Consumer Lending Hub | Decisimo
In consumer lending, decision-making centers on several areas: anti-fraud, loan underwriting, credit limit setting, cross-/up selling, portfolio management, and debt recovery. A data-driven company can automate each area with the help of a decision engine.
If you are new to consumer lending and plan to set up a consumer lending business, you can learn more from our overview.
This hub covers topics related to decision-making across key areas of consumer lending.
Anti fraud
Preventing Identity Fraud- Setting up anti-fraud rules
- Device Fingerprinting for Lending App Fraud Detection
Loan underwriting
- How to set up the approval process
- Setting up eligibility rules
- Interest rate - Risk-Based Pricing
- Alternative data in credit scoring
- 7 Steps to Replace Manual Underwriting with Automated Decision Logic
Portfolio management
Data Analytics
Frequently asked questions
How should we check whether credit limit changes affect groups differently?
Compare customers whose limits changed with a suitable unchanged group, then break results out by relevant customer groups within the same score band and product. Track each group’s bad rate, utilisation, arrears and losses over a period long enough for repayment outcomes to emerge. Overall averages can hide a group whose bad rate is rising, and small samples can make apparent gaps noisy, so set minimum volumes and review triggers before changing limits again.
What should we test before adding alternative data to credit scoring?
Keep a data source only if it adds useful signal beyond the existing score and remains available and accurate for the applicants you assess. Test it on a later, out-of-time sample, compare approval and loss outcomes at the same lending appetite, and examine error rates across relevant groups. A source that improves ranking in historical data can still fail when coverage changes or reflect past access inequalities, so monitor it after launch and retain a fallback for missing data.
