As financial institutions battle fraudsters, they still face enormous pressures to grow the business, deliver innovative services, and comply with strict regulatory requirements.
In an effort to get ahead of cybercriminals and meet compliance goals, finance institutions have continued to rely on traditional fraud management solutions to help them reduce fraud.
Unfortunately, according to risk analytics company OneSpan, these institutions are finding that traditional tools and technologies are no longer good enough, and they require a modern solution.
Traditional fraud solutions do very little to reduce fraud rates, it argues. According to Forrester’s Fraud Management Solutions Forecast, 2017 To 2023 (Global), spending related to fraud management solutions is expected to double in the next five years, partly because traditional solutions cannot keep up with agile fraudsters and their ever-changing tactics.
They simply cannot address the speed and scale of new fraud, particularly when combined with new business challenges, such as new and expanding digital channels, mobile banking, and regulatory requirements, the company warns.
Executives at OneSpan believe a new, modern approach to risk analytics is required that maintains compliance whilst tackling fraud, without pushing up operational costs.
Through pre-defined compliance policies and rules, a modern fraud solution allows finance companies to deploy solutions faster and perform compliance checks across channels, while also providing reporting for auditors.
A OneSpan spokesman said: “While no fraud prevention system is bulletproof, constantly updating existing fraud tools and staying sharp with modern capabilities has become a way of life for financial institutions.
"OneSpan Risk Analytics helps financial institutions to protect against attacks happening in the online and mobile channels using machine learning-based risk analysis to identify risk at critical steps, predicting risk levels, and taking instant action when suspicious activities are identified.”
OneSpan’s Risk Analytics solution works in the background, scoring activities in real-time based on a detailed analysis of user behaviour, transaction details, and other key contextual data collected from multiple channels.
The OneSpan spokesman added: “The use of machine learning enables risk scoring to streamline processes, reduce operational costs tied to manual reviews, and ultimately improve the user experience through fewer false positives.”
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