Cerebell.ai gives smaller banks a chance

Machine learning is an incredibly powerful tool, but one which normally requires data science and programming expertise which smaller banks don’t have and can’t afford. Cerebell.ai aims to remedy this by creating banking AI as a service.

Benefits of Banking AI as a Service

Key use-cases for machine learning

Machine learning can be used to predict which customers are dissatisfied and about to leave you for a competitor, using transaction data and sentiment analysis of communications.

By distinguishing between absent-minded and financially distressed customers, the bank can focus its resources on dealing with those who have long-term payment problems.

Reduce costs by automating high-volume repetitive customer queries, for example those involved in account application processes or AML/KYC updates.

Machine learning can greatly improve credit scoring, by increasing the number of variables or adding additional data sources – allowing you to reduce losses, increase volumes, or both.