Financial institutions (FIs) want to reduce fraud, but at the same time don’t want to create false positives, which is the flagging of legitimate customers as fraudulent. As a result, a growing number are turning to new solutions powered by artificial intelligence (AI) and machine learning (ML).
FIs’ adoption of AI and other advanced technologies roughly tripled between 2018 and 2021, from 5.5% to 16% of respondents to a survey, PYMNTS reported in the September 2021 Preventing Financial Crimes Playbook.
AI and ML offer major advantages over rules-based systems for banks and other institutions in the fight, including the fast and accurate identification of fraud before it occurs, reduction of false positives, elimination of manual labor costs and improvement of the customer experience.
AI and ML detect fraud by recognizing deviations from standard activity. They excel at fraud prevention because they can identify subtle trends in savvy cybercriminals’ constantly evolving approaches. This explains why more industry players, governments and auditors alike are adopting AI and ML for fraud prevention. Synchrony, for example, has achieved an over 90% accuracy rate with its AI anti-fraud ecosystem.
Preventing Fraud, Improving Efficiency
The FIs surveyed by PYMNTS that had already adopted AI identified the top five benefits, which are either directly or indirectly related to fraud monitoring and prevention. They cited being alerted to fraud before it happens (81%), the improvement of operational efficiencies (81%), the reduction of false positives (75%), the improvement of customer satisfaction and experience (63%) and the reduction of payment fraud (56%).
Some of these key benefits are core anti-fraud functions, while others relate indirectly to effective fraud prevention, because an accurate and seamless AI-based system will increase efficiency ensure a frictionless customer experience.
Reaching a Tipping Point
Only the larger FIs surveyed tended to have already adopted AI systems, however. PYMNTS found that 79% of FIs with more than $100 billion in assets said they were using AI versus just 4.5% in the $25 billion to $100 billion range, and none among those with less than $25 billion in assets.
Why? Among the firms that had not implemented AI systems, 72% cited regulatory problems, 59% cited the complexity of AI and 59% cited the higher data management costs of AI.
Most smaller firms already have plans to start using AI, however. Twenty-one percent said they either have already invested in AI systems and 72% plan to within three years. Among the latter group, 57% plan to invest in AI systems within 12 months.
These strong results suggest that AI systems have reached a tipping point in terms of interest among FIs. Companies that wish to remain competitive in the rapidly evolving fraud landscape — and detect fraud without generating false positives that drive away customers — will want to invest in these systems without delay.