Today's fraud challenges are emerging in real time at the hands of more sophisticated criminals. That puts financial institutions in a tough position, tasked with devoting more time and resources to ensuring security while trying to deliver a frictionless customer experience. However, advancements in artificial intelligence (AI) are already easing the burden – and creating a more promising outlook for the future.
Using data analytics to detect fraudulent activity is not a new concept. Credit card companies, financial institutions and others have been using behavioral and predictive analytics to reduce risk and fraud for years. Emerging AI technologies take these capabilities to a new level, using greater automation, unsupervised learning and more sophisticated algorithms to strengthen fraud prevention.
Machine learning is a particularly promising element of AI, because it enables solutions to build on previous knowledge and evolve to face new fraud threats without being expressly programmed to do so. As these capabilities continue to advance, AI systems could be fine-tuned to deliver the best response for any situation, providing a higher level of security with fewer disruptions to the customer experience.
The speed and scale of AI-powered solutions – and their ability to look at data in a different way – enable financial institutions to successfully monitor for suspicious activity that would otherwise go unnoticed. Today, many organizations are using software to review data from limited sources using predetermined rules. AI enables more comprehensive and continuous monitoring of data and behavior across multiple channels.
By reviewing all account activity in real time, including ACH transfers, wires, credit, debit and bill payments, an AI system identifies behavioral anomalies and suspicious transactions faster and more effectively, which in turn creates a better customer experience. Aggregated account data can also be combined with market information to produce better insights that help detect emerging threats – enabling financial institutions to spot and prepare for threats they may otherwise not have known existed.
Adding biometrics to the mix, including voice, face and fingerprint authentication, strengthens AI strategies by creating an additional layer of protection to stop fraud before it begins.
As transaction speeds have increased in recent years, there's less time for approvals, making the automation and precision of AI more necessary than ever for financial institutions. Deploying real-time machine-learning algorithms can improve the accuracy and speed of decisions that help curb fraud.
As these algorithms are calibrated to become more accurate over time, look for false-positive fraud alerts to be greatly reduced. That's good news for security analysts who spend significant time reviewing alerts – and for customers whose payments can be delayed by extra research and approvals. And better accuracy in detecting fraudulent transactions means customers won't be interrupted (and potentially annoyed) by a text, call or email to validate legitimate transactions.
Freed from time-consuming reviews of false positives, banking employees can instead turn their attention to other, more efficient tasks, including finding solutions to complex threats. Human insight is an essential method for fine-tuning machine learning models to more accurately detect changing patterns of fraud. A financial institution's team can use information about today's fraud to enhance the next generation of automated fraud prevention.
A successful AI strategy is about bringing together human intelligence and machine intelligence. Financial institutions that embrace AI have the opportunity to better protect their organization and their reputation, while improving the customer experience. They can strike a better balance between automation and employee analysis, redirect their team to higher-value tasks and respond more quickly to new threats. More than simply offering a step forward in fraud prevention, AI has the potential to propel fraud strategies in a new direction.