The main challenge of this use case is to predict whether the customer will become delinquent or not. The model has to be built for both new customers and existing customers. The delinquency problem causes the bank to incur loss like operations cost, cash rotation etc. The solution has to address multiple solutions.
We developed the model and deployed using Machine learning and deep learning algorithms and few other deployment tools. By analysing the customer demographics and few other features model for both existing and new customer has been built. The complexity level for existing customers is high than new. All those complex issues are solved with our optimized model.
Artificial intelligence (AI) solutions provide proactive algorithms and models to predict and prevent delinquency and default. Using supervised and unsupervised learning, AI can track borrowers’ purchasing and payment trends to predict future problems. Based on lenders’ actual data, the system will send notifications when customers’ behaviours show negative change—late payments, making only minimum payments, and so on.
This optimized AI model helped the bank to identify the delinquent and default customer at the earliest stage with good accuracy. This helped them to not to incur any loss which can be caused from many factors.
