We help our clients make sense of the data they possess and creatively use that data to underwrite better, sell more, collect more all the while making a direct impact to their profits.
This is one of our most sought-after programs. We work with our clients to build predictive analytical solutions across credit scoring, behavioral scoring, collection scoring, next-best product forecasting and custom analytics solutions. Within custom analytics we work with available data to answer any business question. Our teams also assist our clients in the design of the data warehouses and in choosing the right data analytics tools. Our data scientists work along wise our banking specialists to define, refine and engineer the features used in our data models. All our programs involve a certain level of knowledge transfer to our client teams and validation of our models over time.
Examples of our Work
- Our client bank had traditionally been underwriting over 55% of all unsecured small business loans in that South Asian country. The bank followed a cash flow based underwriting approach but did not trust the data they had captured in their files. This reflected in a 90dpd of ~13%. Our team used a novel approach in collecting data from a sample of a single segment of customers and designed an underwriting scorecard with a Gini of 71%. The client deployed this scorecard after a brief pilot period and post two years of using the scorecard the delinquency is 0.5% with no reduction in the approval rates of over 80%.
- We developed an enabler for the field sales team at one of our large non-banking finance clients in India for their commercial vehicle portfolio. We analyzed their existing clients and data and arrived at an upsell scorecard, which mimicked the propensity of the existing client to purchase further vehicles. Sales RMs who used the scorecard performed 23x better than the Sales RMs who continued meeting and pitching to clients the traditional way.