In today’s intricate financial landscape, where the digital realm converges with economic activities, the escalating prevalence of financial crimes presents a significant challenge. The year 2022 witnessed an alarming $5 billion in fines imposed on institutions for failing to thwart these illicit activities — an astounding 50 per cent YoY increase. Organisations experienced a 3 per cent reduction in turnovers due to FinCrime and FinCrime compliance issues, tallying up to a staggering $274 billion in 2022.

Banks grapple with several pivotal challenges like disparate systems and redundant processes for customer onboarding, customer due diligence (CDD), and risk assessment present significant hurdles.

The persistence of outdated practices like manual handovers compounds inefficiencies in anti-FinCrime efforts. Lack of efficient change management leads to banks being unable to keep up with constantly evolving FinCrime regulations.

Advancement in AI has invariably led to scammers utilising the technology to conduct financial crimes on an unprecedented scale. Deepfakes and AI are set to drive $1 trillion in financial fraud and crimes as the technology enables scammers to lower costs and increase reach towards a wide pool of consumers.

AI is being used to ‘turbocharge’ fraud, and despite heavy investment in fraud detection, consumers lost upwards of $8 billion last year due to FinCrimes in the US alone. Hence, it is critical for regulators and banking community having consensus, collaborate, and update processes that can tackle AI-fuelled crimes.

The possible road ahead

Embracing an AI and data analytics-led approach for both first and second lines of defence can prove invaluable. AI-enabled first line of defence would help with predictive analysis, pattern identification, hypothesis validation, and new model creation.

Adopting a 360-degree centralised platform approach fully integrates internal and external systems and helps track both internal and external FinCrime attempts. A centralised, platform approach can result in not only eliminating current siloed approaches and operational redundancies to prevent financial crime by at least 50 per cent but also bring various aspects of financial crime prevention under a unified function for effective monitoring, prevention, and remediation.

Housed by a library of AI models, rules engine, case management workflow, and intelligence and knowledge repository, this central FinCrime prevention would enable real-time detection of suspicious activities, creating the best first line of defence in a bank. It enhances the second line of defence using AI, rules engines, traditional data techniques, and an intelligence repository.

The writer is Global Head of BFSI, Experion Technologies