Can Big Data Crack Fraud?

How many jailed criminals receive unemployment benefits? How many people are working while claiming unemployment benefits?  How many unemployment benefits recipients are driving high-end BMWs? These questions are not always very easy to answer.

Part of the problem is the increasing number of services delivered through online methods.  Registering with Medicare or Social Security and then receiving benefits can be done in a fully virtual environment.  The situation is complicated further by various jurisdictional boundaries - local, state and federal governments.  This problem is probably less pronounced in countries with two levels of government, but it still exists, nevertheless.

However, the above questions are becoming easier for authorities to answer by using Big Data. And, smaller jurisdictions, with correspondingly smaller budgets and "narrower" view of their constituents, are going to be some of the biggest beneficiaries.

An example of using Big Data to identify fraud is the work done by +LexisNexis in US.  The company compared Medicaid recipients against vehicle registrations.  The check discovered quite a number of people receiving Medicaid benefits and driving everything from Bentleys to Aston-Martins to high-end Mercedes-Benz vehicles.

According to Andy Bucholz, director of Government Fraud Solutions for +LexisNexis, a much more holistic view of citizens and their activities is very likely to solve some of the fraud-related problems.

Read the full article in +Government Technology by Wayne Hanson here.