Fraud is pervasive; financial services institutions have been bogged down with fraud issues for ages now. In its latest report, security company McAfee estimates that cybercrime currently costs the global economy approximately $600 billion, or 0.8 percent of global gross domestic product. At this juncture, fraud detection in banking is a critical need that can span a series of fraud schemes and fraudulent activity from bank employees and customers alike.
Many organizations are developing automated and generalized predictive algorithms that specialize in matching customers and products to fight against financial frauds. Developers are also implementing deep learning techniques to create user and transaction fingerprints for identifying underlying relationships between data points for monitoring behavior patterns, enabling unusual transaction detection.
When it comes to financial risk mitigation, the ability to detect fraud in real-time can dramatically improve the customer experience. This is why banks and financial institutions are turning to advanced artificial intelligence (AI) based solutions. By dynamically conducting fund flow analytics in real-time, such solutions can effectively pinpoint fraudulent transactions, while reducing the possibility of false positives as well as false negatives. Another widely adopted way to approach the issue of fraud detection is using AI-based predictive modeling, by collecting and analyzing historical data to anticipate an event correctly.
To help CEOs, CTOs, and CIOs find the right financial fraud detection solutions provider, a distinguished selection panel comprising of CEOs, CIOs, VCs, industry analysts, and CFO Tech Outlook’s editorial board has selected a list of organizations that exhibit innovative features and service strategies. We have considered the vendor’s ability in delivering solutions and services that can effectively yet economically account for a secure fraud detection offering. We present to you “Top 10 Financial Fraud Detection Solution Providers - 2019.”