Financial-statement fraud in the oil and gas sector poses a significant challenge necessitating advanced detection methods. This study evaluates the effectiveness of integrating techniques from two approaches to enhance fraud detection in scanned financial documents. The research addresses limitations of existing rule-based algorithms by adopting a novel hybrid approach. The methodology incorporates an encryption technique to generate unique cryptography for document images, enabling fraud-evidence identification through cryptography comparisons.
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