The COVID-19 pandemic has ushered in unprecedented challenges for many. Individuals’ daily lives and businesses have been disrupted, and personal and organizational vulnerabilities have opened new doors for criminals to commit fraud.
According to the U.S. Federal Trade Commission, criminals are setting up online shops purporting to sell personal protective equipment (PPE) to consumers, but failing to deliver the goods. This can help criminals capture information like name, billing address, payment card information, and other personal identifiable information that can be used to commit fraud.
Now more than ever, financial institutions and fintechs need to be smart about which credit applications to approve and which to decline to protect both consumers and themselves from financial losses. According to Aite Group, financial institutions will spend approximately $781 million to combat credit card application fraud by 2022. As important as money is time. Javelin Strategy & Research found consumers spend 15 hours or more resolving matters if they fall victim to new account fraud.
Leveraging technology Innovation to Fight Application Fraud
Additionally, Javelin estimates application fraud costs financial institutions more than $10B a year and that doesn’t even include synthetic or other identity related crimes. It continues to be one of the biggest challenges for financial institutions since it is difficult to detect with traditional methods. Financial institutions must now look for new ways to use technology to turn the tide against new account fraud.
Artificial intelligence (AI) can help financial institutions dramatically reduce new account fraud. For example, some financial institutions have started using AI to gather insights from multiple data sources to inform the underwriting process. It can also help reduce the number of new accounts opened with stolen identities and protect consumers against synthetic ID or account takeover fraud. AI can be used to rapidly examine information, such as application velocity, fraud and suspicious activity, bankruptcy data across consumer identity elements, all while incorporating data from government agencies, third-party data providers, law enforcement agencies, and self-reported data from consumers.
This is a powerful combination that can be used to complement existing fraud prevention strategies many financial institutions use and fill in the current gaps and limitations in rules-based legacy fraud prevention systems that can create customer friction or false positives. More importantly, AI can empower financial institutions to manage risk in a way that quickly adapts as criminal behavior changes. Fraudsters are becoming more sophisticated by the day. It’s time for financial institutions to turn to advanced technology like AI and ML to help combat fraud by harnessing data and producing near-real-time results so financial institutions can make more informed decisions.
