A standing room only crowd of invited guests converged at the New York Palace hotel on Thursday to listen to experts from government, insurance, healthcare and banking talk about one thing: countering fraud.
Criminal activity is rampant, and the brash sophistication of recent attacks—as well as the magnitude of damage— is making fraud a top priority. Consumers are concerned about their privacy and security., government agencies are working out how to address the volume of improper payments and claims
Just like the great train robberies of the wild west, criminals today go where the money is: online fraud. Unfortunately, fraud has become an ever more lucrative, and increasingly difficult to track, criminal enterprise. The same technologies, from cloud to mobile to big data and analytics, that
Using a powerful big data platform from IBM, Vanderbilt University School of Medicine clinicians cut research timelines from nearly a year to only a few weeks to help accelerate the pace of discovery and, ultimately, improve patient health.
Co-authored by Kim Minor, Worldwide Industry Marketing Manager for Insurance at IBM.
Claims fraud is an important topic, so we’ve written about it several times before. In this blog, I want to discuss how IBM big data capabilities can augment an existing fraud system at any insurer. By wrapping
Big data means different things for different industries. The definition also differs within an organization, across departments and management layers within IT and business. Within IBM, big data spans four dimensions: volume, velocity, variety and veracity. At The Big Data Institute (TBDI), big
One of the key best practices for successful implementation of a big data analytics solution is to validate the business use case for big data. It will help organization with two important aspects for success:
1. Keeping the scope limited
2. Helping to measure the success of a solution that
Solutions for analyzing big data can play a critical role in addressing the increasing prevalence of claims fraud. Traditionally, fraud is estimated to account for approximately 10 percent of insurance company losses, and that percentage is rising. Insurance companies need ways to quickly
In my previous two blogs [here and here], I’ve talked about how cognitive computing and big data present the insurance industry with great opportunities and some challenges. To develop strategies that capitalize on the potential gold mine of information that big data represents, many carriers will
“Organizations around the world lose an estimated five percent of their annual revenues to fraud, according to a survey of Certified Fraud Examiners (CFEs) who investigated cases between January 2010 and December 2011. Applied to the estimated 2011 Gross World Product, this figure translates to a
In last month’s post, I talked about how cognitive computers, like IBM Watson, have the ability to do what the earliest underwriters did: approach each risk individually and, based on historical learning, apply reason and judgment to determine a rate. Cognitive computing allows insurers to analyze
Historically, the insurance industry has simply accepted the staggering cost of fraud as a cost of doing business. Now, however, insurance fraud is on the rise. But help is at hand. Next-generation fraud solutions and big data are changing the equation in favor of insurance companies and their
Interest is growing among insurers for big data solutions that can help them identify, monitor and manage fraud in their underwriting and claims. Advanced fraud detection and management solutions are helping P&C and life insurers reduce losses by improving the precision and timeliness of fraud
Big Data. It’s everything from machine data from sensors to social media, audio and video, transactions, and enterprise content. We’re all trying to figure out what it means and how to leverage it to better understand our customers and drive change in our organizations.
So what’s the answer?