NAO Good Practice Guide - Tackling external fraud - HM Treasury

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0 Good practice in tackling external fraud | Detecting and investigating external fraud and imposing sanctions 3.4 It is also good practice to record information received onto a standard form. This can help in prompting the person making the referral into providing as much relevant information as possible. An electronic version of the form can be included on a website, which can be completed and submitted anonymously online. The person may want to know what action may be taken and feedback on what has happened. While it is possible to give general information on how referrals are handled, it may well not be possible to give specific details on individual referrals where this would breach confidentiality requirements. 3.5 Hotlines should be evaluated at regular intervals, for example, analysing the number and type of referrals received, what has happened in each case, and overall results. Figure 23 How some departments are using hotlines The Department for Work and Pensions has a dedicated telephone hotline (0800 854440) and website (www.dwp.gov. uk/benefit-thieves) to support the public in reporting suspicions of benefit fraud. In 2007-08, the hotline received 250,000 calls from the public. The NHS Counter Fraud Service has a confidential NHS Fraud and Corruption Reporting Line (0800 02840 60) which NHS staff and the public can ring to report suspicions of fraud. Members of the public can anonymously report a vehicle that appears to be unlicensed and used/kept on the public highway to The Driver and Vehicle Licensing Agency by using the national untaxed vehicles telephone hotline on freephone (0800 0325202), by completing an online form or by writing to a DVLA local office. The Agency receives around 10,000 reports a month from the public. In November 2005, HM Revenue & Customs set up a confidential Tax Evasion Hotline (0800 788 887) allowing members of the public to report suspicions on the evasion of income tax, corporation tax, capital gains tax, inheritance tax, VAT or National Insurance contributions. The hotline takes calls Monday to Friday 8am to 8pm, Saturday and Sunday 8am to 4pm. People can also report details of their suspicions through the Department’s website by completing an online form. In March 2006 the Department commissioned a major advertising campaign, using a combination of TV, press and radio to encourage members of the public to use the hotline. The hotline received around 120,000 calls in 2006-07. The number of calls has averaged 7,000 a month since then. 10 Serious Crime Act 2007 – http://www.opsi.gov.uk/ACTS/acts2007/ukpga_20070027_en_1 The use of computer techniques to detect fraud 3.6 A range of techniques using computer software and technologies can be used to detect cases of fraud. These include techniques such as data matching, data mining and neural networks. Smaller departments and agencies may be able to draw on the experience and lessons of others in the use of these techniques. 3.7 Data matching involves computerised scanning of data held in different data files either within the same organisation or in different organisations. It can be used by management for a range of purposes including detecting potential fraud. With increasing computer power, data matching across files is possible on a very large scale. 3.8 To help focus resources on the matches which indicate possible fraud, data matching software: l highlights the highest priority matches; l allows users to filter only those matches that meet investigators’ criteria for investigation; l explains the importance of each match type and protocols for sharing information between matched bodies. 3.9 The Audit Commission’s National Fraud Initiative is the country’s largest data matching exercise in relation to fraud (Figure 24). The National Fraud Initiative will be expanded in future years as a result of a new statutory power under Part A to the Audit Commission Act 998 as amended by the Serious Crime Act 007. 10 The Act enables bodies other than those that have a mandatory requirement to provide data for the National Fraud Initiative to volunteer to participate by providing data to the Commission. This means that central government departments and agencies can participate in future data matching exercises. Figure 25 to 27 shows how the Department for Work and Pensions, the Driver and Vehicle Licensing Agency and HM Revenue & Customs use data matching to detect evasion.
Figure 24 The Audit Commission’s National Fraud Initiative The National Fraud Initiative is the country’s largest public sector anti-fraud exercise. It is a computer based system which is run every two years and matches information such as housing benefit claims, pensions and social housing records from local councils, the NHS, police authorities, local probation boards and fire and rescue authorities across England. Figure 26 Shows how the Driver and Vehicle Licensing Agency uses data matching to detect vehicle excise duty evasion Automatic Number Plate Recognition (ANPR) cameras, some fixed and some mounted in mobile units, collect images of stationary and moving vehicles. Computer software searches for images of number plates and records the registration mark. The recorded mark is then compared with details from the Agency’s vehicle database. If a match is found, the image and event details are stored as evidence of the offence. The images of vehicle registration marks that are not matched to the unlicensed vehicle data bank are discarded. The matching process enables public bodies to share and compare information through a secure website and identify those taking services or money that they are not entitled to. Typical examples include council tenants renting (and subletting) council property in two different authorities, fraudulent claims for housing benefit, pensions being claimed for deceased people, fraudulent use of blue badge parking passes and duplicate trade creditor payments. Figure 25 Shows how the Department for Work and Pensions is using data matching The Department for Work and Pensions has a dedicated Database and Matching Service to identify possible fraud and error. It matches data: l across benefit systems; l between other Government departments and Department for Work and Pensions data; l for other Government departments; l for Local Authorities on Housing and Council Tax Benefits; l to tackle internal fraud. Good practice in tackling external fraud | Detecting and investigating external fraud and imposing sanctions The Department for Work and Pensions is currently modernising its Database and Matching Service to deliver a more timely and streamlined service to its customers. The objectives are to: l modernise the extraction of data from data systems to provide electronic transfer, cutting down on clerical and manual interventions; l operate a fraud and error referral system from a modern IT platform which allows new risk analysis techniques to be used; A record £140 million in fraud and overpayment was detected by the National Fraud Initiative in 2006-07. The National Fraud Initiative has now detected around £450 million in fraud and overpayments since it started in 1996. l provide an integrated service centred around the customer rather than the product; l provide more frequent and timely referrals. The programme aims to provide regular and timelier feeds into the data matching system to prevent frauds from being in the system for long periods of time. Fraudsters are therefore more likely to be caught sooner, and overpayments are expected to reduce as a result. Figure 27 Example of how HM Revenue & Customs has used data matching Using data matching, HM Revenue & Customs has identified people who may have received income from property but have not disclosed it. Following on from an advertising campaign, HM Revenue & Customs is sending letters to taxpayers for whom it holds information suggesting that they may have received income from letting property. The letters contain clear guidance, along with a standard form that can be used to return details of income received. Where no reply is received, HM Revenue & Customs considers what further action needs to be taken which could include formal enquiry or, in exceptional cases, criminal investigation.
Page 1 and 2: GOOD PRACTICE GUIDE Good practice i
Page 3 and 4: Contents Foreword 5 Introduction 6
Page 5 and 6: Foreword Reports published by depar
Page 7 and 8: laundering may be taking place. Mos
Page 9 and 10: Figure 2 The main elements of an in
Page 11 and 12: Taking a strategic approach to tack
Page 13 and 14: Assessing the scale of the threat
Page 15 and 16: 1.11 For some organisations, produc
Page 17 and 18: Focusing resources on the most effe
Page 19 and 20: Good practice in tackling external
Page 21 and 22: Figure 15 The main elements for det
Page 23 and 24: 2.4 To maximise the deterrent effec
Page 25 and 26: 2.8 There are a range of controls (
Page 27 and 28: 2.15 Strengthening internal control
Page 29: Figure 22 The actions to deal with
Page 33 and 34: 3.14 Data mining is the process of
Page 35 and 36: Figure 32 The NHS Counter Fraud Ser
Page 37 and 38: Figure 35 Examples of departments
Page 39 and 40: The recovery of money defrauded “
Page 41 and 42: Evaluating the effectiveness of san
Page 43 and 44: Good practice in tackling external

NAO Good Practice Guide - Tackling external fraud - HM Treasury

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