Industry
Banking
Banking Services Transformation: Unlocking Exponential Value
HIGHLIGHTS
- Generative artificial intelligence (GenAI) has become a focal point in the global banking and financial services sector, with several institutions exploring how this technology can enhance their transaction monitoring capabilities, spot potential threats, and bolster their defenses.
- That said, fighting fraud requires more than just technology and the skills to deploy it. It takes human ingenuity and understanding, as well as problem-solving capabilities, to put in place truly effective controls.
- While GenAI shows promise in detecting, investigating, and preventing fraud, how effective it will be on the ground is a function of how well-rounded and comprehensive the design and the deployment strategy behind it is.
The GenAI promise
Back in 1950, a founding figure of modern computer science and artificial intelligence, Alan Turing surmised, "A computer would deserve to be called intelligent if it could deceive a human into believing that it was human". Well, looks like we shall see this happen rather soon, if not already. The pace at which generative artificial intelligence (GenAI) is progressing is unprecedented, to say the least, even for technology enthusiasts.
As newer fintechs emerge almost every day, GenAI is rapidly gaining importance not only as a means to improve operational efficiencies, but also as a key player in the fight against cyber attacks and financial crimes. Given that this technology goes far beyond traditional data analysis, it is actively shaping the future of fraud detection, particularly in the financial services industry.
Fraud detection has gone through an evolution of its own. From a rule engine based static system to a dynamic self-learning and modulating system which functions with certain degree of autonomy, fraud detection has come a long way due to recent technological developments, particularly the immense power of AI.
Two sides of a coin
As is the case with most technologies, it is the user that decides what the outcome is. So, where on one hand GenAI can help financial institutions keep fraud at bay, on the other, it can wreak havoc across the ecosystem. It is well known that fraudsters are increasingly using AI tools to scam the masses. Financial fraud these days is being perpetrated in a growing number of innovative ways, like harvesting hacked data from the dark web for credit card theft, using GenAI for phishing personal information, and laundering money between cryptocurrency, digital wallets, and fiat currencies. Many such financial crimes are lurking in the digital underworld as we speak.
In his Nobel prize acceptance speech in 2024, British-Canadian scientist and the Godfather of AI, Geoffrey Hinton spoke about the short term risks GenAI poses, such as being used by cyber criminals for phishing. He also hinted at a more longer term danger – a more existential threat from an all omniscient and all powerful sentient being which may not know any bounds – a dark prospect indeed, even though the chances of this happening may be less than 20% (which is still quite high).
So, now that we know the good, the bad, and the ugly that AI can unleash on us, financial services firms need to think a lot more comprehensively to be able to effectively use the technology for fraud detection. That’s because these sinister digital crimes need to be halted in their tracks in real time so that consumers and financial firms can prevent and minimize losses. Acting after the assault will hardly do anybody any good.
Using GenAI in fraud prevention
Real-time fraud and risk analysis: GenAI can create an exhaustive set of real-time scenarios in a considerably short amount of time, and test the resilience of the enterprise-wide system in a much more holistic way with speed and accuracy (not traditionally possible without significant burden on resources). They can also build rules based on historical fraud data analysis.
No more silos for fraud prevention: With frauds no longer a one-entity problem, a few leading banks and financial institutions in North America are coming together to form a consortium to share insights and have a shared action plan against systemic, serial, and relentless fraud attacks. For example, the Financial Services Information Sharing and Analysis Center (FS-IAC) is a global consortium where financial institutions share information about cyber threats and fraud patterns to protect the larger financial ecosystem. Another example is the Early Warning Services, LLC, a consortium owned by several US banks that focuses on fraud prevention and secure payment solutions. Early Warning Services is behind services like Zelle, which incorporates advanced fraud detection mechanisms.
Data augmentation: GenAI is also effective in creating synthetic datasets based on real-time data. By doing so, it can boost the attention signal for core detection tools, thereby making the model more robust and enabling it to detect not only on patterns, but also similar attacks that could be missed using traditional methods.
Conclusion
In conclusion, GenAI is a powerful tool for fraud detection, but its dual nature poses risks. While it enhances data synthesis and fraud detection techniques, it also fuels deception through deepfake technology. The response to handling fraud in the current age must be colossal, coordinated, agile, and well organized, globally. Research, action, and commitment to this critical aspect of the financial system should remain as one of the top priorities for leaders worldwide.
As financial institutions strive to stay relevant in an ever-evolving digital landscape, fraud remains a fast-moving and costly threat. GenAI offers a transformative shift – enabling a systemic approach to fraud detection that is intelligent, self-learning, and perpetually adaptive. GenAI, leveraged as a fraud detection tool, can be a stragetic pillar for enterprises that aim to be customer-centric and future-ready.
