A century ago, a storeowner could look a customer in the eye and determine whether to extend them credit or accept check payment. Scam artists were notorious. Certainly, the art of fraud detection has advanced more than a bit since, but so have attacks. Global estimates of digital transactions per day topped one billion in 2020. Businesses engaging in thousands or millions of daily sales must contend with ever-more-sophisticated fraudsters in a continual game of one-upmanship. Economic uncertainty adds fuel to fraudulent activity. The savviest lenders, retailers and other organizations are leveraging the combined force of AI-powered applications to effectively mitigate fraud and its effects.
Comprehensive AI applications – machine learning, decision automation and process automation – provide end-to-end fraud detection, determination and processing. User organizations enjoy cost-effective, accurate protection. And customers enjoy an easy shopping experience with minimal disruption.
Swift, accurate detection at scale – Machine learning (ML) provides dynamic, instant fraud detection. Businesses that engage in thousands, even millions of daily transactions must balance the goal of preventing fraud losses versus preventing false-positive alerts and associated loss of customer patronage. The combo of two models provides a tight net of just the right size:
- Supervised, explainable models flag suspicious activity based on all previous transactions and give data scientists detailed, updated user and behavior breakdowns to continually hone fraud profiles and increase detection accuracy.
- Unsupervised models flag transaction anomalies regardless of prior activity, enabling immediate detection of never-before-seen fraud attacks.
Immediate, appropriate determination – Supporting ML with decision logic facilitates swift action on flagged transactions. Using an integrated decisioning platform, non-technical users can indicate actions such as simple decline, routing to a specialist or police alert, among any other directions. Users can also deploy decision logic on the front end of transactions, for instance automatically declining known stolen credit card numbers, to further improve speed and accuracy.
Quick action to minimize impact – Integrating process automation closes the loop in financial-crime management and resolution. Once fraud is determined, the application takes over, canceling and reissuing credit cards, alerting credit reporting agencies, licensing authorities and criminal divisions and other urgent actions to limit any loss or suffering.
As the world grows smaller and business moves ever faster, the threat and impact of financial crime will surely grow larger. Comprehensive, user-accessible AI power gives businesses an accurate, easy, immediate and cost-effective way to defend against fraud while minimizing infringement on customer satisfaction.
Learn about InRule solutions for fraud detection and other advantages for lenders and financial services organizations. Visit here.
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