With the creation and adoption of new AI technologies reaching warp level speed, it is becoming more apparent than ever that we are now truly living in the digital-dominant age.
Considering the explosion of new innovations hitting the market, this undoubtedly – as always accompanies innovations – means challenges will abound. In a time where AI is leading to fresh doubts for businesses and individuals alike around maintaining security, is AI-powered fraud detection the answer?
In the view of Madhu Nadig, co-founder of Flagright, financial crime is fast evolving – and this is leading to big challenges for traditional fraud detection.
He said, “Financial crime is evolving at a breakneck speed, and traditional fraud detection just isn’t enough anymore. Rule-based systems that rely on historical patterns are struggling to keep up with new, sophisticated attack methods, from synthetic identity fraud to deepfake scams. That’s where AI-powered fraud detection comes in.”
According to Nadig, AI could help predict fraud in addition to detecting it. By analysing massive datasets in real-time, AI can identify hidden patterns, flag suspicious transactions and adapt to new fraud tactics as they emerge.
A key question that remains for many firms though in the area is whether AI will be enough to keep FinTech’s secure.
“AI is a powerful tool, but it’s not a silver bullet,” said Nadig. “Fraudsters are also leveraging AI to outsmart defences, so the future of fraud prevention will require, amongst other things, federated learning and data sharing, better explainability and AI with human oversight.”
He remarked, “AI-powered fraud detection is the future, but only if it’s combined with real-time monitoring, strong governance, and adaptive learning models.”
Profound and positive
Jon Elvin, a strategic risk advisor at Saifr, remarked that AI is likely to have a ‘profound positive impact for security applications’ and will be able to help in a variety of ways.
He said, “First, it can grasp much larger data sets and bring risk/security context that can immediately be actioned by rule provisioning and human involvement.
“Second detection anomalies, trends, and intrusion penetration schema can migrate to AI-assisted decision making in strategic and tactical responses. As an example, AI is particularly keen on picking up on true changes of behaviour and insights such as the difference between a human typing a password or a bot actor.”
Elvin remarked that, ultimately, AI will continue to be a valuable tool in near-real time for risk and security and is projected to rapidly evolve. “However, as a cautionary thought, bad actors will also leverage AI to refine and hone their tradecraft, which makes the measures and countermeasure scenarios and evolution something to watch,” he concluded.
Double-edged sword
According to Fraser Mitchell, Chief Product Officer at SmartSearch, the rapid rise of AI continues to be a double-edged sword for compliance.
He said, “AI is increasingly being harnessed by fraudsters to conduct financial crime in a more sophisticated and convincing way. Take deepfake technology as an example, which is being deployed more frequently by bad actors and is progressively becoming more difficult to detect. As AI advances, compliance teams need to deploy equally innovative tools to stay ahead of cybercriminals.”
He highlighted that, on a more positive note, AI is already being harnessed by businesses to streamline customer verification, accelerate due dilligence and strengthen anti-fraud measures.
Mitchell remarked, “As the technology matures, AI-enhanced compliance technology will be able to take fraud prevention one step further. For instance, while a deepfake may fool human perception, AI can be used to check meta data for signs of tampering within documents or where voice recognition software is deployed.. Growing adoption of this type of cross-checking will make it far more difficult for fraudsters to slip through the net and insert fake identities into the system.”
Bringing transformation
In the opinion of Anthony Quinn, founder and CEO of Arctic Intelligence, security is at the forefront of any modern financial system, as fraud, cybercrime and financial crime threats evolve at an alarming and unprecedented pace.
He detailed, “Whilst clearly in its infancy, AI-powered fraud detection is already transforming the fight against financial crime offering faster, more accurate, and real-time fraud threat detection”.
Quinn noted, however, that using AI-powered fraud detection systems on their own is not enough.
He explained, “Firms must adopt multi-layered approaches including end-to-end encryptions, multi-factor authentication, human oversight to prevent bias and false positives, as well as fraud risk assessments and fraud risk awareness training”.
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