SPEED UP YOUR LOAN DECISIONING AND REDUCE RISK WITH AUTOMATED LOAN DECISION-MAKING
December 18, 2023
Modern decision-making systems enable fast and accurate loan origination and decisioning due to low human involvement and wide usage of automatic customer checks.
Digital Q Decision Support System allows banks to choose and set up any credit decisioning strategy based on the its specific decision-making rules, matrices for calculation of credit scores and other algorithms.
Such strategies are set ups and executed as a standard BPMN process and can support both fully automated decision making and a combination of automatic and manual steps, which can include the following:
- Customer pre-scoring (customer assessment by appearance, behavior, style of conversation).
- Initial customer and application screening against pre-configured stop factors (monthly income, living wage, employer verification, security checks, legal checks).
- Customer screening against internal and external watchlists (OFAC, Dow Jones, UN watchlists, list of terrorists, black lists, list of invalid passports, list of bankrupts, tax ID check, social security number check, criminal record check, wanted check, drugs check, etc.).
- Analysis of the internal credit history.
- Automatic search for duplicates of customer applications (both among current or previously submitted applications).
- Requests to Credit Bureaus, verification of the credit score (Credit Bureau’s score, FICO credit score)
- Collateral examination by the collateral manager.
- Automatic calculation of the customer’s credit score based on loan application details with the use of preconfigured scorecards.
- Generation of the decision matrix and alternative offers that match the customer’s credit score and loan requirements. Based on the results of checks, the underwriter can edit the requested loan parameters and offer more suitable loan options with the help of the decision matrix.
- Loan decision making and customer notification on the decision.
A decision matrix compares credit options and criteria that match the customer’s credit score and requested loan parameters (e.g., the interest rate, fees, monthly payment and total payments) and presents the information in the most convenient form.
If a customer does not meet the bank’s requirements for the requested loan, the bank can offer other loan options instead of declining the application. In this case, the system generates alternative offers, i.e. it adjusts requested loan parameters based on the customer’s credit score.
Using the decision matrix, the bank and the borrower can compare the following loan parameters:
- The maximum credit limit
- The maximum monthly payment
- Suitable credit products
- Interest rate
- Loan term
- Down payment
- Monthly payment.
The solution provides a convenient workbench for the Underwriter that supports manual decision making in case of borderline credit scores or specific loan requirements. The manual underwriting is required only in case of a controversial situation, when a potential borrow needs additional expert assessment. The workbench supports the following:
- Verification of the customer’s papers.
- Analysis of the customer’s creditworthiness.
- Analysis of the customer’s credit history.
- Manual decision making.
Low human involvement and wide usage of automatic customer checks help to speed up the overall decisioning process, reduce human errors and mitigate bad debt risks. With the end-to-end automation of the loan origination and decisioning processes, the whole loan origination and disbursement can be completed within just 10 minutes.
The solution provides APIs to accounting and external systems (core banking, credit bureaus, AML, customer screening) to ensure its easy integration into the bank’s business processes.
Learn more on Diasoft’s Loan Origination at https://diasoft.com/loan/