Can Data Analytics Help Prevent Fraud?

Can Data Analytics Help Prevent Fraud

Broadly speaking, data analytics is defined as qualitative and quantitative techniques and processes, often utilized to accomplish a business objective by someone with a forensic accounting degree. This type of analytics is also useful when it comes to fraud detection and prevention.

The Growth of Data-Based Analytics

Over the course of the past several years, data-based analytics is being more widely used in a number of settings. Some experts in the field of this type of analytics contend that its use will have a significant impact on a fairly broad range of different industries. This includes everything from the financial sector to the healthcare industry to myriad enterprises relying on digital communication.

Forbes magazine reports that analytics derived from data is set to have a particularly important impact in a number of areas. The magazine goes so far as to maintain that it will “change the shape” of business, sports, and politics.

Moreover, with financial and other types of transactions involving the use of digital technology, data-based analytics is becoming ever more important when it comes to policing against fraud. Consequently, people armed with a forensic accounting degree are finding abundant employment opportunities. The data analyst is one of the hottest corporate jobs, according to Forbes.

Five Steps of Data Analytics for Fraud Prevention

In most settings, a five-phase approach is taken to analytics of this nature designed to prevent fraud. The first step is establishing specific fraud indicators to be tested. These fraud indicators are developed based on experience as well as common fraud schemes.

Once fraud indicators are established, data identification and extraction occurs. The IT system that stores required data is identified. The data itself is then extracted from the system in a controlled environment.

The third phase in the process is what is called cleaning the data and converting into a suitable, usable format for analysis. The next step is the translation of fraud tests into appropriate data tests. When achieved, the analysis is performed using data interrogation techniques. Interrogation techniques identify control breakdowns, data anomalies, and unusual trends.

The final segment of analytics for fraud prevention is the creation of an easy to understand report. The report delineates and summarizes the insights that are gleaned from the analytic process. Oftentimes a determination is made to re-run the tests periodically to continue monitoring in a proactive manner.

In-House Analytics

Another trend mentioned in the Forbes magazine report is that data-based analytics to detect and prevent fraud is being undertaken in-house with growing frequency. Rather than hire third-party professionals and firms to undertake the analysis of data as part of a fraud detection and prevention program, companies are employing their own staff to accomplish this task. This trend has made employees with a background in forensic accounting all the more valuable.

Data-based analytics has grown in use in the realm of fraud detection and prevention. In the final “analysis,” not only can data analytics, particularly with the involvement of a person with a forensic accounting degree, prevent fraud, but it is also likely to become the key manner in which it is combated.

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