The Client needed to enhance its pre-approved personal loans system, which is offered to clients via digital channels. A key component of this system is a risk engine that evaluates various data points—such as salary, credit history, and liquidity—to determine if a loan should be offered. The existing risk engine, built entirely in SQL, required features that would allow it to be configured for different credit products, including personal loans and credit consolidation.
Dariel’s team collaborated with a quantitative analyst to extend and enhance the risk engine. This involved configuring the engine to apply specific risk-based rules for each product type, ensuring flexibility and scalability. To improve efficiency, the team created an automated testing process using pre-prepared data packs, which allowed for the simulation of a wide range of scenarios, ensuring that the engine performed as expected across different product offerings.
Outcome: The configurability and extension of products offered increased the number of leads generated by target marketing to clients.
Tech:
- Netezza SQL
