Fraud Detection

Using datafusion's Analytics Platform in the finance or banking industry

Why Use Data Analysis for Fraud Detection?

Data analysis software enables auditors and fraud examiners to analyze an organization’s business data to gain insight into how well internal controls are operating and to identify transactions that indicate fraudulent activity or the heightened risk of fraud. Data analysis can be applied to just about anywhere in any organization where electronic transactions are recorded and stored.

Here are a few typical fraud schemes encountered in banking  and some examples of the way datafusion Platform features can be applied to detect and prevent them:


  • Find people  who appear on certain black lists.
  • Ensure Financial Action Taskforce on Money Laundering (FATF) compliance.
  • Produce listing of transactions with organizations on the list of non-cooperative countries and territories.


  • Identify cash transactions just below regulatory reporting thresholds.
  • Identify a series of cash disbursements by customer number that together exceed regulatory reporting thresholds.
  • Identify statistically unusual numbers of cash transfers by customer or by bank account.


  •  Identify unusually large number of waived fees by branch or by employee.


  • Highlight very short time deposit and withdrawal on the same account.
  • Find indicators of kiting checks.
  • Highlight duplication of credit card transactions and skimming.

Financial Statement Fraud

  • Monitor dormant and suspense General Ledger accounts.
  • Identify Journal Entries at suspicious times.
The datafusion Platform  is designed to combine information from virtually any data source or format, reaching from communication data, such as telecomunications and Internet, to other organization databases and financial data systems and assemble it on one platform for analysis.
The data are analysed using sophisticated data mining techniques, metadata extraction and a number of analytics measures.