Financial Crime World

Here is the article rewritten in markdown format:

Polish Companies Can Now Detect Financial Statement Fraud with Ease

Warsaw, Poland - Financial statement fraud can have devastating consequences for businesses. To help prevent this type of fraud, KPMG’s actuarial team in Poland has developed a comprehensive process for detecting potential financial statement fraud with an emphasis on its economic aspect.

Benford’s Law: A Powerful Tool for Fraud Detection

One of the key approaches used by KPMG’s actuarial team is Benford’s law. This law describes the frequency of the distribution of the first digit in many real data sets, allowing analysts to identify suspicious or possibly manipulated data.

  • Manipulated or made-up numbers will not be consistent with the expected observations of the frequency of the first digits as expressed by Benford’s law.
  • However, even if a data set complies with Benford’s law, there is still a risk of fraud. A mere deviation from Benford’s law does not necessarily mean that the data has been modified.

KPMG’s Comprehensive Fraud Detection Process

To efficiently assess the risk of financial statement fraud, KPMG’s actuarial team has developed a comprehensive process that includes:

  • Descriptive analysis: Understanding the characteristics and limitations of available data
  • Customer segmentation: Identifying areas at risk of fraud within the organisation
  • Community analysis: Analyzing external data from a wider context to identify potential threats
  • Predictive analysis: Using machine learning methods to identify fraud patterns based on historical data

The process involves several stages, including:

  • Defining the fraud and its characteristics
  • Applying necessary tools to understand the available data
  • Handling missing values
  • Detecting and treating outliers
  • Flagging damages depending on their characteristics
  • Building predictive models using advanced analytics techniques such as linear regression, logistic regression, decision trees, neural networks or multi-class classification techniques

A Proactive Approach to Financial Statement Fraud Detection

“Every organisation should identify areas at risk of fraud and implement comprehensive fraud detection and verification processes to effectively and dynamically respond to fraud challenges,” emphasizes Marcin Zabój, Manager, Actuarial services at KPMG in Poland and CEE.

By using KPMG’s comprehensive process for detecting potential financial statement fraud with an emphasis on its economic aspect, Polish companies can now detect this type of fraud more easily and effectively prevent it from occurring in the first place.