To Monitor and Detect Suspicious Transactions in a Financial Transaction System Through Database Forensic Audit and Rule-Based Outlier Detection Model

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Author(s): Harmeet Kaur Khanuja (Marathwada Mitra Mandal's College of Engineering, India)and Dattatraya Adane (Shri Ramdeobaba College of Engineering and Management, India)
Copyright: 2019
Pages: 32
Source title: Organizational Auditing and Assurance in the Digital Age
Source Author(s)/Editor(s): Rui Pedro Marques (University of Aveiro, Portugal), Carlos Santos (University of Aveiro, Portugal)and Helena Inácio (University of Aveiro, Portugal)
DOI: 10.4018/978-1-5225-7356-2.ch012

Keywords: Accounting & Finance / Accounting and Finance / Business & Management / Business Science Reference

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Abstract

The objective of this chapter is to monitor database transactions and provide information accountability to databases. It provides a methodology to retrieve and standardize different audit logs in a uniform XML format which are extracted from different databases. The financial transactions obtained through audit logs are then analyzed with database forensic audit. The transactions are examined, detected, and classified as per regulations and well-defined RBI antimony laundering rules to obtain outliers and suspicious transactions within audit logs. Bayesian network is used in this research to represent rule-based outlier detection model which identifies the risk level of the suspicious transactions.

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To Monitor and Detect Suspicious Transactions in a Financial Transaction System Through Database Forensic Audit and Rule-Based Outlier Detection Model

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