Fraud threats have been growing both in sophistication and scope, compelling credit unions to determine where and how to deploy resources to shield from possible breaches, even as they manage their daily operational challenges. So what more can credit unions do to protect themselves from fraud?
Given the slackening pace of growth preceded by a spike in quantitative easing and flush liquidity in many countries, severely impacted corporate borrowers debts servicing, and consequently, there’s a higher potential for loan defaults. This whitepaper examines critical early warning indicators and scenarios, why multidimensional inputs are crucial to LEWS efficiency and the need for an innovative approach to it.
The bank customer of the day has a new avatar. Easy, instant access to wider information, extensive knowledge about choices available and privileged treatment by organizations in other industries have made them remarkably well-informed and demanding. They do not hesitate to quickly shift to whosoever serves their needs best.
The use of hybrid fraud detection models to ensure high fraud detection rates with low false positives is a vital aspect of enterprise fraud management. A ‘hybrid’ fraud detection model comprises 4 primary techniques are used to accurately risk score every transaction and to advise the right action of whether to approve, decline or challenge the transaction in real-time with sub-second response time.
Risk as a Service with a focus on Enterprise Financial Crime Risk Management (EFCRM) is fast becoming a core component in a bank’s overall risk management framework. EFCRM-centric RaaS addresses a spectrum of areas ranging from transaction monitoring to fraud management to money laundering to CFT (combating the financing of terrorism) programs to cyber-security.
In the world of financial transactions, rule based heuristics are often employed to detect fraud, rather than to detect anomalies. The cat and mouse chase of financial institutions and fraudsters is an ongoing battle that has costed the global economy close to half a trillion dollars. Given the fundamental shortcomings of rule based heuristics, how does machine learning help in fraud detection?