To reduce or better prevent the economical and reputational repercussions of fraud, many organizations make their traditional fraud prevention measures focus on discrete data points such as specific accounts, individuals or individual devices. Increasingly sophisticated fraudsters have developed a variety of ways to escape detection by forming fraud rings comprised of stolen and synthetic identities. […]
Nowadays customers demand to see their data in real-time without any lag time. The challenge is to process in real-time and, if necessary, transform or clean the data to make sense of it. It’s not just about the quantity of data you can analyze at once, it’s about the speed, scale, and quality of processing. A […]
We are very happy to join this year the Big Data Academy workshop series organized by our long-time partner BNova. We will be part of the 4 days “Data-Driven Workshop” in March and April 2019. You can find the full program and registration process here: LARUS will head the second day of work, next April […]
How Graphs can help insurance industry to combat Fraud Detection Introduction Insurance fraud came into being concomitantly with the spread of insurance policies themselves. From then on, every type of insurance coverage has always been accompanied by attempts, of varying degrees of success, to defraud insurers. In times of recession and economic crisis, insurance fraud […]