Fraud Detection

What is Fraud detection?

Fraud detection on bank statements involves identifying and flagging documents that may contain fake or manipulated data. This process helps ensure that only genuine documents are processed, thereby preventing potential fraud and maintaining the accuracy of financial records.

The document might have been tampered with malicious intentions, which could be detected by authorities to differentiate between genuine bank statements and fraudulent ones.

Fraud checks on bank statements

• To enable the fraud check to be triggered when the document is uploaded, add the additional parameter detect_fraud:true in the pre-processing settings.

• Enable the Fraud Check field in the Edit Fields section of the document type.

  • To apply this change to the actual field being populated, the documents must be manually retried.

  NOTE: For older and existing document types, you need to reset the document type to enable the fraud table field to be visible on the Edit Fields page.

  

The Fraud Check field is a table grid representing two tables.

1. All the checks that have been applied to the document
2. All the checks that failed (i.e. which might indicate that it is a probable fraud) in in-depth with description/position

Fraud Table

Table 1: All the checks applied on the document

Table 2: All the checks that failed

The second table will display individual checks and indicate the exact position where tampering or anomalies may have occurred.

There won't be a position for generic checks like tally_checks or document meta-data checks like EXIF analysis.

Transaction-level checks are conducted on the extracted transaction tables in the document. These checks include verifying the account information, such as opening and closing balances, and the start and end dates.

The amount layout alignment check also uses the OCR data from the extracted transaction tables.

Checks

There are 3 categories of checks currently implemented into the Bank statement API, in all, there are 17 individual fraud checks as follows:

1. EXIF Analysis: This analysis examines the document's metadata for signs of tampering or suspicious values. It checks metadata fields such as author, producer, and creator against a known set of whitelisted and blacklisted terms and keywords. If any match is found, the check is marked as fraud. Additionally, it verifies PDF trailer tampering and validates the checksum from the trailer.
2. Transaction Analysis: This analysis identifies anomalies or patterns in transaction table data extracted from the bank statement document. It includes basic checks on the tally, daily balance, repeated or overly frequent transactions, anomalies in transactions (such as inconsistent trailing digits or high amounts), circular or round trip transactions, and invalid dates.
3. Amount Layout Analysis: This analysis detects position-related anomalies in the amount/debit/credit columns. If a row deviates in position range from other rows, it is flagged as a suspicious transaction.

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There might be erroneous fraud detection

There might be instances where the document might not be fraud per se, but there might be fraud checks failing for that document, those could be for a few justifiable reasons:

• The image quality in the document is low due to which the extraction and analysis might not have been accurate enough.
• The document might have such a structure that might cause fraud checks giving false positive analysis of the layout or data.

In case of an error from the fraud module, the fraud check table will be a row table with the description marked as Error during fraud analysis or Fraud check timed out. in case of a timeout issue from the processing of data.