Measuring Fraud and Corruption - Assignment Example

Measuring Fraud and Corruption Accurately is Expensive and Time Consuming and is only Worth Measuring When Public Money is at Stake.’ Critically Evaluate this Statement Background & Introduction According to Dr. Bernard Herdan, Chief Executive Officer at National Fraud Authority, the yearly fraud indicator has figured out the loss to the UK economy from fraud at £38.4 billion. This shows and provides a stern warning against fraudsters who steal away huge amounts through frauds every year, impacting the UK people directly or indirectly. When divided, this huge amount represents fraud valuing each adult member of the population an average of £765 each year (National Fraud Authority, 2011, p. 3). As per the NFA yearly Fraud Indicator (2011), a range of methods has been employed within the public sector to measure fraud. The gold parameters are FLM exercises and the departments conducting these exercises on a regular basis include the Department for Work and Pensions (DWP), HM Revenue and Customs, and the NHS. So far, the (Fraud Loss Measurement Exercise (FLM) routines followed by the government departments have not produced any worldwide statistics for fraud losses. Any such stride to measure the depth and density of fraud is generally based on a number of measures, sometimes of various kinds. The DWP spends a lot of time in measuring fraud losses. It organises time bound FLM exercises to avail various leverages of these exercises, capacitating it to approximate a worldwide figure of fraud losses, made possible because of FLM, although there is difference of currency for some kinds of expenses. DWP has been spending huge resources in measuring fraud, nearly £10M each year on fraud measurement. This is divided between £0.4M on empirical analysis and £9.5M on checking performance. Nearly £1.5M of spending constitutes travel and living expenses of staff during travelling while performing the checks. Fraud measurement programme requires the involvement of 200 to 300 employees, remaining engrossed in measurement routines. The DWP also differentiates between fraud and error rates with the fraud alone rate differing from 0.0% for pensions to 4.1% for jobseekers allowance. It needs to be acknowledged that the FLM exercises are not organised each year for availing various benefits. For instance, the last FLM for Disability Living allowance was organised in the year 2004-05 (Home Office UK Government, 2011, p. 14). HM Revenue and Customs (HMRC) also spend hugely in correct measurement mechanisms to find out the ‘tax gap’. This is wider than fraud and error. It is defined as the difference between tax collected and the tax that should be collected (the theoretical liability). The theoretical tax liability represents the tax that would be paid if all individuals and companies complied with both the letter of the law and HMRC’s interpretation of the intention of Parliament in setting law (referred to as the spirit of the law). The tax gap estimate is net of the Department’s compliance activities. An equivalent way of defining the tax gap is the tax that is lost through non-payment, use of avoidance schemes, and interpretation of tax effect of complex transactions, error, failure to take reasonable care, evasion, the hidden economy and organised criminal attack (Seely, 2013, p. 5). Definition Before discussing methods of measuring fraud and corruption, it is relevant to know what constitutes fraud. These terms need to be defined to comprehend the contexts where these are used. Some people make use of these terms, ‘fraud and corruption’ without differentiation while others discuss corruption by including fraud as well. A clear-cut definition can help alleviate irrelevancy in conceptual design of the terms for facing measurement challenges related to fraud and corruption although as per the discussions of the United Nations Convention against Corruption, any trial at defining corruption can end in creating legal, criminological and political issues in a number of countries (Samford et al., 2006, p. 9). Corruption is a very wider term, assimilating various behaviours. The Asian Development Bank defines corruption as: “...behaviour on the part of officials in the public and private sectors, in which they improperly and unlawfully enrich themselves and/or those close to them, or induce others to do so, by misusing the position in which they are placed (Asian Development Bank, 2013, p. 1)”. In nutshell, corruption is the misuse of a rank for benefit. There is enough corruption, which for sure is bad, irrespective of the volume of funds released. For example, in public domain a corrupt public servant uses his rank to get assured that a contract is awarded to the specific supplier only for agreed services of an aid project who has paid him off. This conveys that the contract is granted at a lesser cost because the corrupt official informs the specific bidder what the cost of the lowest bidder is. A government official accepting bribe to make a job offer to a particular person may not be actually causing monetary loss to the organisation. On the same wave-length, a politician might use funds as per policy decision, but might not use all-across the region equally, and rather spend all funds in his/her own polling area, for own tribe. Technically, this is not frauds, as funds were supposed to be spent but it is tantamount to corrupt practices (Button et al., 2011, p. 7). Nevertheless, corruption by an official also causes losses of funds, which is a sort of fraud. For example if a corrupt official uses funds given to him through the government to construct a hospital, which he misuses by building a palace, it is an instance of corruption and fraud. The Fraud Act 2006 has codified the criminal definition of fraud in England and Wales. This law has offered enough benefits. The book by Farrell et al. (2007)) enumerates various methods of committing fraud, which include aid related frauds as well, such as: Fraud by False Representation (this may include presenting false invoices for payment). Fraud through non-disclose of information (e.g. if a contractor receives payment for providing medical facilities to 1000 children, but only 700 children are attended and the funder is not informed about it). Fraud by Abuse of Rank (this is when an individual in a responsible position misuses their rank by diverting funds to their individual account) (Farrell & Ladenburg, 2007, p. 9). Fraud can be related to corruption through many other similar examples of people in high positions committing frauds. A number of fraudulent activities take place against the government by NGOs that cannot be trusted. When a contractor raises invoices or invoices in full for uncompleted contractual obligations, it is not corruption but fraud. Therefore, both fraud and corruption need to be discussed two entities of partially overlapping criminal behaviours (Home Office UK Government, 2011, p. 8). Measuring or Not Measuring is the Question This is the most serious question that needs to be analysed, which is whether it is worth finding to correctly measure fraud in overseas aid. Due to various challenges in the way of correctly measuring fraud over the spectrum of a bilateral aid donor and its associate bodies, it can possibly be very costly and time wasting activity. Actually, a huge amount is spent by the DWP, nearly £10 million on measuring fraud in otherwise a relatively easy area to fathom. If this is used to a bilateral, these resources could be used for aid helping people, instead of producing empirical data. There is a possibility that if the outcomes then indicated important leakage to fraud, this could possibly create political complexities and public anger at a time of austerity over the rest of the public sector. Perhaps, it is more preferable to just advance with very little knowledge of discerned degrees of fraud as the best pointer of degrees of fraud and pay attention on methods well tested in tackling fraud (Button et al., 2012, p. 16). Fraud Loss Measurement (FLM) Methodologies Academic research has revealed two possibilities, called ‘Super FLMs’ and use of both FLMs and modelling. Super FLMs are extra-ordinarily larger and have not been accomplished before, as they required huge workload. Therefore, they were cancelled for measuring fraud in bilateral aid agency. The other possibility of methodology is based on the approach for a bilateral to work on a basket of measures, employing both FLMs and modelling (Button et al., 2012, p. 21). The ‘Super’ FLM on Bilateral aid agency Payments Considering the size of the task of fraud measuring, the related possible costs, the new methods to be developed, it would under-approximate fraud, which is the cause behind rejecting the ‘Super FLM’ approach. However, it offers political benefits by generating global data but that would perhaps be quite insufficient. This methodology might be tried but it is impractical because it is beyond the budget due to high cost and dependence on randomly chosen multilateral associate and their recipients (Button et al., 2012). Secondly, most FLMs generally measure ditto transactions like payment of social security benefits, payroll, expense claims or procurement. A random sample of expenses would create a vast range in size, kind and complicate transactions. It would make the FLM highly costly, never attempted before. Besides, a vast range of checks, including overseas, would be required, resulting in further increase in the costs (Button et al., 2012). The leading technical disadvantage of this approach is that enough transactions cannot be verified to check fraud. Payments made to multilateral organisations might cloud the reality that most fraudulent activities happen down the ‘pipeline’, after the payment is in the coffers of the organisation. Possibility of misusing payments through duplicating of invoice or some other kind of fraud is not high. It requires humongous effort to inquire and check further FLM exercises (Button et al., 2012). A good number of transactions in an FLM might produce a number of nil returns for testing fraud, thus, undermining the possibility of fraud in funds down the pipeline. Removing multilateral budget support can be tried as an adaptation to this methodology, including straight government assistance, and by taking a random sample from the rest of the transactions. It would provide better outcomes of measuring fraud in select areas of the budget. Yet, logistics issues can emerge related with a random sample over a vast range of transactional categories. It would also necessitate a new kind of FLM to be developed, requiring huge resources, leading to finally presenting an incomplete view of the degrees of fraud. The Basket Approach No single method is used by government agencies and NGOs for measuring fraud losses. Instead a basket of measures are applied because the basket approach offers the possibility of trying different methods for various expenses types, which is quite complicated in bilateral aid agency model. Expenses can occur necessarily via 5 financial output modes: Administration (payroll and purchasing) Direct purchasing for aid purposes Funding to multilateral bodies Funding to governments Funding to NGOs (Button et al., 2012, p. 21). Strengths and Weaknesses of Various Assessments Irrespective of the various fraud measuring methodologies, strengths and weaker areas of some of the accomplished assessments, found unfit for assessment purpose, are given below: The Public Expenditure and Financial Accountability (PEFA) is quite comprehensive appraisal mode for public monetary management systems, which is its strength but its weakness is that it does not pay attention to taking measures to control fraud and corruption tactics. The strength of Fiduciary Risk Assessment (FRA) lies in vast appraisal of measures to tackle with corruption in public sector. Its weakness lies in increased attention to trace out corruption rather than fraud. Another assessment related to Business Case Core Script Procedure has its strength in wider analysis of the benefits of a project. Its leading deficiency is related to lack of deeper insights on fraud risks and risks reducing strategies. On the assessment of Project Control Systems, it accomplishes general appraisal of projects, which is its strength but again like the Business Case Core Script Procedure, it lacks a comprehensive focus on fraud. Regarding the assessment through Public Expenditure Tracking Surveys (PETS), the strength lies in finding out funds leakages, but it is project-based, including fraud, error and inefficiency. It is also very costly assessment otherwise (Button et al., 2012, p. 32). Conclusion Measuring the costs of fraud should not be seen only in terms of financial loss. Fraud degrades the whole spectrum of society, depending on the size of the businesses. Loss of reputation can be a critical concern for a large business relatively to a small and medium sized business for which it can be a fight for survival. Fraud can be detrimental for SMEs, affecting the entrepreneurs, their employees along with their families, causing a gloomy shadow over the economic horizon of the country. Individually, fraud can be suicidal for weaker sections of a society, as some people may even try to commit suicide when cheated of their assets (Home Office: UK Gov, 2011, p. 6). The discussion above on the need of measuring fraud and corruption and various methodologies clearly hints at not going strong-headed by starting measurement procedures in all cases where funds in various governments, private and NGO level are released. Random selection of transactions from the available lot seems to be the best alternative to avoid high costs in checking fraudulent transactions when public money is at stake. References Asian Development Bank. (2013). Anticorruption in developing member countries. Public Sector Management and Governance. Retrieved 11 November 2013 from http://www.adb.org/themes/governance/anticorruption Button, M., Lewis, C., Shepherd, D., & Brooks, G. (2012). Measuring fraud in overseas aid: options and method. Centre for Counter Fraud Studies. University of Portsmouth. Retrieved 11 November 2013 from http://r4d.dfid.gov.uk/pdf/outputs/misc_gov/60908DFID_FINAL_REPORT_March2012post_david.pdf Farrell, Y. N., & Ladenburg, G. (2007) Blackstone’s guide to the Fraud Act 2006. Oxford: Oxford University Press. Retrieved 11 November 2013 from http://books.google.co.in/books?id=iobXmpblsUAC&pg=PA29&lpg=PA29&dq=Farrell,+Yeo,+N,+Ladenburg,+G.+(2007)+fraud&source=bl&ots=7J7Ilcb-6h&sig=7u9Nb1gGwLSfAOOkiDb0kKrMVn0&hl=en&sa=X&ei=X2CDUt3HOYONrQeltIHwBA&ved=0CCwQ6AEwAA#v=onepage&q=Farrell%2C%20Yeo%2C%20N%2C%20Ladenburg%2C%20G.%20(2007)%20fraud&f=false Home Office. (2011). Fighting fraud together: The strategic plan to reduce fraud. NFA. Retrieved 11 November 2013 from http://www.homeoffice.gov.uk/agencies-public-bodies/nfa/ NFA. (2011). Annual Fraud Indicator. National Fraud Authority. Retrieved on November 12, 2013 from http://www.homeoffice.gov.uk/publications/agencies-public-bodies/nfa/annual-fraud-indicator/annual-fraud-indicator-2011?view=Binary NHS. (2011). NHS Protect: NHS CFS Performance Report 10/11. Retrieved 11 November 2013 from http://www.nhsbsa.nhs.uk/Documents/CounterFraud/PERFORMANCE_REPORT.pdf Samford, C., Shacklock, A., Connors, C. and Galtung, F. (Eds). (2006). Measuring corruption. Aldershot: Ashgate. Law, Ethics and Governance Series. Retrieved 11 November 2013 from http://books.google.co.in/books?id=k06ImKacaqEC&printsec=frontcover&source=gbs_atb#v=onepage&q&f=false Seely, A. (2013). Tax avoidance: a general anti-abuse rule. Standard Note: SN6265. House of Commons Library. Business & Transport Section. Retrieved 10 November 2013 from www.parliament.uk/briefing-papers/sn06265.pdf Read More