Utilizing Data Analysis to Monitor and Detect Fraudulent Activity
Data analysis is changing the way many organizations operate. Extracting, cleaning, transforming and modeling data can help uncover valuable information, derive conclusions, support decision making and drive strategies. It’s also changing how forensic accountants do their jobs, providing fraud experts with the means to harvest and analyze massive amounts of data more quickly and effectively than ever before.
According to the 2018 Report to the Nations released by the Association of Certified Fraud Examiners (ACFE), organizations that use active methods of detection, such as data monitoring/analysis, can reduce their fraud losses by an average of 52 percent and detect scams in one fourth the time. In fact, data monitoring and surprise audits were correlated with the largest reduction in fraud loss.
Types of data that be analyzed include:
- Accounting and financial data
- Human resources data
- Payroll data
- Customer data
- Vendor data
- Internal communications and documents
- Benchmarking data
Data analytics, as it applies to fraud examination, refers to the use of analytics software, techniques and strategies to identify trends, patterns, anomalies and exceptions within data. This can be especially useful when fraud is hidden in large data volumes and manual checks are insufficient and inefficient.
How can data analytics help with fraud risk management in your organization?
- Identify and assess control weaknesses. In areas of high risk, you can use analytics to search for indications of control weaknesses and anomalies that could be strong indicators of fraud. Data analysis strategies can then be devised for each risk factor.
- Use data analytics proactively. The demand for using data analytics tools and techniques has increased substantially in recent years, but data analysis and data mining remain underutilized when it comes to addressing fraud risk. Utilizing data analysis proactively provides the opportunity to assess and improve internal controls to better prevent and detect fraud.
- Support fraud monitoring plans. A fraud monitoring plan assists in high-risk areas. An active data monitoring plan allows forensic accountants to detect patterns, review trends and uncover irregularities in real time so fraud can be identified before it becomes material.
- Address the fraud triangle. Data analysis can be used to address aspects of the “fraud triangle” (pressure, rationalization and opportunity). When data is analyzed and employees know data patterns are being examined, they are less likely to commit fraud. Effective data analysis enables detecting fraud sooner and provides supporting evidence, should fraud be discovered.
Organizations that do not actively seek out fraudulent activity are more likely to experience higher fraud losses than those utilizing active detection methods. Data extraction, analysis and visualization all help to not only prevent and detect fraud, but also test vital controls and assess process efficiency and effectiveness.