The Bank is expanding its analytics capabilities and investing in artificial intelligence (AI) to execute diverse use cases across multiple divisions, including Risk, Customer Service, Human Resources, and Operations. As part of Banks' bigger AI roadmap, the Banks AI Center of Excellence collaborated with AWS to design a templatized framework for rolling out use cases using Amazon Sage Maker to rapidly and efficiently build, train, and deploy machine learning (ML) models.

RBL Bank's Risk and Operations departments will use Amazon Textract, a machine learning tool that extracts text, handwriting, and data from scanned documents, to evaluate documents such as financial accounts, stock statements, and stock audit reports to identify default risk.

RBL Bank analysts can extract data and automate the handling of 2,500 papers per quarter using machine learning. Other use cases being evaluated in the Operations division include using services like Amazon Rekognition and Amazon Textract to automatically extract and match customer signatures, as well as employing fuzzy match algorithms to replace manual name matching in various processes.