Fraud detection and prevention is a growing concern and a challenge for a majority of financial institutions (FIs) worldwide. As per industry research, major global FIs lose ~5% of their annual revenue due to fraudulent activities conducted through their products/systems. Some of the challenges faced by FIs in detecting fraud include high handling time to conduct investigation, multiple downstream systems, lack of real-tile view, functional silos, system deficiencies, high false positives, manual actions, multiple hand-offs, and lack of skilled resources to conduct investigations.
Fraudulent acts affect FIs institutions by impacting the bond between an institution and its customers. With evolving fraudulent techniques, FIs are struggling to improve their processes and methods to mitigate such risks. Our Fraud Detection & Prevention practice has domain experts delivering 24 x 7 global coverage for multiple clients. With our deep knowledge about the processes as well as our experience with global banks, we bring industry best practices by applying our proprietary Process Progression ModelTM (PPM) framework and help organisations to transform operating models, improve business performance, and standardise processes with reduced costs.
Infosys BPM is uniquely placed in driving process transformation by leveraging our cross-functional teams across consulting and operations as well as our homegrown product suite — Digital Chargeback solution. It consists of:
In addition, our Fraud Detection & Prevention practice delivers benefits to banks by:
Furthermore, we have strategic partnerships with global fintech/regtech companies in the compliance space across advisory, platform, and RPA/ML/AI providers, thus delivering the best, tailor-made solutions to meet client requirements.
Our Solution is a customised, holistic, end-to-end solution that delivers compliance requirements to financial institutions, from business consulting through the entire life cycle of product selection, implementation, maintenance, and day-to-day operations.
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