The Bank is building on its analytics practice and investing in AI capabilitiesto implement various use cases across multiple segments, including Risk, Customer Service, Human Resources, and Operations. The Bankfs AI Center of Excellence worked with AWS to create a templatized framework to roll out use cases using Amazon SageMaker to quickly and easily build, train, and deploy machine learning (ML) models as part of the Bankfs larger AI roadmap.

RBL Bank will leverage Amazon Textract, a machine learning service that automatically extracts text, handwriting, and data from scanned documents, across the Bankfs Risk and Operations divisions to analyze documents such as financial statements, stock statements, and stock audit reports to predict default risk. Using ML allows analysts at RBL Bank to extract data and automate the handling of 2,500 documents per quarter. Other use cases already being tested within the Operations division include usingservices like Amazon Rekognition and Amazon Textract to automatically extract and match customer signatures and running fuzzy match algorithms to replace manual name match for various processes.