Data analysis is the only basis upon which forensic accountants can lay their claims. Evidences are made credible when backed by proof of analysis. All these made it even more pertinent for fraud professionals like forensic accountants. The problem that many accountants have is; what data analysis skills are we supposed to have. If you are in this class, then read further as this article is written for you.
DATA ANALYSIS SKILLS REQUIRED OF A FRAUD ACCOUNTANT / FORENSIC ACCOUNTANT
Ability to carryout statistical analysis: some times, an accountant needs to get certain ratios and some other testamentary evidence for information to have weight in the law court. You must be proficient in the use of statistical tool and other analysis tools. I recommend that you take a course on operations research as this will give you the right kind of exposure you need in areas like: goal programming, integer programming, linear programming, regression analysis, etc. Most occupational frauds concealed in data are easily discovered by simply running any of these statistical tools on them.
Ability to use forensic data analysis tools: digital evidences are oftentimes hidden in digital formats that are impossible for human eyes to see and require the use of forensic tools to recover. This is the area where investigators of our time are now proving their worth. So, if you want to be a force to reckon with, it is a must that you acquire skills of data analysis.
You may be wondering at this point if it is a must that you acquire data analysis skills. Well, it is not a must as many investigators rely on third parties to get their data analysed but for the reasons I will be mentioning in the next paragraph, I would advise that you learn to do your analysis yourself.
DISADVANTAGES OF ANALYZING YOUR DATA EXTERNALLY AS FORENSIC ACCOUNTANT
Forensic data analysis in usually iterative in nature: you will spend more money paying data analyst if they spend more time on your data. And most data analysis is iterative in nature meaning that cost cannot be avoided in doing this. Then what is your worth as an accountant if you cannot safe cost? – after all, accounting is all about cost savings.
No ad hoc access to further and urgent analysis: you cannot always get the service of a data analyst when need them at all time. And this may create a vacuum in the fraud fighting process.
Lack of flexibility: you will lose the benefits of being flexible if you simply outsource all your data analysis jobs to IT specialists and outsiders. Also, you may not get all the privacy that you require to be successful in your investigative work.
YOU CAN EVEN DO FURTHER SEARCH ON AMAZON TO BUY ANY OF THE DATA ANALYSIS TOOLS DISPLAYED THERE BY FOLLOWING THIS LINK BELOW
Search Amazon.com for data analysis
What level literacy of data analysis do I need to gain as a forensic accountant?
As far as data analysis skill is concerned, you can choose to be any of the following:
• Be totally ignorant of what can be done with data
• Understand data analysis possibility
• Know how to generate report from programmed and hidden system
• Ability to use query for data mining
• Full scripting and programming skill to analyse underlying database / data
The choice is yours. But if you really want to be effective and efficient in investigation as a forensic accountant; then you seriously need to acquire basic data analysis skill. This article will not be complete if I don’t say anything about data.
WHAT IS A DATA?
It is important to draw a line between a data and information. Data are statements accepted as they are without further query. That is, data are unprocessed information. Data becomes information when processed.
TYPES OF DATA / DATA TYPES
As a forensic accountant, you are supposed to have idea of the different types of data and how they interpret certain signs like ‘division sign (/)’. We basically have four types of data VIZ:
String (text, char or varchar)
Integer (long, int, bigint or smallint)
Date (time or timestamp)
Float (double or money)
I will not explain these data types now as this article is already too long. But, one thing to take home as regards data type is the fact that a particular symbol have different meaning in the eyes of the computer when processing information.
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