A key issue for the UK's local authorities is housing tenancy, benefit and council tax fraud - a problem that costs them in excess of £1.3bn a year, according to the National Fraud Authority.
In order to help tackle these problems Gravesham Borough Council agreed a deal with Fujitsu to pilot its social housing fraud and error technology, a tool that is already used by HM Revenue & Customs (HMRC).
As a result of using Fujitsu's Social Housing Analytics service technology, the council was able to help its investigative team to identify over 75 properties where the council made a range of interventions from repossession of properties to re-housing.
"A couple of years ago, the government put a focus on councils to tackle tenancy fraud in regards to subletting false applications and ‘key selling'," James Flannery, investigations manager at the council told Computing.
"One way of tackling fraud tenancy is by conducting data matching to ensure that the data we hold with respect to our tenants is correct. Fujitsu came in seeking a partner to help pilot some of their data analytical software and we put our name forward to assist and conducted this at the back end of 2011," he explained.
Although Fujitsu could not disclose detailed information of the technology because of the sensitive nature of data and as the project is still ongoing, its lead practitioner for local government Ian Hall explained in brief how the technology works.
"The council provides us with a list of people claiming a particular housing benefit or exemption, we then run this data through a series of analytics models to provide them with a list prioritised by the level of risk they represent - the council then checks this with a view to preventing fraud or errors and recovering any money owed as a result," Hall told Computing.
Flannery added: "With all data matching there is elements of false positives meaning that fraud isn't actually being committed, it's just a data error, either on our site or the data set that Fujitsu were matching against which in this case was credit reference data."
The council previously used credit referencing agencies to match the data, but this produced hundreds of results, of which many were false positives.
"Fujitsu were very easy to work with. They explained what they needed from our tenancy data and then provided instructions on what the data meant when it came back and how we should tackle the data. We had heard of alternative options for data matching and analytical companies, and they all offer different things but data quality was paramount. What interested me in Fujitsu was that the number of matches we were going to get would be very focused," Flannery explained.
Most importantly for the council, the technology allows the team to focus on high-risk cases.
"Using the technology, we were able to identify a specific amount of cases which required some high resource focus that involved people going door knocking and conducting tenancy audits on properties that we identified as discrepancies," said Flannery.
By eliminating high entry costs for big data analysis, you can convert more raw data into valuable business insight.
A discussion of the "risk perception gap", its implications and how it can be closed