Neil Kelly
Managing Director, Industry Consulting in Financial Services
NTT Data
Technology changes, like AI and cryptocurrency, have made organized crime networks more powerful and more sophisticated.
These technologies have introduced several new threats, including AI-driven fraud, bot-net driven attacks, automated scam networks and using connected devices for financial crime.
Additionally, where AI is revolutionizing numerous industries, malign actors are increasingly using AI to carry out hacks, conduct fraud, create deepfakes for extortion, spread misinformation and execute cyber-attacks at massive scales.
For example, 49% of firms globally reported encountering deepfake frauds, a 10x increase from previous years. Further bot nets, have empowered bad actors to massively scale financial crime activities, continually looking for the weakest links in the system.
The next frontier for criminals is developing AI agents capable of operating independently, identifying and exploiting vulnerabilities without human oversight.
It is evident that this rapid evolution, coupled with accelerated adoption of these new technologies by criminal elements is outpacing existing frameworks and controls, making it difficult for financial institutions to trace non-human actors and detect and prevent financial crime effectively.
Combating “Fire with Fire”
It is not sustainable for organisations to continue to adopt a reactive, siloed approach – instead, a pro-active, enterprise led multi-faceted approach that integrates advanced technology, robust governance, and continuous innovation is necessary to stay ahead of the evident challenges. This multi-faceted approach should consider:
1. Leveraging AI and machine learning for Detection
One of the most effective ways to counter AI-driven fraud and automated scam networks is by leveraging AI and machine learning (ML) technologies for detection and prevention. Organizations can implement AI-based platforms to reduce false positives, enhance payment fraud detection and prevent fraud attempts. These platforms can analyse vast amounts of data in real time, identifying patterns and anomalies that may indicate fraudulent activities.
2. Enhancing Identity Verification
To combat deepfake and synthetic ID fraud, organizations should enhance their identity verification processes. This can be done by using digital identity wallets, like the European Digital Identity Wallet (EUDIW) under eIDAS 2.0. These wallets let people decentralize their identity. Additionally, automating document scanning and chip-based authentication using optical character recognition (OCR) and near-field communication (NFC) can expedite the Know Your Customer (KYC) process and improve accuracy.
3. Cross-Industry Collaboration and Data Sharing
Collaboration across industries and data sharing are crucial in the fight against financial crime. Organizations should establish partnerships with other financial institutions, law enforcement
agencies and regulatory bodies to share information and best practices. This collaborative approach can help identify and mitigate emerging threats more effectively.
4. Adopting blockchain for Transparency
Blockchain technology can be a powerful tool in enhancing transparency and traceability in financial transactions. By adopting blockchain solutions, organizations can create immutable records of transactions, making it more difficult for criminals to obscure illicit financial flows. This technology can also facilitate the detection of suspicious activities and improve compliance with regulatory requirements.
5. Regulatory compliance and model validation
Ensuring compliance with regulatory frameworks is essential in countering technology disruptors. Organisations must establish robust governance structures and model validation processes to ensure that their AI and ML models are compliant with regulations. This includes setting up internal committees for AI model governance and implementing responsible data use frameworks to quantify the impact of false outputs.
6. Addressing Emerging Threats
Organizations must stay ahead of emerging threats by continuously monitoring and adapting to new technologies used by criminals. This includes investing in advanced analytics to identify trends, patterns, and anomalies in financial crime, as well as developing specialized investigative teams with expertise in handling complex fraud cases. This could also include implementing hyper-automation with AI, RPA and NLP to automate fraud alerts and recognize new fraud patterns.
Conclusion
In conclusion, countering the technology disruptors adopted by organized criminal networks requires a comprehensive and proactive approach. By leveraging AI and ML technologies, enhancing identity verification, fostering cross-industry collaboration, adopting blockchain solutions, ensuring regulatory compliance and addressing emerging threats, organizations can strengthen their defences and stay ahead in the fight against financial crime.
If you found this blog insightful and are interested in exploring how to meet ‘fire with fire’ we’d love to continue the conversation. Reach out to learn more and discover how you can strengthen your organization in dealing with your financial crime challenges.
Neil Kelly is Managing Director, International Consulting at NTT DATA who were lead sponsor at EAFC25.
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