Credit Risk Scoring in BFSI
It takes years of experience and dedicated work to judge a borrower’s risk of default. Not only is this process inefficient but it also can’t be implemented on a real time basis for credit transactions that require much shorter turnaround time in this competitive environment.
A credit risk scoring engine based on AI is developed to predict borrower’s probability of default. So, when a new customer comes in with a credit need, this credit scoring engine takes input in the form of borrower’s past financial transactions and current credit requirements to give a credit score in real time. This helps the creditor to decide on the risk and return value proposition for this particular transaction in real time, quickly and accurately.
A number of AI models are built and then the best suited for your case is selected using test dataset results to develop the credit scoring engine. Given our focus on interpretability of models, the logic behind the credit score can be easily understood by the credit risk assessors at your organisation. In fact, our models, at places, have been customised to accommodate the domain specific inputs from the credit assessors. So, this engine can be used to complement as well as substitute the current credit scoring process at your organisation.