With more personal information accessible online and its accuracy questionable, relying solely on the data provided as part of the payment messaging can be risky.
Continued incidents of “spear phishing” and “catfishing” only serve to highlight the complex work required to tell the genuine apart from the fraudulent.
Historically, a mix of free and paid-for resources, as well as good old-fashioned Google, were useful. Today the same tactics that are used to prevent our data from being compromised also prevent fraud analysts from verifying the identity of the individual.
It is increasingly difficult to access the information, such as a friends list in Facebook, to establish whether the passengers on a travel booking are known to the cardholder and substantiate whether the profile is not part of an elaborate synthetic identity.
The job of fraud analysts is getting harder and more pressurized as more data is available to them. By enhancing the data available to analysts during their investigations in the form of a neural confidence score, there is a paradigm shift from so-called “paradox of choice” decisioning to data-driven insight enabled by analytics.
Traditionally, after all available avenues of investigation were exhausted, a judgment call would be made based on experience. With the latest technology in place, a user can utilize a probability score to support his findings.
Myriad device and browser-based intelligence, divulged from hundreds of data points, can be used to build a construct of positive or negative behavior, which, in tandem with real-time decisioning, adds further security to the authentication process. Device identification is not just a unique reference for equipment anymore; it is a puzzle made up of hundreds of pieces, each contributing to build a picture of the consumer.
Understanding the psychology of the user and providing a set of tools to ensure negative behaviors are discouraged will lead to increased accuracy, staff productivity and operational savings. The human mind is not designed for continued repetitive actions, and by integrating operational efficiencies to counter decision fatigue allows for the human component to be utilized for more creative pursuits.
Being able to see what is happening in your operation at any point and in any location is essential, but often the data is not easily digestible. This requires additional operational hours to provide the answers the reports were designed for.
Consolidating your data must be underpinned by well thought out and ergonomically designed visuals, intelligently depicted in a form, so insight can be efficiently determined, and interrogated by linearly and dynamically drilling down to a granular level highlighting previously unseen risk.
Network visualization technology identifies common points of compromise and concealed connections within noisy datasets, exposing new avenues of investigation for analysts to evaluate, highlighting complex associations between cases and individuals leading to the discovery of a possible fraud ring.
Using known frauds as a starting point, networks can be created to trace back genuine activity and identify potential sites of interest, which show a higher proportion of links to them, down to the terminal level and specific times of day. The results of these investigations can be consolidated to generate strategies to mitigate future occurrences within rule management, customized neural models, and by setting reporting KPIs.
Artificial intelligence can be an effective weapon against criminals. Isn’t it time your organization armed itself with the latest fraud and risk management capabilities and started to take the fight to fraud?
