Fraudulent
Benefit claims are a huge problem. The UK Government loses up to £7 billion
in mispaid Benefits [BA]. Detecting bogus claims amongst the immense
number of overall claims is a complex and time-consuming task. The
FEDAURA Project will develop
and evaluate new computerised methods for automated Benefit fraud detection.
The FEDAURA Project
will combine techniques from Statistics, Neural Networks and Machine
Learning to produce fraud detection technologies using large-scale Benefit
Claimant data sets. The FEDAURA Project
will:
- Establish
a baseline by evaluating currently used detection methods.
- Identify
standards and produce an evaluation framework for fraud detection systems.
- Develop
and evaluate a selected range of new techniques.
- Compare
and evaluate the different methods for large-scale data sets.
- Disseminate
the best methods via a single computer package and publications.
The
FEDAURA Project
will be supported by the DTI Management of
Information Programme and the EPSRC (Grant No. GR/R55191/01) and will last for 36 months
from 1st November 2001. The
participating companies are:
- ACAG
Group, Department of Computer Science, University of York,
- Cybula,
- Department
for Work & Pensions,
- EDS,
- SchlumbergerSema
plc,
- Sun
Microsystems
[BA]
BA internal Command paper, March 1999, A New Contract for Welfare: Safeguarding
Social Security.
