The role of data analytics in fraud prevention - EY

1 data analytics February 2014. The role of data analytics in fraud prevention Background savvy' and our experience indicates that they monitoring of business data for potential fraud are increasingly exploiting weaknesses in IT indicators. Organisations commonly limit their Business data is increasingly being managed and related controls to perpetrate fraud . When the fraud data analysis to quantification of the With increased stored by IT systems. The pressure to improve fraud is hidden in large data volumes, manual financial impact when fraud is detected by some accessibility of business efficiencies and integrate supply chains has meant checks for fraud are simply insufficient.

2 Other means. that many organisations are now heavily reliant data from internal on IT systems to support business processes. Such analytics for fraud monitoring However, data analytics techniques can also have a significant role to play in the early- and external sources, systems have also reduced the level of human While the technology enablement of processes warning, detection and monitoring of fraud . intervention required, which traditionally acted organisations now as a fraud control. As a result, organisations are has meant that the data is now available in a These techniques can allow your organisation structured form for further analysis, the EY to extract, analyse, interpret and transform have the opportunity placing more reliance on automated controls to both fraud risk management survey found that your business data to help detect potential prevent and detect fraud .

3 More than ever to many organisations are not capitalising on this instances of fraud and implement effective Additionally, fraudsters are becoming more IT- development and are not performing proactive fraud monitoring programmes. benefit from using analytics in their fraud prevention programmes.. Julie Fenton, Partner data analytics process 1. fraud test definition 3. data cleansing 5. Reporting and monitoring Define the fraud indicators you Clean the data and convert to Business-focused reports which are easy to understand, wish to test for based on experi- a format suitable for analysis. summarise results and provide data insights for process ence, typical business rule limits Import into analysis software owners.

4 If required, the tests can be re-performed on a and common fraud schemes. for test execution. periodic basis to facilitate continuous monitoring. Payroll Ghost employees Duplicate bank details Operational source systems Payments analysis Accounts payable Adherence to limits Weekend payments Benford's Law analysis Payments to unauthorised vendors Trend analysis Financial statement close Manual journal postings/adjustments Journals not balancing to 0. Journals posted after hours 2. data identification and extraction 4. data analysis Identify source IT system(s) which store Translate the fraud tests into suitable technical data the data required and extract this data in a tests and perform analysis using data interrogation controlled environment.

5 The data required techniques to identify unusual trends, data anomalies for testing should be formally requested in and control breakdowns. advance. The role of data analytics in fraud prevention 2. Developing analytics tests Standard tests Customised solutions data analytics challenges Why use data analytics ? Based on previous experience of fraud in It is also important to recognise that standard While data analytics offers many benefits as a Improved efficiency Automated your organisation and your knowledge of fraud tests may not be suitable in certain fraud prevention measure, it is also important method for detecting and monitoring common fraud indicators, you can translate this circumstances.

6 In these cases, it is necessary to recognise the challenges associating with potentially fraudulent behaviour. knowledge and experience into analytics tests to customise analytics tests specifically for the performing these techniques: to help detect potential instances of fraud . This needs of your organisation, based on the known Repeatable tests Repeatable fraud data quality The results from analytics set of standard fraud analytics tests can then issues, key risk areas and data available. This tests that can be run on your data at tests are only as good as the input data . be run against your organisations business data can include consolidating and analysing data any time.

7 Before performing tests, it is important on a periodic basis as part of a fraud monitoring from multiple sources in order to provide the to assess the quality of data and perform Wider coverage Full coverage of programme. This can facilitate the automated data insights required. Additionally, custom validation/cleansing if required. testing population rather than spot analysis on data from a variety of business techniques are also necessary when you are checks' on transactions better chance accounting cycles such as Accounts Payable, required to drill-down into the source data and data volumes There may be significant of finding exceptional items.

8 Accounts Receivable, Procurement Cards, perform additional testing to investigate specific data volumes supporting certain business Payroll, Expenses, General Ledger, and more, all issues. processes. Your data analytics testing Early warning system analytics designed to look for the red flags of fraud . infrastructure should be capable of solutions can help you to quickly handling identify potentially fraudulent these volumes. behaviour before the fraud becomes material. data security It is essential that appropriate security protocols are considered throughout the extraction and analysis to protect the confidentiality and integrity of source data .

9 Skillsets data analytics requires a combination of business and technical skills to define the tests, perform the analysis and interpret the results in order to provide meaningful insights. The role of data analytics in fraud prevention 3. EY | Assurance | Tax |. Transactions | Advisory About EY. About us EY is a global leader in assurance, tax, transaction and advisory services. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities.

10 EY refers to the global organisation and may refer to one or more of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. EY fraud analytics services Our team Learn more Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. For EY's fraud investigation and technology Our dedicated global team of professionals To learn more about how EY can assist you with more information about our organisation, please visit specialists have developed a set of standard specialise in delivering fraud data analytics your fraud data analytics solution needs, please fraud analytics tests that can be tailored to solutions for a variety of clients across industry contact: 2014 Ernst & Young.