Check out our Webinar recording on applying AI to Credit Risk Modeling

 Identifying high-risk customers is critical—and challenging. Jigyasa builds high-performing, stable scorecards using proprietary algorithms, best practices, and advanced machine learning. Our models accurately estimate Expected Loss and LGD, while incorporating business feedback for underwriting acceptance. We follow FDIC and OCC guidelines, provide full regulatory documentation, and ensure timely deployment.  

 Fraud patterns evolve rapidly, and static models alone can’t keep up—especially with the rise of systematic fraud. Jigyasa combines traditional predictive models with dynamic machine learning to detect anomalies and flag suspicious applications early. We strengthen detection using AI-generated synthetic data, enabling robust analysis even in sparse fraud scenarios. Our approach acts as an early warning system, reducing risk and improving fraud prevention strategies. 

 Jigyasa helps lenders improve recovery rates and reduce costs through advanced analytics. We predict accounts likely to become delinquent for proactive outreach, segment customers by risk and payment behavior to tailor strategies, and analyze historical data to recommend settlement offers. Our models rank accounts by recovery probability, enabling efficient resource allocation and maximizing collections performance. 

 Jigyasa helps financial institutions optimize marketing spend by identifying high-value prospects and tailoring campaigns using machine learning. We measure channel performance, ROI, and attribution across multiple campaigns, enabling smarter budget allocation. Our approach reduces costs for outbound and inbound efforts, improves conversion rates, and maximizes profitability through data-driven targeting and campaign optimization.