How can statistical techniques be used to detect financial irregularities?

1 Descriptive statistics

Descriptive statistics are the basic measures that summarize the main features of a data set, such as the mean, median, mode, standard deviation, range, and frequency. They can help you understand the distribution, variability, and central tendency of your data, and compare them with expected or normal values. For example, you can use descriptive statistics to check if there are any outliers, extreme values, or missing data that deviate from the rest of the data and indicate a possible error or fraud.

3 Regression analysis

Regression analysis is a type of inferential statistics that explores the relationship between a dependent variable and one or more independent variables. It can help you model how a change in one variable affects another variable, and quantify the strength and direction of the effect. For example, you can use regression analysis to estimate how sales revenue depends on factors such as marketing expenditure, customer satisfaction, and seasonal trends, and identify any anomalies or inconsistencies that could suggest manipulation or misrepresentation.

5 Benford's law

Benford's law is a mathematical phenomenon that states that the leading digits of many real-world data sets follow a specific distribution, where lower digits are more frequent than higher digits. It can help you identify anomalies in data that are expected to conform to this law, such as financial transactions, invoices, tax returns, and accounting records. For example, you can use Benford's law to check if the frequency of the first digits of a data set matches the expected distribution, and flag any deviations that could indicate fabrication or tampering.

6 Data visualization

Data visualization is the process of presenting data in graphical or pictorial forms, such as charts, graphs, maps, or dashboards. It can help you communicate your findings, highlight key insights, and compare different aspects of your data in a clear and engaging way. For example, you can use data visualization to display the results of your statistical analyses, such as the descriptive statistics, inferential statistics, regression models, time series forecasts, and Benford's law tests, and spot any patterns or anomalies that require further investigation or action.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?