Data Analytics - Grade: A PDF

Preview

Summary

essay on data...

Description

Memorandum

Date:

6/25/2021

Subject:

Benefits and pitfalls of using data analytics in fraud prevention

Introduction

There are many forms of fraud happening in life every day, and it has been negatively influenced a variety of industries. In the field of accounting, the fall of Arthur Andersen gave us a warning on fraud. Arthur Andersen took charge of auditing and consulting work for Enron. Arthur Andersen approved the ‘structure of many SPEs that were used to generate false profits, hide losses, and keep financing off Enron’s consolidated financial statements and that failed to meet the required outsider 3% equity at risk and decision control criteria for nonconsolidation. Arthur Andersen failed to recognize the GAAP that prohibits the recording of shares issued as an increase in shareholder’s equity unless they are issued for cash not for notes receivable).’ (Brooks, page 125). What if we use data analytics at workplace to prevent fraud? This research memo will focus on benefits and pitfalls of using data analytics in fraud prevention.

Key takeaways of data analytics

Benefits of data analytics in governments

Nowadays, the big data analytics is known as one of the most popular data analytics techniques in the world. In the United States, the use of big data becomes a significant tool to help governments reduce tax fraud, pharmaceutical fraud, and waste. The biggest advantage of data analytics is that it can rapidly collect data from database and handle a massive quantity of information at once. “Data analytics can track trends and possible problems substantially faster than people could without help.” (Matthews, line 5) Some federal agencies have demonstrated many benefits of integrating analytics tools during operations.

“The data analytics system of the U.S. Department of Agriculture’s Food and Nutrition Service identified merchants who traffic in food stamps and remove them from the program, thereby reducing the rate of food stamp trafficking from about 2.5 percent of food stamp benefits to about 1 percent. Similarly, by implementing a powerful data analytics system, the Recovery Operation Center (ROC) at the Recovery Accountability and Transparency Board (RATB) identified recipients who had previous brushes with the law or who were receiving multiple awards. Additionally, the Center for Program Integrity at the Center for Medicare & Medicaid Services is now using a predictive analytics system for Medicare fee-forservice payments that screens $450 million in Medicare claims each day. The system is expected to have a major impact on identifying and reducing Medicare fraud.” (Fadairo, Williams & Maggio, page 2)

The paragraph above was cited from the Journal of Government Financial Management. Since 2015, data analytics has been made a great achievement of fraud prevention into all levels of government and agencies. With the implementation of data analytics, decision makers can come out better decisions in a shorter period.

Benefits of data analytics for internal auditors

Data analytics can also be a helpful tool for internal auditors to improve their efficiency and effectiveness while completing the audit process. For example, “investigators are increasingly turning to data analytics to better target higher risk, higher return audits and investigations; comprehensively analyze financial performance; uncover systemic patterns of fraud, waste and abuse.” (Fadairo, Williams & Maggio, page 3) By using data analytics software like Excel, Tableau, and data mining, internal auditors can review everyday transactions and monitor high risk transactions visually.

Shortcomings and Pitfall of data analysis

Although the use of big data has brought many benefits to governmental process in cost, productivity, and innovation. There are some shortcomings of data analysis. The first potential pitfall of data analysis can be a high cost of hiring experienced coding experts or analytics professions. The second potential pitfall can be lack of internal analytics skills. With, there will be a lot of extra expenses on training, employment, and controls.

Connection to class

In Unit 6, we learned the many great data analytics and reporting tools, like data mining, data analysis software functions and the difference between data mining and data analysis. Data mining is the science of searching large volumes of data for patterns, and data analysis is a process of analyzing data from gathered findings. There are many low-cost and useful software that we can use to enhance internal controls, like Excel (pivotable & charts) and Tableau.

Citation

Fadairo, Williams. & Maggio. (2015). Using Data Analytics for Oversight and Efficiency. Page 2. Vol. 64. Issue 2. UMass library

Fadairo, Williams. & Maggio. (2015). Using Data Analytics for Oversight and Efficiency. Page 3. Vol. 64. Issue 2. UMass library

Kayla Matthews, How Data Analytics Can Assist in Fraud Detection. Retrieved in 2021. From: https://www.kdnuggets.com/2019/11/data-analytics-assist-fraud-detection.html

Leonard J. Brooks. & Paul Dunn. (2020). Business & Professional Ethics for Directors, page 125 Executives & Accountants. 9th Edition.

Master’s in data science. What is Data Analytics? Retrieved in February 2021. From: https://www.mastersindatascience.org/learning/what-is-data-analytics/...