retail credit outlook - transunion cibil · 2016 q1 2017 q2 2017 q3 2017 q4 2017 q1 2018 q2 2018 q3...
TRANSCRIPT
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 1
RETAIL CREDIT OUTLOOK
Anticipating and preparing for the
COVID-19 impact on retail credit market
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 2
Key questions that the market is asking, and what we hope to
cover in this presentation
Key implications for lenders1How might the operating
environment change for lenders?
2What can be the potential impact
on retail credit growth?
What may be the likely impact on
asset quality? 3
Future Readiness
Lending Strategy
Risk Management
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 3
Operating Environment
How COVID-19 and ensuing containment and relief measures might change
the lending ecosystem?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 4
COVID-19 has affected more than 6 million people across 210
countries around the world
Source: Our World in Data
As on 2nd June 2020
COVID-19 Confirmed Cases
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 5
Spread of COVID-19 in India has been relatively slower
compared to other major countries affected by the pandemic
1,000
10,000
100,000
1,000,000
1 11 21 31 41 51 61 71 81
# C
onfirm
ed C
ases
(Log s
cale
)
Days since the 1000th confirmed case
Number of Confirmed COVID-19 cases
Source: Our World in Data
USA
RussiaUK
Spain
Brazil
India
As on 2nd June 2020
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 6
The phased lockdown implemented to curb the spread of
COVID-19 has social, financial and economic implications
Social
• Loss of job for daily wage earners and migrant workers
• Migration of labor leaving them struggling to make ends meet
• Anxiety as a result of social distancing, uncertainty, fear of economic recession
Financial
• Impact on consumers’ financial position on account of pay cuts / layoffs
• Revenue reduction for companies leading to potential liquidity challenges for
businesses and solvency crises
• Falling stock prices and widening of credit spreads
Economic
• Hit on consumption demand – Decrease in consumption, reduction in
discretionary spending, postponement of new investments
• 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 | 7
Labor market conditions have been impacted severely
42.8% 43.0% 42.3% 42.6%38.2%
7.0% 8.2% 7.2% 7.8%
23.5%
0%
10%
20%
30%
40%
50%
May-1
9
Jun-1
9
Jul-19
Aug-1
9
Sep-1
9
Oct-
19
Nov-1
9
Dec-1
9
Jan-2
0
Fe
b-2
0
Mar-
20
Ap
r-20
May-2
0
Pe
rcen
tage
Labor Participation and Unemployment
Labor Participation Rate Unemployment Rate
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 8
Consumer sentiment has taken a hit as a result of worsening
economic conditions
108.3 105.7 105.9 105.3
30.9
0
20
40
60
80
100
120
May-1
9
Jun-1
9
Jul-19
Aug-1
9
Sep-1
9
Oct-
19
Nov-1
9
Dec-1
9
Jan-2
0
Fe
b-2
0
Ma
r-20
Apr-
20
May-2
0
Index V
alu
e
Consumer Sentiment Index
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 9
The pandemic has brought nearly all activity to a standstill,
with the effect more pronounced in the services sector
52.7
51.4 51.2 54.5
30.850.2
52.4 52.7 57.5
12.6 0
10
20
30
40
50
60
70
May-1
9
Jun-1
9
Jul-19
Au
g-1
9
Sep-1
9
Oct-
19
No
v-1
9
Dec-1
9
Jan-2
0
Fe
b-2
0
Mar-
20
Apr-
20
Ma
y-2
0
Index V
alu
e
Purchasing Managers’ Index (PMI)
Manufacturing PMI Services PMI
Source: CMIE
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 10
Revenue of most businesses has seen a drop and may fall
further in the short term
0
200
400
600
800
1,000
1,200M
ar-
19
Apr-
19
May-1
9
Ju
n-1
9
Jul-19
Aug-1
9
Sep-1
9
Oct-
19
Nov-1
9
Dec-1
9
Jan-2
0
Fe
b-2
0
Mar-
20
INR
Bn
GST Collections
Source: Government of India
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 11
Consequently, India’s economic growth is expected to contract
in 2020
7.5%8.7%
5.6%4.1%
6.2%
1.1%
-12%
-8%
-4%
0%
4%
8%
12%
Q42016
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
Q32019
Q42019
Q12020
Q22020
Q32020
Q42020
YoY
Gro
wth
Rate
Growth in Real GDP
GDP Actual GDP Forecast (pre COVID-19) GDP Forecast (post COVID-19)
India’s GDP estimates have been revised for FY18, FY19 and FY20
~INR 24
trillion(current
prices)
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 12
The Indian government has announced an economic relief
package of INR 20 trillion under “Atmanirbhar Bharat Abhiyan”
ReformsLiquidity
InfusionInfra
Infrastructure
Push
Helping Stressed
Businesses
• New definition of
MSMEs
• Agri marketing reforms
• Coal, minerals
liberalization
• Higher FDI in defense
production
• Airport, DISCOM
privatization
• New policy for PSUs
• Reduction in CRR
• Collateral free loans /
subordinate debt /
equity for MSMEs
• Special liquidity and
partial guarantee for
NBFCs
• Funds for DISCOM
• EPF support
• INR 2.3 trillion extra
credit to farmers
• Affordable rental
housing for migrants
• Extension of middle
income housing
scheme
• Agri infrastructure
fund
• Higher VGF for social
infrastructure
• Relaxation in
insolvency law
• Expediting tax
refunds
• Funds for stressed
NBFCs
• Moratorium on loan
repayments
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 13
India's economic relief package, intended to help spur near
term growth and spending, is amongst the largest in the world
0%
5%
10%
15%
20%
25%Japan
US
Austr
alia
Can
ada
India
Bra
zil
South
Afr
ica
UK
Fra
nce
Tu
rkey
Germ
any
Italy
Indo
nesia
Arg
entina
Russia
Saud
iA
rabia
Chin
a
South
Kore
a
Mexic
o
% o
f G
DP
Economic Relief Packages by G20 Countries
Source: IFC, CSIS, VOX
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 14
The pandemic has created operational challenges for lenders
to re-consider and potentially change their operating model
Distribution
• Realigning branches and loan centres to support social distancing guidelines
• Adjusting working hours, staffing mix and times to avoid contamination
• Encouraging customers to use digital channels
• Automating routine service requests (chatbots, etc.)
Customer
Management
• Providing temporary relief to customers without impact on credit history
• Creating customer awareness on support and relief measures
• Addressing evolving needs of customers
• Segmenting customers based on their credit behavior
Internal
Operations
• Automating regular tasks and processes
• Rebalancing workload across operational sites
• 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 | 15
• 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
To summarize:
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 16
Credit 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 | 17
Retail credit growth, which is a reflection of wider economic
activity, has contracted in the last two years
0%
3%
6%
9%
12%
0%
10%
20%
30%
40%
Q12015
Q32015
Q12016
Q32016
Q12017
Q32017
Q12018
Q32018
Q12019
Q32019
Q12020
YoY
GD
P G
row
th R
ate
YoY
Reta
il C
redit
Bala
nces G
row
th R
ate
Growth in Retail Credit Balances and Real GDP
Retail Credit GDP
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 loanSource: TransUnion CIBIL consumer database,
Oxford Economics
Q1 2020 retail credit growth number is as of February 2020
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 18
Lending activity has been impacted severely, with some
revival seen in May
0
50
100
150
200
250
Apr-
18
May-1
8
Jun-1
8
Jul-
18
Aug-1
8
Sep-1
8
Oct-
18
Nov-1
8
Dec-1
8
Jan-1
9
Fe
b-1
9
Mar-
19
Apr-
19
Ma
y-1
9
Jun-1
9
Jul-
19
Aug-1
9
Sep-1
9
Oct-
19
No
v-1
9
Dec-1
9
Jan-2
0
Fe
b-2
0
Mar-
20
Apr-
20
May-2
0
Indexed V
olu
mes
Inquiry and Origination Volumes
Inquiry Originations
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
Index: April-18 = 100
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 19
Credit growth is a function of demand and supply factors
Credit Growth
Demand for Credit
(Inquiries)
Supply of Credit
(Originations)
Ability to Lend
(Liquidity)
Willingness to Lend
(Risk aversion)
Analyzed data pertaining
to previous crisis
Relationship between macro-
economic variables and
inquiries for key products
Money Supply in the economy
Changes in approval rates
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 20
The previous crisis represents an economic downturn scenario
that may help guide our direction during the current crisis
0%
2%
4%
6%
8%
10%
12%
14%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
YoY
Gro
wth
Rate
Growth in Real GDP
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 21
0
50
100
150
200
Q12007
Q32007
Q12008
Q32008
Q12009
Q32009
Q12010
Q32010
Q12011
Q32011
Q12012
Q32012
Indexed V
olu
mes
Growth in Inquiry and Origination Volumes
Inquiry Originations
Inquiry and origination volumes declined by almost 50% YoY
during the crisis period
Products considered: home loan, LAP, auto loan, personal loan and credit card
Source: TransUnion CIBIL consumer database
Index: Q1 2007 = 100
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 22
Demand for housing is closely associated with wealth creation
through the equity market
-60%
-30%
0%
30%
60%
90%
120%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
YoY
Gro
wth
Rate
Growth in Home Loan (HL) Inquiries and Share Price Index
HL Inquiries Share Price Index
Source: TransUnion CIBIL consumer database,
Oxford Economics
Correlation = 0.89
Share price index is the average value of BSE SENSEX
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 23
There is a linkage between overall industrial activity and
demand for loans against property (LAP)
-10%
-5%
0%
5%
10%
15%
20%
25%
-40%
-20%
0%
20%
40%
60%
80%
100%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
IIP Y
oY
Gro
wth
Rate
LA
P I
nquirie
s
YoY
Gro
wth
Rate
Growth in LAP Inquiries and Index of Industrial Production (IIP)
LAP Inquiries IIP
Source: TransUnion CIBIL consumer database,
Oxford Economics
Correlation = 0.75
The index of industrial production measures the output of the industrial sector of the
economy, which includes manufacturing, utilities, mining and quarrying
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 24
Private consumption and demand for auto loans move together
2%
4%
6%
8%
10%
12%
-50%
0%
50%
100%
150%
200%
250%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
PC
YoY
Gro
wth
Rate
AL I
nquirie
s
YoY
Gro
wth
Rate
Growth in Auto Loan (AL) Inquiries and Private Consumption (PC)
AL Inquiries Private Consumption
Source: TransUnion CIBIL consumer database,
Oxford Economics
Correlation = 0.78
Private Consumption is the value of goods and services consumed by households
and non-profit institutions serving households expressed in local currency
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 25
Household financial liabilities and demand for personal loans
are closely associated
10%
15%
20%
25%
30%
-200%
-100%
0%
100%
200%
300%
400%
500%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
HF
L Y
oY
Gro
wth
Rate
PL I
nquirie
s
YoY
Gro
wth
Rate
Growth in Personal Loan (PL) Inquiries and Household Financial Liabilities (HFL)
PL Inquiries Household financial libilities
Source: TransUnion CIBIL consumer database,
Oxford Economics
Correlation = 0.97
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).
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 26
Demand for credit cards, being a lifestyle payment product, is
connected with household wealth
12%
14%
16%
18%
20%
-100%
-50%
0%
50%
100%
150%
200%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
GH
W Y
oY
Gro
wth
Rate
CC
Inquirie
s
YoY
Gro
wth
Rate
Growth in Credit Card (CC) Inquiries and Gross Household Wealth (GHW)
CC Inquiries Gross Household wealth
Source: TransUnion CIBIL consumer database,
Oxford Economics
Correlation = 0.87
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)
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 27
The ability of financial institutions to lend can be determined
by money supply (M2) in the economy
0%
5%
10%
15%
20%
25%
-40%
-20%
0%
20%
40%
60%
80%
100%
120%
Q12007
Q22007
Q32007
Q42007
Q12008
Q22008
Q32008
Q42008
Q12009
Q22009
Q32009
Q42009
Q12010
Q22010
Q32010
Q42010
Money S
upply
(M2)
YoY
Gro
wth
Rate
Origin
ation B
ala
nces
YoY
Gro
wth
Rate
Growth in Origination Balances and Money Supply (M2)
Origination Balances Money Supply (M2)
Source: TransUnion CIBIL consumer database,
Oxford Economics
Products considered: home loan, LAP, auto loan, personal loan and credit card
Correlation = 0.70
Money supply (M2) includes cash in circulation, current account deposits as well as all
time-related deposits, savings deposits, and non-institutional money-market funds
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 28
Approval rates declined for all key products during the crisis
period indicating increased risk aversion
0%
20%
40%
60%
Home Loan LAP Auto Loan Personal Loan Credit Card
Appro
val R
ate
%
Products
Approval Rates during Crisis Period
2007 Q2 to2008 Q1
2008 Q2 to2009 Q1
2009 Q2 to2010 Q1
-16%
-28%
-22%
-30%-11%
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 29
Secured lending products are expected to see more pronounced
decline in demand
ProductMacro
Variable
YoY 2020
Forecast
Outlook for
DemandKey Dynamics
Home
Loans
Share Price
Index-11.0%
• Reduction in affordability
• Postponement of home purchases
• Drop in home prices / attractive offers by builders
LAP IIP -2.9%
• Lower manufacturing / services output
• Drop in real estate prices
• Need of finance to revive business
Auto LoansPrivate
Consumption-1.7%
• Reduction in discretionary spending
• Impact on travel and tour business
• Diminished ability and need to travel
Personal
Loans
Household
Liabilities+15.1%
• Need of funds to bridge personal finance gap
• Flexible product structure
• Greater access via digital channels
Credit
Cards
Household
Wealth+9.6%
• Increase in the need for digital payments
• Reduction in discretionary spending
• Postponement of lifestyle purchases
Low High
Low High
Low High
Low High
Low High
[Oxford Economics]
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 30
Liquidity may not be a challenge consequent to rate cuts and
other fiscal measures initiated by the regulator
0%
5%
10%
15%
20%
25%
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
Q32019
Q42019
Q12020
Q22020
Q32020
Q42020
YoY
Gro
wth
Rate
Money Supply (M2)
Source: Oxford Economics
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 31
Lenders are likely to tighten their credit policy and customer
selection norms to manage and mitigate risk
Product Willingness Key Dynamics
Home Loans• Backed by security, lower default probability
• Lower interest rates, reduced margins
LAP• Higher risk of default in smaller businesses
• Irregular cash flows may present assessment challenges
Auto Loans• Avoiding exposure to tour / travel segment
• Challenges in repossession and resale of vehicles
Personal Loans
• Unsecured in nature, increased risk of default
• Key product offering for many lenders especially FinTechs
• Higher margins, increased profitability
Credit Cards
• Revolving credit line which can be periodically managed
• Spending and behavior can be monitored
• Leveraging CASA / internal database for acquisition
Low High
Low High
Low High
Low High
Low High
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 32
• 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
To summarize:
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 33
Asset Quality
What may be the likely impact on stress levels for major products?
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 34
Portfolio delinquency rates have remained largely steady in
the last three years, with the exception of LAP
0%
1%
2%
3%
4%
5%M
ar-
17
Ju
n-1
7
Sep-1
7
Dec-1
7
Mar-
18
Jun-1
8
Sep-1
8
Dec-1
8
Mar-
19
Jun-1
9
Sep-1
9
Dec-1
9
Fe
b-2
0
% B
ala
nce in 9
0+
DP
D
Balance-level 90+ Delinquency Rate by Product
LAP
Auto Loan
Home Loans
Credit Card
Personal Loan
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 35
Impact on asset quality can be determined by analyzing
consumer scores, collection roll rates and payment hierarchy
Asset Quality
Consumer Risk
Scores
Shifts in borrower risk tiers
across product portfolios and
delinquency rates associated
with each tier
Collection Roll
Rates
Number of accounts
becoming newly delinquent
and flowing into subsequent
delinquency buckets
Payment
Hierarchy
The order in which
consumers prioritize
payments during times of
financial hardship
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 36
We looked at 6-month risk tier movement for non delinquent
consumers and their delinquency rates thereof
Risk Tier (t+6)90+ Balance DPD rate
(t+6)
Product-level
BalanceSubprime
Above
Subprime Subprime
Above
Subprime
Ris
k T
ier
(t =
0) Subprime
No
upgradeUpgrade High Risk Low Risk
Above
SubprimeDowngrade
No
downgrade
Very High
Risk
Very Low
Risk
Risk tier movements and DPD
rates can be simulated to
gauge the likely impact on
delinquency rates Subprime segment constitute a CV score of <=680
and above subprime a CV score of >=681
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 37
Share of portfolio in very high risk segment has increased for
credit cards and personal loans in the last one year
2%
4%
6%
8%
Q22016
Q32016
Q42016
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
% o
f B
ala
nce
Share of Portfolio in Very High Risk Segment
Auto Loan
Credit Card
Personal Loan
LAP
Home Loans
Source: TransUnion CIBIL consumer database
Very High Risk segment refers to those consumers who have moved
from above subprime segment to subprime segment in next 6 months
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 38
During the same time period, share of portfolio in low risk
segment has decreased for credit cards
1%
2%
3%
4%
5%
Q22016
Q32016
Q42016
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
% o
f B
ala
nce
Share of Portfolio in Low Risk Segment
Auto Loan
Personal Loan
LAP
Credit Card
Home Loans
Source: TransUnion CIBIL consumer database
Low Risk segment refers to those consumers who have moved from
subprime segment to above subprime segment in next 6 months
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 39
Delinquency rate in very high risk segment has moved up for
home loans and LAP in the last one year
0%
4%
8%
12%
16%
Q22016
Q32016
Q42016
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
% B
ala
nce in 9
0+
DP
D
Delinquency Rate for Very High Risk Segment
Credit Card
LAP
Personal Loan
Home Loans
Auto Loan
Source: TransUnion CIBIL consumer database
Very High Risk segment refers to those consumers who have moved
from above subprime segment to subprime segment in next 6 months
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 40
Analyzing bucket net flow rates and lagged flow to 90+ would
also help gauge the impact on 90+ delinquency rate
BucketOutstanding Balance (value) Net Flow Rates
T T+1 T+2 T+3 T+4 T+1 T+2 T+3 T+4
Current 100.0 102.0 105.0 107.0 110.0
1-29 4.0 5.0 5.0 6.0 6.0 5% 5% 6% 6%
30-59 2.0 3.0 3.0 4.0 5.0 75% 60% 80% 83%
60-89 1.6 1.8 2.2 2.5 3.0 90% 74% 83% 75%
90+ 1.3 1.5 1.8 2.1 2.4 94% 100% 95% 96%
Total 108.9 113.3 117.0 121.6 126.4 Lagged flow to 90+ is the
product of diagonal bucket
net flow rates90+ DPD 1.90% 2.40%
[Illustration]
Impact on DPD can
be calculated basis
lagged flow to 90+
Bucket net
flow rates
can be
simulated to
get lagged
flow to 90+
Balance in next delinquency bucket
(eg: 30-59) on time T+1Bucket net
flow rate Balance in previous delinquency
bucket (eg: 1-29) on time T
=1
2
3
4
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 41
Delinquency rate and lagged flow to 90+ move in same direction
which enables us to use one to predict the other
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
Q32019
Q42019
Rate
(%
)
Home Loan and Personal Loan Delinquency and Lagged Flow Rate
HL lagged flow
HL 90+ delq
PL lagged flow
PL 90+ delq
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 42
Lagged flow to 90+ has deteriorated for LAP and credit cards
in the last one year
0%
1%
2%
3%
4%
5%
6%
Q12017
Q22017
Q32017
Q42017
Q12018
Q22018
Q32018
Q42018
Q12019
Q22019
Q32019
Q42019
Perc
enta
ge
Lagged Flow to 90+ DPD
LAP
Auto Loan
Credit Card
Home Loans
Personal Loan
Source: TransUnion CIBIL consumer database
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 43
We studied payment hierarchy for two separate product
combinations, which represent different consumer groups
Credit
card
Home
loan
Auto Credit
card
Consumer
durable loan
Personal
loan
Significantly
different
populations
Study 2Study 1
• More affluent
• Higher income
• Lower risk
• Tighter lending criteria
• Lower income
• Higher risk
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 44
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
Jan-1
4
Mar-
14
May-1
4
Jul-14
Sep-1
4
Nov-1
4
Jan-1
5
Mar-
15
May-1
5
Ju
l-1
5
Sep-1
5
Nov-1
5
Jan-1
6
Mar-
16
May-1
6
Jul-16
Sep-1
6
Nov-1
6
Jan-1
7
Mar-
17
May-1
7
Jul-17
Sep-1
7% A
ccounts
in 9
0+
DP
D
Study Cohorts
Account-level 90+ Delinquency Rate
Credit Cards
Auto Loans
Home Loans
The study on payment hierarchy revealed that home loans
generally have the highest payment priority
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
Study cohort is the month for which the sample of consumers holding the
above products was picked (~300K per cohort)
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 45
0.0%
0.5%
1.0%
1.5%
2.0%
Jun-1
4
Au
g-1
4
Oct-
14
Dec-1
4
Fe
b-1
5
Apr-
15
Jun-1
5
Aug-1
5
Oct-
15
Dec-1
5
Fe
b-1
6
Apr-
16
Ju
n-1
6
Aug-1
6
Oct-
16
Dec-1
6
Fe
b-1
7
Apr-
17
Jun-1
7
Aug-1
7
Oct-
17
Dec-1
7
Fe
b-1
8
% A
ccounts
in 9
0+
DP
D
Study Cohorts
Account-level 90+ Delinquency Rate
CreditCards
ConsumerDurableLoans
PersonalLoans
Amongst unsecured lending products, personal loans generally
have the highest payment priority
Source: 2019 TransUnion CIBIL Payment Hierarchy Study
Study cohort is the month for which the sample of consumers holding the
above products was picked (~300K per cohort)
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 46
We simulated these risk related factors to determine the likely
impact on asset quality
Risk FactorsHistoric
Ranges
Base
case
Worst
Case
Increase in share of portfolio moving from above
subprime to subprime (Very High Risk Segment)0.5% - 0.8% +1% +2%
Increase in delinquency rate of Very High Risk
Segment 1.04X - 1.07X 1.1X 1.2X
Increase in share of subprime portfolio remaining in
same risk tier (High Risk segment)0.3% - 0.6% +1% +2%
Increase in delinquency rate of High Risk Segment 1.03X - 1.06X 1.1X 1.2X
Deterioration in net flow rates for all delinquency
buckets4% - 7% 10% 20%
Above simulations carried out individually for home loan, LAP, auto loan, personal loan and credit card
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 47
Asset quality for unsecured products is likely to be impacted
more severely than asset backed products
Product Impact Key Dynamics
Home Loans
• Adverse impact on consumers financial situation
• Possibility of non-payment for under-construction home loans
• Highest payment priority
LAP
• Shutdown of businesses / Slowdown of orders
• Irregular cash flows / poor churning
• Emergency credit line / sub-ordinate debt to small businesses
Auto Loans• Slowdown of cab services and car rental businesses
• Migration of drivers to their hometown
Personal Loans
• Job losses / Lay-offs / Pay-cuts
• Recent acquisition by NBFCs / FinTechs from high risk customers
• Increase in loan stacking behavior
Credit Cards
• Job losses / Lay-offs / Pay-cuts
• Least payment priority
• Alternate and convenient payment option
Low High
Low High
Low High
Low High
Low High
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 48
The 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”Profile of existing consumers
Acquisition of high risk consumers
in past, age profile, income, etc.
Current portfolio mix
Open market acquisitions, sourcing
from DSA, collateral coverage
Credit models
Use of risk models and data
analytics in credit underwriting
Portfolio monitoring
Use of behavior scorecards and
early warning systems
Collection practices
Collection prioritization models and
cohesive treatment strategies
Asset Quality
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 49
• 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
To summarize:
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 50
Key implications from findings for lenders to consider
Future Readiness Lending Strategy Infra Risk Management
• Innovate and redesign
distribution channels
• Reconsider the customer
management framework
• Facilitate seamless customer
onboarding
• Digitize and automate internal
operations
• Decide on the choice of
customers (open market /
existing)
• Evaluate partnership models
(co-lending / co-origination)
• Leverage on digital sourcing
channels
• Decide on the right product
mix (secured versus
unsecured)
• Use of risk models and data
analytics in credit underwriting
• Segment customers basis
their credit behavior
• Monitor portfolio using
behavior scorecards and early
earning tools
• Implement collection
prioritization models to
maximize recoveries
v
vv ThankThank You!
© 2020 TransUnion CIBIL Ltd. All Rights Reserved | 52
Disclaimer
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.