Existing customers are worth retaining. Organizations have the ability to cross-sell and up-sell to their existing customers, which is why these organizations must keep in mind a customer’s lifetime value.
Integrity within social governmental agencies can be a big problem in the digital age. City, state and federal agencies can lose huge sums of money to errors, waste and abuse. Analytics can go a long way in helping these agencies validate claims and minimize the potential for fraud. Having read
Financial services and banking are data-driven. Organizations in these industries store and analyze data on millions of customers, this data valued in the billions. As a consequence, they have to struggle with ever increasing volumes, velocity and variety of data. To stay ahead of competition, and
When I think back to last year’s Information on Demand (now Insight) conference, one customer story in particular comes to mind: Memorial Healthcare System’s uncovering of vendor fraud, a bid rigging scheme and a potential staff risk in what began as an effort to simply streamline and improve the
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