19
Dec-19
Mar-20
Oct-19
Jul-19
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 9Revenue of most businesses has seen a drop and may fall
further in the short term
GST Collections
1,200
1,000
800
INR Bn
600
400
200
0
May-19
Jan-20
Apr-19
Jun-19
Aug-19
Sep-19
Nov-19
Dec-19
Mar-19
Mar-20
Oct-19
Jul-19
Feb-20
Source: Government of India
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 10Consequently, India’s economic growth is expected to contract
in 2020
Growth in Real GDP
GDP Actual GDP Forecast (pre COVID-19) GDP Forecast (post COVID-19)
12%
8.7%
YoY Growth Rate
7.5% 6.2%
8% 5.6%
4.1%
4% 1.1%
~INR 24
0% trillion
(current
-4% prices)
-8%
-12%
Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2016 2017 2017 2017 2017 2018 2018 2018 2018 2019 2019 2019 2019 2020 2020 2020 2020
India’s GDP estimates have been revised for FY18, FY19 and FY20
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 11The Indian government has announced an economic relief
package of INR 20 trillion under “Atmanirbhar Bharat Abhiyan”
Liquidity Infrastructure Helping Stressed
Reforms Infra
Infusion Push Businesses
• New definition of • Reduction in CRR • Affordable rental • Relaxation in
MSMEs • Collateral free loans / housing for migrants insolvency law
• Agri marketing reforms subordinate debt / • Extension of middle • Expediting tax
• Coal, minerals equity for MSMEs income housing refunds
liberalization • Special liquidity and scheme • Funds for stressed
• Higher FDI in defense partial guarantee for • Agri infrastructure NBFCs
production NBFCs fund • Moratorium on loan
• Airport, DISCOM • Funds for DISCOM • Higher VGF for social repayments
privatization • EPF support infrastructure
• New policy for PSUs • INR 2.3 trillion extra
credit to farmers
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 12India's economic relief package, intended to help spur near
term growth and spending, is amongst the largest in the world
Economic Relief Packages by G20 Countries
25%
20%
15%
% of GDP
10%
5%
0%
Australia
Brazil
Korea
Germany
India
Italy
Argentina
US
Canada
UK
France
Turkey
Japan
Indonesia
China
Mexico
South
Russia
Arabia
Africa
South
Saudi
Source: IFC, CSIS, VOX
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 13The pandemic has created operational challenges for lenders
to re-consider and potentially change their operating model
• Realigning branches and loan centres to support social distancing guidelines
• Adjusting working hours, staffing mix and times to avoid contamination
Distribution
• Encouraging customers to use digital channels
• Automating routine service requests (chatbots, etc.)
• Providing temporary relief to customers without impact on credit history
Customer • Creating customer awareness on support and relief measures
Management • Addressing evolving needs of customers
• Segmenting customers based on their credit behavior
• Automating regular tasks and processes
Internal • Rebalancing workload across operational sites
Operations • Enabling online sanction and disbursement of loans
• Reviewing financial health and BCP plans of third-party service providers
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 14To summarize:
• The lockdowns implemented to curb the spread of COVID-19, and the virus itself, would have
far reaching implications on Indian economy
• Consumers’ financial positions are likely to change dramatically and many companies may
see a reduction in revenue
• Drop in consumer sentiment, significant hit on consumption demand and spending will have a
bearing on the future trajectory of the retail credit market
• Lenders will need to innovate and redesign their operating model to transact with confidence
and better support consumers during these unprecedented times
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 15Credit Growth
What can be the potential impact on demand for major products and the
ability and willingness of lenders to extend credit?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 16Retail credit growth, which is a reflection of wider economic
activity, has contracted in the last two years
Growth in Retail Credit Balances and Real GDP
Retail Credit GDP
Balances Growth Rate
40% 12%
YoY GDP Growth Rate
YoY Retail Credit
30% 9%
20% 6%
10% 3%
0% 0%
Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1
2015 2015 2016 2016 2017 2017 2018 2018 2019 2019 2020
Q1 2020 retail credit growth number is as of February 2020
Products considered: home loan, LAP, auto loan, two-wheeler loan, commercial
vehicle loan, construction equipment loan, personal loan, credit card, business loan,
Source: TransUnion CIBIL consumer database,
consumer durable loan, education loan and gold loan
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 17Lending activity has been impacted severely, with some
revival seen in May
Inquiry and Origination Volumes
Inquiry Originations
250
Indexed Volumes
200
150
100
50
0
May-19
May-18
Jun-18
Jan-19
Jun-19
Nov-19
Jan-20
May-20
Apr-18
Apr-19
Apr-20
Jul-18
Aug-18
Sep-18
Nov-18
Dec-18
Oct-18
Jul-19
Aug-19
Sep-19
Dec-19
Feb-19
Mar-19
Oct-19
Feb-20
Mar-20
Index: April-18 = 100
Products considered: home loan, LAP, auto loan, two-wheeler loan, commercial
vehicle loan, construction equipment loan, personal loan, credit card, business loan,
consumer durable loan, education loan and gold loan
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 18Credit growth is a function of demand and supply factors
Analyzed data pertaining
to previous crisis
Demand for Credit Relationship between macro-
economic variables and
(Inquiries) inquiries for key products
Credit Growth
Ability to Lend
Money Supply in the economy
(Liquidity)
Supply of Credit
(Originations)
Willingness to Lend
Changes in approval rates
(Risk aversion)
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 19The previous crisis represents an economic downturn scenario
that may help guide our direction during the current crisis
Growth in Real GDP
14%
12%
YoY Growth Rate
10%
8%
6%
4%
2%
0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 20Inquiry and origination volumes declined by almost 50% YoY
during the crisis period
Growth in Inquiry and Origination Volumes
Inquiry Originations
200
Indexed Volumes
150
100
50
0
Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3 Q1 Q3
2007 2007 2008 2008 2009 2009 2010 2010 2011 2011 2012 2012
Index: Q1 2007 = 100
Products considered: home loan, LAP, auto loan, personal loan and credit card
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 21Demand for housing is closely associated with wealth creation
through the equity market
Growth in Home Loan (HL) Inquiries and Share Price Index
HL Inquiries Share Price Index
120%
Correlation = 0.89
YoY Growth Rate
90%
60%
30%
0%
-30%
-60%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Share price index is the average value of BSE SENSEX
Source: TransUnion CIBIL consumer database,
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 22There is a linkage between overall industrial activity and
demand for loans against property (LAP)
Growth in LAP Inquiries and Index of Industrial Production (IIP)
LAP Inquiries IIP
100% 25%
IIP YoY Growth Rate
YoY Growth Rate
80% Correlation = 0.75 20%
LAP Inquiries
60% 15%
40% 10%
20% 5%
0% 0%
-20% -5%
-40% -10%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
The index of industrial production measures the output of the industrial sector of the
economy, which includes manufacturing, utilities, mining and quarrying Source: TransUnion CIBIL consumer database,
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 23Private consumption and demand for auto loans move together
Growth in Auto Loan (AL) Inquiries and Private Consumption (PC)
AL Inquiries Private Consumption
250% 12%
PC YoY Growth Rate
YoY Growth Rate
200% Correlation = 0.78
10%
AL Inquiries
150%
8%
100%
6%
50%
0% 4%
-50% 2%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Private Consumption is the value of goods and services consumed by households
and non-profit institutions serving households expressed in local currency Source: TransUnion CIBIL consumer database,
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 24Household financial liabilities and demand for personal loans
are closely associated
Growth in Personal Loan (PL) Inquiries and
Household Financial Liabilities (HFL)
PL Inquiries Household financial libilities
500% 30%
HFL YoY Growth Rate
YoY Growth Rate
400% Correlation = 0.97
25%
PL Inquiries
300%
200%
20%
100%
0% 15%
-100%
-200% 10%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Household financial liabilities is defined as the combined liabilities of all people
in a household. It includes loans and borrowings from banks, housing finance
companies (HFCs) and nonbanking financial corporations (NBFCs). Source: TransUnion CIBIL consumer database,
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 25Demand for credit cards, being a lifestyle payment product, is
connected with household wealth
Growth in Credit Card (CC) Inquiries and Gross Household Wealth (GHW)
CC Inquiries Gross Household wealth
200% 20%
GHW YoY Growth Rate
YoY Growth Rate
Correlation = 0.87
150%
CC Inquiries
18%
100%
50% 16%
0%
14%
-50%
-100% 12%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Gross household wealth represents the total value of assets (financial
as well as non-financial) minus the total value of outstanding liabilities
of households (including non-profit institutions serving households) Source: TransUnion CIBIL consumer database,
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 26The ability of financial institutions to lend can be determined
by money supply (M2) in the economy
Growth in Origination Balances and Money Supply (M2)
Origination Balances Money Supply (M2)
120% 25%
Money Supply (M2)
Origination Balances
YoY Growth Rate
100%
YoY Growth Rate
20%
80%
60% 15%
40%
20% 10%
0%
5%
-20% Correlation = 0.70
-40% 0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2007 2007 2007 2007 2008 2008 2008 2008 2009 2009 2009 2009 2010 2010 2010 2010
Products considered: home loan, LAP, auto loan, personal loan and credit card
Money supply (M2) includes cash in circulation, current account deposits as well as all
Source: TransUnion CIBIL consumer database,
time-related deposits, savings deposits, and non-institutional money-market funds
Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 27Approval rates declined for all key products during the crisis
period indicating increased risk aversion
Approval Rates during Crisis Period
60%
-22%
2007 Q2 to
Approval Rate %
-16% 2008 Q1
40% -11%
-30% 2008 Q2 to
-28% 2009 Q1
20%
2009 Q2 to
2010 Q1
0%
Home Loan LAP Auto Loan Personal Loan Credit Card
Products
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 28Secured lending products are expected to see more pronounced
decline in demand
Macro YoY 2020 Outlook for
Product Key Dynamics
Variable Forecast Demand
[Oxford Economics]
• Reduction in affordability
Home Share Price
-11.0% • Postponement of home purchases
Loans Index
Low High • Drop in home prices / attractive offers by builders
• Lower manufacturing / services output
LAP IIP -2.9% • Drop in real estate prices
Low High • Need of finance to revive business
• Reduction in discretionary spending
Private
Auto Loans -1.7% • Impact on travel and tour business
Consumption
Low High • Diminished ability and need to travel
• Need of funds to bridge personal finance gap
Personal Household
+15.1% • Flexible product structure
Loans Liabilities
Low High • Greater access via digital channels
• Increase in the need for digital payments
Credit Household
+9.6% • Reduction in discretionary spending
Cards Wealth
Low High • Postponement of lifestyle purchases
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 29Liquidity may not be a challenge consequent to rate cuts and
other fiscal measures initiated by the regulator
Money Supply (M2)
25%
YoY Growth Rate
20%
15%
10%
5%
0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2018 2018 2018 2018 2019 2019 2019 2019 2020 2020 2020 2020
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 30Lenders are likely to tighten their credit policy and customer
selection norms to manage and mitigate risk
Product Willingness Key Dynamics
• Backed by security, lower default probability
Home Loans
• Lower interest rates, reduced margins
Low High
• Higher risk of default in smaller businesses
LAP
• Irregular cash flows may present assessment challenges
Low High
• Avoiding exposure to tour / travel segment
Auto Loans
• Challenges in repossession and resale of vehicles
Low High
• Unsecured in nature, increased risk of default
Personal Loans • Key product offering for many lenders especially FinTechs
Low High • Higher margins, increased profitability
• Revolving credit line which can be periodically managed
Credit Cards • Spending and behavior can be monitored
Low High • Leveraging CASA / internal database for acquisition
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 31To summarize:
• Demand for products like credit cards and personal loans will remain moderate as consumers
look to secure funds to bridge any personal finance gap
• Decline in discretionary spends and reduced affordability will impact demand for asset finance
products
• Given the inherent risk of products like LAP and personal loans, we anticipate a greater
decline in approval rates for these products
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 32Asset Quality
What may be the likely impact on stress levels for major products?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 33Portfolio delinquency rates have remained largely steady in
the last three years, with the exception of LAP
Balance-level 90+ Delinquency Rate by Product
5%
% Balance in 90+ DPD
LAP
4%
Auto Loan
3%
Home Loans
2%
Credit Card
1%
Personal Loan
0%
Jun-17
Jun-18
Jun-19
Sep-17
Sep-18
Sep-19
Mar-17
Dec-17
Mar-18
Dec-18
Mar-19
Dec-19
Feb-20
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 34Impact on asset quality can be determined by analyzing
consumer scores, collection roll rates and payment hierarchy
Asset Quality
Consumer Risk Collection Roll Payment
Scores Rates Hierarchy
Shifts in borrower risk tiers Number of accounts The order in which
across product portfolios and becoming newly delinquent consumers prioritize
delinquency rates associated and flowing into subsequent payments during times of
with each tier delinquency buckets financial hardship
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 35We looked at 6-month risk tier movement for non delinquent
consumers and their delinquency rates thereof
90+ Balance DPD rate
Risk Tier (t+6)
(t+6)
Product-level Above Above
Subprime Subprime
Balance Subprime Subprime
No
Subprime Upgrade High Risk Low Risk
Risk Tier
upgrade
(t = 0)
Above No Very High Very Low
Downgrade
Subprime downgrade Risk Risk
Risk tier movements and DPD
rates can be simulated to
Subprime segment constitute a CV score of =681 delinquency rates
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 36Share of portfolio in very high risk segment has increased for
credit cards and personal loans in the last one year
Share of Portfolio in Very High Risk Segment
8%
Auto Loan
% of Balance
Credit Card
6%
Personal Loan
4% LAP
Home Loans
2%
Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2
2016 2016 2016 2017 2017 2017 2017 2018 2018 2018 2018 2019 2019
Very High Risk segment refers to those consumers who have moved
from above subprime segment to subprime segment in next 6 months
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 37During the same time period, share of portfolio in low risk
segment has decreased for credit cards
Share of Portfolio in Low Risk Segment
5%
Auto Loan
% of Balance
4% Personal Loan
LAP
3%
Credit Card
2%
Home Loans
1%
Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2
2016 2016 2016 2017 2017 2017 2017 2018 2018 2018 2018 2019 2019
Low Risk segment refers to those consumers who have moved from
subprime segment to above subprime segment in next 6 months
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 38Delinquency rate in very high risk segment has moved up for
home loans and LAP in the last one year
Delinquency Rate for Very High Risk Segment
16%
% Balance in 90+ DPD
Credit Card
12% LAP
Personal Loan
8%
Home Loans
4%
Auto Loan
0%
Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2
2016 2016 2016 2017 2017 2017 2017 2018 2018 2018 2018 2019 2019
Very High Risk segment refers to those consumers who have moved
from above subprime segment to subprime segment in next 6 months
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 39Analyzing bucket net flow rates and lagged flow to 90+ would
also help gauge the impact on 90+ delinquency rate
[Illustration]
Outstanding Balance (value) Net Flow Rates
Bucket
T T+1 T+2 T+3 T+4 T+1 T+2 T+3 T+4
3
Current 100.0 102.0 105.0 107.0 110.0
Bucket net
1-29 4.0 5.0 5.0 6.0 6.0 5% 5% 6% 6%
flow rates
30-59 2.0 3.0 3.0 4.0 5.0 75% 60% 80% 83% can be
60-89 1.6 1.8 2.2 2.5 3.0 90% 74% 83% 75% simulated to
get lagged
90+ 1.3 1.5 1.8 2.1 2.4 94% 100% 95% 96%
flow to 90+
Total 108.9 113.3 117.0 121.6 126.4 Lagged flow to 90+ is the
2 product of diagonal bucket
90+ DPD 1.90% net flow rates 2.40%
Balance in next delinquency bucket 4
(eg: 30-59) on time T+1
Bucket net Impact on DPD can
1
flow rate =
Balance in previous delinquency be calculated basis
bucket (eg: 1-29) on time T lagged flow to 90+
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 40Delinquency rate and lagged flow to 90+ move in same direction
which enables us to use one to predict the other
Home Loan and Personal Loan Delinquency and Lagged Flow Rate
2.5%
HL lagged flow
2.0%
Rate (%)
1.5% HL 90+ delq
1.0% PL lagged flow
0.5% PL 90+ delq
0.0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2017 2017 2017 2017 2018 2018 2018 2018 2019 2019 2019 2019
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 41Lagged flow to 90+ has deteriorated for LAP and credit cards
in the last one year
Lagged Flow to 90+ DPD
6%
LAP
5%
Auto Loan
Percentage
4%
3% Credit Card
2% Home Loans
1% Personal Loan
0%
Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
2017 2017 2017 2017 2018 2018 2018 2018 2019 2019 2019 2019
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 42We studied payment hierarchy for two separate product
combinations, which represent different consumer groups
Study 1 Study 2
Home Significantly Consumer
loan different durable loan
populations
Auto Credit Personal Credit
card loan card
• More affluent • Lower income
• Higher income • Higher risk
• Lower risk
• Tighter lending criteria
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 43The study on payment hierarchy revealed that home loans
generally have the highest payment priority
Account-level 90+ Delinquency Rate
% Accounts in 90+ DPD
1.0%
0.8% Credit Cards
0.6%
Auto Loans
0.4%
0.2% Home Loans
0.0%
Jan-14
May-14
Jan-15
May-15
Jan-16
May-16
Jan-17
May-17
Mar-14
Sep-14
Mar-15
Mar-16
Sep-16
Mar-17
Sep-17
Nov-14
Jul-15
Sep-15
Nov-15
Nov-16
Jul-14
Jul-16
Jul-17
Study Cohorts
Study cohort is the month for which the sample of consumers holding the
above products was picked (~300K per cohort)
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 44Amongst unsecured lending products, personal loans generally
have the highest payment priority
Account-level 90+ Delinquency Rate
2.0%
% Accounts in 90+ DPD
Credit
Cards
1.5%
Consumer
1.0% Durable
Loans
0.5% Personal
Loans
0.0%
Jun-14
Aug-14
Jun-15
Jun-17
Apr-15
Apr-16
Jun-16
Apr-17
Aug-15
Aug-16
Aug-17
Dec-14
Dec-15
Dec-16
Dec-17
Oct-14
Feb-15
Oct-15
Feb-16
Oct-16
Feb-17
Oct-17
Feb-18
Study Cohorts
Study cohort is the month for which the sample of consumers holding the
above products was picked (~300K per cohort)
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 45We simulated these risk related factors to determine the likely
impact on asset quality
Historic Base Worst
Risk Factors
Ranges case Case
Increase in share of portfolio moving from above
0.5% - 0.8% +1% +2%
subprime to subprime (Very High Risk Segment)
Increase in delinquency rate of Very High Risk
1.04X - 1.07X 1.1X 1.2X
Segment
Increase in share of subprime portfolio remaining in
0.3% - 0.6% +1% +2%
same risk tier (High Risk segment)
Increase in delinquency rate of High Risk Segment 1.03X - 1.06X 1.1X 1.2X
Deterioration in net flow rates for all delinquency
4% - 7% 10% 20%
buckets
Above simulations carried out individually for home loan, LAP, auto loan, personal loan and credit card
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 46Asset quality for unsecured products is likely to be impacted
more severely than asset backed products
Product Impact Key Dynamics
• Adverse impact on consumers financial situation
Home Loans • Possibility of non-payment for under-construction home loans
Low High • Highest payment priority
• Shutdown of businesses / Slowdown of orders
LAP • Irregular cash flows / poor churning
Low High • Emergency credit line / sub-ordinate debt to small businesses
• Slowdown of cab services and car rental businesses
Auto Loans
• Migration of drivers to their hometown
Low High
• Job losses / Lay-offs / Pay-cuts
Personal Loans • Recent acquisition by NBFCs / FinTechs from high risk customers
Low High • Increase in loan stacking behavior
• Job losses / Lay-offs / Pay-cuts
Credit Cards • Least payment priority
Low High • Alternate and convenient payment option
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 47The impact on individual lender’s portfolio will also depend on
the risk management practices adopted by that lender
Origination growth
Slower pace of growth may lead to
increase in delinquency levels –
“denominator effect”
Collection practices Profile of existing consumers
Collection prioritization models and Acquisition of high risk consumers
cohesive treatment strategies in past, age profile, income, etc.
Asset Quality
Portfolio monitoring Current portfolio mix
Use of behavior scorecards and Open market acquisitions, sourcing
early warning systems from DSA, collateral coverage
Credit models
Use of risk models and data
analytics in credit underwriting
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 48To summarize:
• Ascertaining the impact of COVID-19 on asset quality is a complex picture dependent on
number of interlocking factors like consumer credit scores, collection roll rates and payment
hierarchy
• A wider analysis of these factors predicts that asset quality will likely be impacted most for
personal loans and credit cards with home loans and auto loans experiencing less of a shift
• In these difficult times, lenders need to actively monitor their portfolio and implement analytics
driven risk and collection management practices to minimize impact of any potential risk
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 49Key implications from findings for lenders to consider
Future Readiness Lending Strategy Infra
Risk Management
• Innovate and redesign • Decide on the choice of • Use of risk models and data
distribution channels customers (open market / analytics in credit underwriting
• Reconsider the customer existing) • Segment customers basis
management framework • Evaluate partnership models their credit behavior
• Facilitate seamless customer (co-lending / co-origination) • Monitor portfolio using
onboarding • Leverage on digital sourcing behavior scorecards and early
• Digitize and automate internal channels earning tools
operations • Decide on the right product • Implement collection
mix (secured versus prioritization models to
unsecured) maximize recoveries
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 50Thank
Thank You!
vDisclaimer
This Presentation is prepared by TransUnion CIBIL Limited (TU CIBIL). This Presentation is based on
collation of information, substantially, provided by credit institutions who are members with TU CIBIL.
While TU CIBIL takes reasonable care in preparing the Presentation , TU CIBIL shall not be responsible
for errors and/or omissions caused by inaccurate or inadequate information submitted to it by credit
institutions. Further, TU CIBIL does not guarantee the adequacy or completeness of the information in
the Presentation and/or its suitability for any specific purpose nor is TU CIBIL responsible for any access
or reliance on the Presentation and that TU CIBIL expressly disclaims all such liability. This Presentation
is not a recommendation for rejection / denial or acceptance of any application nor any recommendation
by TU CIBIL to (i) lend or not to lend; (ii) enter into or not to enter into any financial transaction with the
concerned individual/entity. The user should carry out all the necessary analysis that is prudent in its
opinion before making any decisions based on the Information contained in this Presentation. The use of
the Presentation is governed by the provisions of the Credit Information Companies (Regulation) Act,
2005, the Credit Information Companies Regulations, 2006, Credit Information Companies Rules, 2006.
No part of this presentation should be copied, circulated, published without prior approvals.
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 52You can also read
