India Banking Fraud Survey, Edition IV has been saved
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Enhancing and complementing FRM teams with market intelligence and data analytics capabilities to ensure continuous monitoring
Currently, the alert definitions configured for EWS and fraud monitoring systems are primarily based on a customer’s transaction in the bank and financial statements.
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Enhancing the existing FRM function
The current traditional methods of fraud detection are plagued with the lack of centralised control, limited feedback from FRM processes, lack of risk-based monitoring, focus on detection than prevention, etc. To transform to a proactive, agile future and achieve a robust and comprehensive system, EWS and FRM needs to be integrated.
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Need to enhance EWS and FRM using AI/ML
Currently, most early-warning and transaction monitoring systems that generate fraud alerts are rule-based. When a certain threshold exceeds/certain conditions are met/recurrence is identified, the transaction is marked for further investigation.
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Banking industry in India at the cusp of a revolutionary change, driven by Artificial Intelligence (AI) and Machine Learning (ML): Deloitte India Banking Survey
Press Release
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