The Next-Gen Technologies to Detect Fraud and Financial Crime Report 2024 highlights how banks, fintechs, and PSPs leverage AI and emerging tech to detect and combat advanced fraud.
Over the last two years, fraud detection and prevention in financial services has faced unprecedented challenges. Factors such as the uncertain economy, ongoing global conflicts, the wider adoption of diverse payment methods, and the development of AI – often used for deep fakes and automating cyberattacks – have contributed to the rise in fraud. According to NICE Actimize’s 2024 Fraud Insights report, authorised fraud grew by 22% in 2023, with the average fraudulent transaction amount surging by 43% to reach USD 3,222.
AI has become integral to various business segments within financial institutions, with applications primarily focused on financial reporting, accounting, and fraud detection. However, despite its many benefits, financial institutions continue to face challenges in AI implementation.
Additionally, compliance obligations are growing, often exceeding the capacity of many organisations. This strain is due not only to current regulations but also to new ones coming into effect, such as the AI Act, DORA, the new APP fraud requirements, and PSD3.
In this context, The Paypers’ Next-Gen Technologies to Detect Fraud and Financial Crime Report 2024 reveals the latest fraud threats and technological developments that financial institutions, banks, fintechs, and PSPs must be aware of to ensure safer digital transactions for businesses and consumers.
Top fraud challenges for FIs and how AI addresses them – NICE Actimize shares why AI is vital for tackling rising fraud challenges like scams, payment fraud, and identity fraud, improving detection and compliance while lowering operational costs for financial institutions.
The instant payments dilemma – EBA Clearing discusses the rise of instant payments in Europe, challenges in fraud prevention, and how Verification of Payee (VOP) checks can safeguard against fraud and misdirected payments.
The signals are there – let’s democratise them – ACI Worldwide payment experts agree that banks can use AI and shared risk signals to fight scams like APP fraud and deepfakes, collaborating on fraud detection without breaching customer privacy or regulatory compliance.
Fraud intelligence sharing with the EBA fraud taxonomy – the EBA Fraud Taxonomy enables PSPs to share data and fight fraud across Europe, creating a unified, pan-European framework for categorising and sharing payment fraud intelligence.
The FRAML approach – INFORM explains how the FRAML framework combines AI and machine learning to detect fraud and AML violations, improving detection accuracy while reducing false positives in fast-paced environments.
Solving the fraud puzzle with labelled data and AI – EverC uses AI, machine learning (ML), and large language models (LLMs) to detect high-risk ecommerce activity. Labelled data and well-structured questions are key to improving fraud detection accuracy.
Where to begin with AI in financial services – AI, especially Generative AI and LLMs, is reshaping financial crime prevention. NatWest's Colin Whitmore advises firms to combine scientific methods with business acumen to effectively implement AI solutions.
Acknowledgements: honouring experts who shaped the fincrime report
We would like to extend our heartfelt thanks to all our contributors to the Next-Gen Technologies to Detect Fraud and Financial Crime Report 2024, as well as to our key media partner, Qube Events.
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