The ability to Identifying
a borrower’s ability to re-pay a loan is a mixture of Art and Science. Generally,
an underwriter will manually reviews the borrower’s credit history, collateral
value, credit score, grade and recommended system decision to approve or reject
a loan. I believe including Artificial Intelligence in the Underwriting process
will greatly enhance and simplify the process. I think time has come to include
AI to contribute to the Underwriting process.
Prescreen to Multiple
Counteroffers
Making
swift and accurate credit decisioning is the key for winning in the digital
market-place. Modern Origination Systems provide automatic technical analysis and
decision capabilities to assist in the underwriting process. This allows more
loan applications to be processed in less time and fewer human resources are required.
Scoring and auto-decision engines use following parameters, calculation and
empirical scoring to recommend a decision based on pre-configured rules.
·
Pre-Screening
o Customer,
Collateral Age, Base income
·
Financial Ratios Calculations
o Debt
to Income
o Payment
to Income
o Applicant
Stated Vs Actual Verified
o Before
and After New Loan
·
Income,
Liabilities, Assets and Net worth Calculations
·
Credit
Score Cards
·
Credit
History Evaluation
o Past Bankruptcy, Foreclosures, Liens and
Judgments
o Near Past Credit delinquencies,
repossessions, collections, or charge-offs
o Different types of credit account,
age, limits, usage and status
o Borrower's request for new credit in
recent past
This automatic analysis is adequate but not enough. It looks as at very small set of data. Based on my personal experience looking at multiple score cards instead of relying on a single credit score card increase the probability of identifying potential borrowers Instead of rejecting a credit applicant it’s better to provide counteroffers based on the credit potential Borrower may be eligible for the more credit or may require putting more down payment to qualify for an offer.
How does Artificial
Intelligence work?
Artificial Intelligence looks at thousands of variables to
analyze patterns and identify the risk profile of a potential borrower. AI combines numerous variables with iterative
processing and intelligent algorithms, allowing the software to learn
automatically from the patterns in the data. These data meta variables are fed
into multiple models, each with a different perspective. These models vote to
create the final score and the decision.
Portfolio
Performance Feedback
In addition to the origination
and credit data it is very important for the self-learning capabilities of the
models to feed current credit information and portfolio performance data to the
AI Models. These modern technologies are becoming fundamental while evaluating your
next Origination System (on-premise or
on-cloud) for the success and growth of your business. Feel free to contact me
for more information and questions.
About the Author:
Vinay Bhatia is an experienced product leader, passionate about building financial products that delight customers. He has an extensive background in technology, cloud and agile software development.
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