![]() You cannot find issues that you have historically overlooked by looking at it in the same fashion every time. If you follow the same old methods, the same audit approach, the same reports, you will not be surprised when you get the same results and findings, and the fraudsters learn the process and are able to hide. In today’s audit, if you don’t have all this knowledge, issues tend to be overlooked. Understand the people is key to understanding the money. Let them know you are here to help their department by investigating processes. People feel attacked when they are investigated, and you need to put them at ease. Your need for information and data can only be fulfilled by being collaborative and a team player with a bit of persistence and relentlessness. Interview the peers in the group, use your critical thinking and management skills to see the whole picture from the auditors’ viewpoint. When asking questions, people skills come into play. Is your query about time of day, day of week, month, or is it a holiday? You may be suspicious of strange timing, the order of events or gaps? How about if you expand that microscope to categories, such as peer group outliers? Apply Your People Skills How about deviations from the rules of nature? An example of this is a time-series analysis audit. There are deviations from the business, contract or industry rules. Start by asking, “What are you looking for in an audit? What is your intention?” Audit traditionally looks at rule deviations, and in some cases, these could be vast. ![]() With data analytics, data can be examined from different angles, perspectives, and possibilities, especially those that may have overlooked previously. This expands your contribution to the overall business strategy and improves the auditor opinion, not to mention the possibility of saving the client money. You need to challenge your reporting and audit approaches to find what you’ve missed. You cannot find issues that you have historically overlooked by looking at things the same way you’ve been looking for. The same audit approach, the same reports regenerated on a schedule yielding the same results and findings won’t give you much. Solid interviewing techniques and management skills also help ensure the process runs smoothly. Finding the answer may require you to revisit the same sources more than once. It is also important to be creative, collaborative and persistent. While most auditors are natural critical thinkers, detecting peculiar behavior requires innate skepticism and an inquisitive approach. During a time-series analysis are you suspicious of the time of day or day of the week? A month or holiday or maybe you would like to find out if there are any time gaps or a deviation in the order of events, the actual cycle of the process? Maybe it is found purely in the category or peer group outliers. When investigating rule deviations, these deviations most likely will be from the business rules or industry standards, rules of nature, or potentially from the contractual terms. ![]() Use facts to drive key questions and data analytics as to the truth serum. What the management styles of the leadership? How are teams structured? What is the culture like? What controls are in place and how are they communicated? What motivates the employees and what types of relationships do they share?įinding the answers will also help you understand the data, which is a major step towards discovering what should not be there. ![]() It’s important to gain as much knowledge about the organization you’re auditing as possible. You can’t audit what you don’t understand. Data analytics can be used to pinpoint patterns and trends of suspicious behavior, deviations from the rules, and associations and correlations that should, or should not, exist to uncover fraudulent activity. These anomalies, errors, fraud, waste, and abuse can be found in discrepancies between systems that should not exist. As technology gets “smarter” so do the fraudsters working to outsmart the system.Īuditors have traditionally used data analytics for rule deviations, time-series analysis, investigate category/peer group outliers and other methods but is that enough? Fraud could lurk within process reengineering opportunities, business/process efficiency opportunities, groups working in silos, revenue leakage, and/or payment abnormalities. The median loss from occupational fraud was a whopping $150,000. Only 26.4% of frauds are found in six months or less, and 7.8% take more than 60 months to find. The ACFE Report to the Nations includes a graph which quantified how much time it takes to identify fraud. Missing information can also indicate fraud, but is difficult to find if data from different systems are not joined together for comparison. When working with rows and columns of data to spot suspicious behaviors, fraud and errors can look very similar to one another.
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