Deep Pockets - Best Offers
Finastra Global Risk Practice
8 out of 10 SME loan applications are refused due to lack to history data. For the applications that are approved, the lead time is very long due to manual assessments and loan pricing.
On the other hand, retail customers get loans instantly with many price comparison apps providing easy access and great customer experience. We want to bring the retail experience to the SME sector which is currently underserved, especially in developing markets.
Deep Pockets App uses deep learning based optimization of the bank's balance sheet to instantly suggest 3 best offers given the ranges and constraints specified by the loan officer.
It allows the lender to socially steer the loans based on preferred line of business, products, customer segments. But at all times the Optimizer will meet the Risk-Return objective of the lender.
Deep reinforcement based learning is used to solve a constrained optimization problem over high dimensional parameters. Once the model is trained, the Optimizer can be used in real-time to suggest the best loan products.