Data mining is the automated process of sorting through large data sets to identify trends and patterns. It can provide a cost-effective and comprehensive solution to detecting employee fraud and errors in the processing of financial transactions in an organisation. Data mining is currently the most recognised and effective technology that has been implemented for fraud detection. Fraudulent acts impose serious threats to businesses financially, operationally and psychologically. Studies and research have proven that traditional fraud detection techniques such as internal control systems, external audits and risk management systems may not be effective methods for new fraud trends and data mining is a great, more modern alternative.
How can it benefit your business?
For many small to medium business owners, internal controls are not always practical to implement. Internal controls are processes that are put in place to safeguard the assets of the organisation. These controls are designed to protect the business against fraud, errors and misappropriations. Overseeing and policing these controls can be costly, time-consuming, and is also prone to human error. Embracing technology as an option to assist with this process is an effective solution to this.
How does it work?
Through the utilisation of specific software, anomalies or unusual trends can be identified based on the historical information. The software uses pattern recognition technologies, statistical and mathematical techniques to filter through information. Data mining helps analysts recognise significant relationships, trends, patterns, exceptions and anomalies that might otherwise go unnoticed.
Unlike a typical audit where random sampling methods are used, data mining can easily review all employee and creditor payments made during the period of the analysis. In many businesses, data mining is used to identify competitive advantages however, it is more importantly used to automatically find patterns in the data that may signify abnormalities including those related to fraud. While there is no way of preventing fraud, certain internal controls are essential.
The process is most effective when a complete data set is provided directly out of your business’ system for all payments made along with the underlying source data for all employees and creditors within the system. Data mining can then cross-check relationships to ensure all key abnormalities have been reported and can be investigated.
Data mining is not restricted to analysing financial data however it is one of the most common and important areas of a business to be used. Financial data is already collected in a business for accounting purposes and is already stored as ‘structured data’ which is a clean format often presented in tables. This makes the data mining process effective and efficient compared to ‘unstructured data’ which needs to be manipulated in order to be analysed by data mining. For a company to ensure that they are making the most of data mining, they must ensure that the quality of their data is accurate.
Why should you think about it?
An example of fraud identified from a data mining project was where an employee had established a fake ‘supplier’ account connected to their bank account and unlawfully been making claims for payments from the organisation. The data mining process identified that the employee and the supplier both had the same bank account details which was then investigated, and the fraud uncovered.
As a cost-effective internal audit process, data mining is something that all business owners should consider. If you have concerns about claimed payments, this is picked up in the system by the data mining software and you will be alerted of any abnormalities. Information is power and having software that can assist you in identifying issues swiftly, will leave you free to focus on other parts of your business and can give you peace of mind.
If you want more information about data mining or have any questions that concern your business, our specialists can help you. Simply contact your accountant.
