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Efficiency without deficiency: Tackling fraud and error in the public sector

Efficiency without deficiency: Tackling fraud and error in the public sector. Sanjay Mackintosh – Cabinet Office Jonathan Lloyd-White – HMRC. Overview. Context Benefits, credits and revenue fraud Cross-cutting fraud and error Procurement Grants Payroll and insider-enabled fraud.

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Efficiency without deficiency: Tackling fraud and error in the public sector

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  1. Efficiency without deficiency:Tackling fraud and error in the public sector Sanjay Mackintosh – Cabinet Office Jonathan Lloyd-White – HMRC UNCLASSIFIED

  2. Overview • Context • Benefits, credits and revenue fraud • Cross-cutting fraud and error • Procurement • Grants • Payroll and insider-enabled fraud UNCLASSIFIED

  3. Fraud in the public sector - context

  4. Fraud in the public sector

  5. HMG Counter Fraud Taskforce • Established October 2010 • Ministerial and senior officials group • Francis Maude MP – Minister for the Cabinet Office (Chair) • Lord Freud – Minister for Welfare Reform (DWP) • David Gauke MP – Exchequer Secretary (HMT) • James Brokenshire – Minister for Crime and Security (HO)

  6. What has the taskforce done so far? • Overseen eight pilot projects across government that saved £12m and will save £1.5bn by 2014/15 • Set up cross-government network of Counter Fraud Champions • Cross-government fraud alerts system • Fraud, error and debt metrics on departmental quarterly data summaries • Civil service learning – counter fraud e-learning tool • Identified cross-cutting issues – procurement, grants and payroll/insider-enabled fraud

  7. Interim report – June 2011 • Collaboration across public services • Properly assess riskand quantify losses • Focus on prevention • Establish a zero tolerance culture

  8. Benefits, Credits and Revenue Error and Fraud

  9. Size of the prize and approach • Benefits & Credits • 6 million customers – £327bn paid annually • Complex policy – 160 moving parts • 1 million new claims • 8 million changes of circumstance • 6 million renewals • 1,800 staff working on error and fraud • 8.9% error and fraud rate in 2008/09 reduced to 7.4% in 2009/10 - £2bn over last two years • Benefits & Credits – The New Strategy • Customer Understanding – knowledge of risk categories and losses drive design of services • Right first time – shift from “Pay now, check later” to clear strategy of “Check first, then pay” • Measure – proxy in-year targets informed by real time data to engage staff and drive redeployment • Professionalism – campaigns on risk groups based on data mining and analytics • Tax Compliance • Approximately 4.5 million businesses and 31 million individual customers • Estimated £16bn tax gap attributable to fraud & error • 25,000 staff in Enforcement & Compliance working on spectrum of non-compliance rising to 28,000 by 2014/15. • Tax Compliance • Risk driven strategy – risking done at national level based on data analytics • Increased coverage - significant re-investment of staffing over next three years • Connect - Continued investment in our data matching and analysis tool • Campaigns & Taskforces – focused activity to tackle specific populations and risks

  10. Tax Credits Error and Fraud Strategy • PREVENT • Fraud & Error Assessment Risk Tool (FEAST) – Screening tool for new tax credit applications – finds risks that would be extremely difficult to detect using manual intervention; • High Risk Changes of Circumstances - Working in partnership with Contact Centre colleagues allows us to challenge customer information when they try to make changes to their awards. • High Risk Renewals – our chance to correct previous year awards whilst putting current year claims on correct footing. Based on feedback and lessons learned, moved towards a more targeted risk-based approach based on Risk Groups. • MAINTAIN • Pilot with Credit Reference Agencies on Undeclared Partner • 20k Tax Credit claims with some evidence of an Undeclared Partner. • CRAs ranked the cases into high, medium low risk. • Red – letter issued to customers where we have specific information or data from the CRA that strongly suggests there is a high risk of and Undeclared Partner. • Amber – letter issued where we have information from the CRA which suggests there maybe a risk of an Undeclared Partner

  11. Driving effective interventions with data • Matching data from 26 separate systems - Connect • Approximately 1 billion matched data items • £45m invested over last three years - £1.3bn in tax yield • Top-end data analytics used to address whole spectrum of risks • High volume-low value error, to sophisticated on-line organised criminal attacks or complex corporate tax affairs • Driving focused taskforce activity on evasion – scrap metals in Scotland • Driving focused campaigns on populations – Medics, Offshore, Plumber

  12. Ongoing investment • Data/capacity – growing storage, processing capability and user numbers • Text mining – ability to mine unstructured text based information • In-house academy for data analytics – keeping people up to pace with technology • ‘Upstream Transaction Risking’ • Credit Reference Agency trials – using third party data to check declared income • Predictive analytics – spotting behavioural trends to separate error from deliberate evasion

  13. Cross-Cutting Fraud and Error – New Opportunities

  14. Procurement fraud £2.4bn lost in the public sector each year Pre-contract award fraud – cartel activity, corruption, collusion Post-contract award fraud – false payments, duplicate invoicing HO/DfT – detected £4m and £0.5m in overpayments using spend analytics Counter fraud training and awareness for public procurement specialists in the public sector Undertake cross-govt analysis on spend through accounts payable systems to detect fraudulent or erroneous payments Spend analysis audits - £100m may have been paid across government Procurement fraud training – CiPS have partnered with CIPFA to provide a course, but more courses should be run for public bodies

  15. Grant fraud £515m lost to fraud in the public sector each year Grants expenditure not fully understood – cross-cutting fraud threats even less well understood Applying for grants no different from applying for benefits or tax credits – fraud and error risks is the same Deeper analysis of grants administration across government – identify how much is paid out, to whom, what processes are used, fraud/error risks Deploy use of data analytics to detect grant fraud and error at application stage as well as post-payment Piloting prevention/ detection screening tools with government departments who issue grants

  16. Insider-enabled fraud £329m lost to fraud in payroll and recruitment, but unknown how much fraud is ‘insider-enabled’ PwC estimate 39% of economic crime in public sector is enabled by staff within organisations Analysts believe insider threat grows during recession – risk is highest now Staff fraud database – record staff dismissed for insider-enabled fraud and allow public bodies to use this as a pre-employment tool Training and awareness for public servants Whistleblowing/fraud reporting line Insider-enabled fraud database – possibly outsource this Whistleblowing function – individual services within departments or single cross-government reporting tool

  17. Summary • Tax and benefit fraud and error is well understood – has the investment to match • Other cross-cutting issues need to be better understood and solved – could be bigger than what we already know • New opportunities for supplier engagement – work with us to understand the problems and develop solutions • Engage with counter fraud champions across government

  18. Contact us fed@cabinet-office.gsi.gov.uk

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