Transaction Monitoring Systems (TMS) used by financial institutions look at standard deviations, anomalies, and red-flag topologies. Being mostly rule based, they cannot assess a transaction in context of transaction patterns, customer risk score, past alert history, etc. These rules are designed to be overly cautious, as to not leave institutions open to a hefty fine should an instance of money laundering go unnoticed. Hence, more than 90% of the alerts generated by Transaction Monitoring System turns out to be false positive.
Our Financial Crime Management Solution has been built as a part of our Digital Banking Capability uses Hyper Automation – Artificial Intelligence, Machine Learning, RPA and a strong data foundation – created by way of a “Single Risk View of Customer”, to Identify True and False positive alerts and automate end-to-end processes.
Built on Microsoft cloud platform, our solution is designed to run large scale data and analytics workloads in a scalable and cost-effective manner.
• Azure Data Cloud Lake brings together all your big data from disparate sources across cloud and on-premises environments into one central place.
• Customer Insights comes equipped with the Power Platform. This makes it easy to import data from just about any source, and includes Power BI, Power Apps, Microsoft Access, Excel, JSON and REST APIs. It is easy to Map, Merge and Unify the data and create a “Single Risk view of Customer”
• Azure ML Studio offers an easy and flexible low code platform for building advanced machine learning solutions.
• Dynamics 365 is being leveraged to build a robust case management system
• Microsoft Power BI allows for creation and sharing of interactive data visualizations on Financial Crime Compliance data across different dimensions. It meets the need for a self-service and an enterprise data analytics on a single platform
• RPA based process automation to automate manual operational processes like Case Assignment, Managing inter/intra department communication, Filing SAR reports, etc.