Lending solutions leverage on emerging technologies to simplify the lending process and to increase the accessibility of lending services. Lending solution encompasses functions like credit scoring, AI deployment, alternative lending solutions and intuitive mobile solutions for lending. The solution enables lending companies to perform credit scoring through the consumer’s digital footprint, allowing the financial institution to create accurate scorecards of consumers that the financial institution have limited information on. The solution increases the loan approval rate to 48% higher than traditional loan processing at 39% less risk, allowing financial institution to optimize their lending portfolio. The credit rating process is also shortened, from days to minutes, increasing the speed of loan approvals. Find out more at www.ey.com/sg/fintechhub. For enquiries, contact us via email at fintech@sg.ey.com.

1. Alternative credit scoring of underbanked
consumers
Case study
Context:
A local bank was facing difficulty in promoting
personal loans products to the underbanked
clients since they cannot score credit according
to existing credit scorecards being used by the
bank. More than 90% of new-to-bank applicants
were rejected under their existing decisioning
policy. The bank was seeking a solution that
turns clients' digital footprints into credit
scorecards.
Solution configuration:
• Thousands of data points, including call
history, contact, SMS history, calendar,
data from user’s internet browser and
geographical position
• Providing highly predictive behavioral
insights by analyzing users’ smartphone
data
• Flexible multiple scorecard integration
options: merge and parallel
• Low cost of risk by machine learning
applied in digital footprint analyzing
Client impact:
• Improved the number of loans disbursed for
underbanked customer personal loans
product with a delinquency increase of only
2.3%
• Fastened the decision-making time to one
minute, as compared with the number of
days taken in the traditional manual
process
Contact us
Varun Mittal
EY Global Emerging Markets FinTech
Leader
varun.mittal@sg.ey.com
Challenges faced by banks
Limited information to assess
credit-worthiness of clients
Unstable predictive power of
traditional application data
Long development time for new
credit frameworks
Expensive manual processes to
approve a personal loan
Turnkey and customized solution
Integrated
Software
development kit
(SDK)
Credit scorecard-
applied machine
learning
Big data
Generating highly
predictive credit
scorecards
through
customers’ digital
footprints
Customizing
scorecard based
on the financial
institution’s
characteristics,
target customer
segment and
products
Shortening credit
rating process
from days to
minutes
Simplifying the
loan application
process across all
channels, in
branch, online,
on mobile and via
direct sales
agents
BR refers to the percentage of default on loans.
AR refers to the percentage of loans approved, signifying the stringency on loan
criteria.
Alternative credit scoring comparison
48% higher approval rate 39% lesser risk
Approval rate (AR)
Badrate(BR)
BR: 7.9%
BR: 4.8%
AR: 74%
Traditional scorecard
Vendor scorecard
Website: www.ey.com/sg/fintechhub
Email: fintech@sg.ey.com
Sahil Gupta
EY ASEAN FinTech Manager
sahil.gupta@sg.ey.com

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