Financial institutions increasingly deploy AI in fight against fraud

Artificial intelligence (AI) and machine learning (ML) are proving invaluable allies in the battle against fraud. A new report details that 70% of financial institutions are now deploying these technologies to guard against financial malpractice. This pivot towards AI and ML reflects a growing unease within the sector, as 40% of organisations acknowledge an increase in fraudulent incidents.

The 'Financial Institutions Revamping Technologies to Fight Financial Crimes' survey uncovers a trend towards tech innovation in the fight against cyber threats. Organisations now largely turn to a blend of in-house operations, third-party suppliers, and emerging technologies to secure their own operational integrity and customers' safety.

The study also provides insight into the specific defensive technologies employed, showing that 90% of respondents use fraud prevention application programming interfaces (APIs), while 80% turn to adaptive and web-based multifactor authentication.

Perttu Nihti, Chief Product Officer of Basware, highlighted the enormous pressure on financial institutions, especially against large-scale scams like vendor impersonation. He suggested that "an automated defence against fraud using AI and ML is essential for financial institutions, especially the CFOs, who are ultimately accountable for any errors."

Nihti expanded on the capability of AI to significantly enhance the accuracy of fraud detection by analysing huge volumes of data for suspicious activity. "AI algorithms can be trained to minimise false positives, which limits the number of legitimate transactions that are mistakenly flagged as fraudulent", he noted. Importantly, this supports institutions to accurately identify real threats without compromising legitimate transactional activity.

Nihti also hinted at the strategic value of third-party collaborations for CFOs grappling with the surge in fraudulent activity. The deployment of AI and ML solutions through partner organisations effectively 'shares the compliance burden', ensuring that evolving mandates and regulations are robustly managed and the risk of fraud mitigated through high-tech measures.

Institutions tend to rely heavily on external tech support for vital fraud alert technologies. Typically, less than half of these alert systems are developed in-house. Instead, 30% of institutions develop over half of their systems with external support, and only one-fifth construct their alerting tools entirely internally. Such data underscores the valuable role of AI and ML expertise in the ongoing struggle against fraud.

The shift towards leveraging artificial intelligence and machine learning technologies marks a pivotal moment in the ongoing battle against financial fraud. As financial institutions grapple with increasing malpractice incidents, adopting AI and ML represents a proactive response to evolving cyber threats.

The collaborative approach, blending in-house capabilities with external expertise and innovative technologies, underscores the industry's commitment to enhancing security measures and safeguarding operational integrity and customer trust. The strategic integration of AI and ML will continue to play a vital role in fortifying defences, enabling financial institutions to stay ahead in the relentless fight against fraudulent activities.