Using IBM Counter Fraud Management (CFM), an insurer can improve the operational effectiveness of its fraud prevention program and drive impressive fraud savings. IBM Watson helps insurers detect, respond and stop fraud with the ability to tap unstructured data.
No one is safe from fraud and financial crimes. When fraud occurs, it compromises secure data, raises legal fees, affects the bottom line and erodes customer confidence. Fraud is universal, with constantly evolving schemes. Regardless of the industry, a new holistic approach is needed to detect
Many suggest that the insurance industry's operating models already include the cost of fraud, creating higher cost structures and premiums. By taking full advantage of the integration and advanced capabilities being offered by leading counter fraud solution providers, enterprise counter fraud
Hunting the elusive black swan that is a fraudulent high-value payment requires a meticulous process of refining the fraud detection methodology to accurately identify the small variances in usual customer patterns. See how spotting elusive black swans requires the right tools to spot variances in
The financial services industry is in the midst of a shift toward integrating advanced analytics techniques into fraud prevention operations. Hear from two industry luminaries how fintech organizations challenged with limited skilled resources can use advanced analytics to identify patterns and
Using IBM Counter Fraud Management (CFM), an insurer can improve the operational effectiveness of its fraud prevention program and drive impressive fraud savings. IBM CFM leverages entity analytics, anomaly detection, predictive analytics and machine learning along with powerful forensic analysis
Cyber crime is no longer a mere nuisance but is quickly becoming a huge problem. Just recently, a cyber criminal was charged with wire fraud and computer fraud as he tried to steal more than $1.5 million. Cyber criminals are becoming increasingly more brazen as they exploit vulnerabilities in new
Cyber crime is no longer a mere nuisance but is quickly becoming a huge problem. Just recently a cyber criminal was charged with wire fraud and computer fraud as he tried to steal more than $1.5 million. Cyber criminals are becoming increasingly more brazen as they exploit vulnerabilities in new
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.
From mobile to tablet to desktop, today’s banking consumers demand instant and all-hours access to their financials across multiple platforms around the world. Online theft has expanded in scope from isolated, single-channel incidents to a whole framework of fraud that can happen anywhere and
Don’t let your guard down in the digital playground: although social media networks have become a part of daily life for many of us, they pose greater risks than many realize. Find out how solutions designed to identify fraudulent activity and stop it in its tracks help make financial security the
How does blockchain and cognitive computing affect fraud? Listen to the latest Finance in Focus podcast featuring Alex Tapscott, a blockchain expert and coauthor of a best selling book on the topic, who discusses how these technologies have the potential to eliminate fraud.
Mandatory fiduciary rule compliance looms, and yet wealth management firms are confronting a dearth of technology options to aid compliance. Hear what experts on this subject have to say about the critical need for surveillance technology to adequately monitor wealth management firm compliance.
IBM test data management (TDM) services are designed to satisfy the demands of enterprises trying to take advantage of test data and environment management solutions for complex IT deployments. TDM services cater to test data discovery, subset production, masking, test data refresh, automation of