Retail Banking Net Financial Impact Analyzer

Context
A retail bank needed a robust scoring method to optimize offers for both new and existing clients, combining marketing (e.g., propensity-to-buy) and risk factors (e.g., probability of default).

Engagement
The team developed customer segmentation, propensity-to-buy models, and calculations for net financial impact (NFI) to identify the most profitable product offers per client. We conducted a champion-challenger test to evaluate performance.

Results
The new models increased response rates in the test group fivefold compared to the control group. Personalized loan offers, optimized for profitability and client risk appetite, significantly boosted the bank’s performance.

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Fig 1: Customer Segmentation

Fig 2: Probability-to-default survival model

Fig 3: Probability-to-default survival model

Fig 4: Customers and predicted -best offers with expected profitability > 0 based on PtB, PD, LGD, EAD, and gross profit

Fig 5: Propensity-to-buy model

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