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Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.
SAS 99 defines fraud as an intentional act that results in a material misstatement in financial statements. There are two types of fraud considered: misstatements arising from fraudulent financial reporting (e.g. falsification of accounting records) and misstatements arising from misappropriation of assets (e.g. theft of assets or fraudulent expenditures).
It is widely used in the financial sector, especially by accounting firms, to help detect fraud. In 2022, PricewaterhouseCoopers reported that fraud has impacted 46% of all businesses in the world. [1] The shift from working in person to working from home has brought increased access to data.
Technology that works with big data can work alongside audit evidence to increase the quality and efficiency of an audit. Big data uses pattern recognition, natural-language processing, and data mining to elevate audit data analytics, [2] which is briefly discussed in the paragraph below.
Data auditing is the process of conducting a data audit to assess how company's data is fit for given purpose. This involves profiling the data and assessing the impact of poor quality data on the organization's performance and profits.
ELKI is an open-source Java data mining toolkit that contains several anomaly detection algorithms, as well as index acceleration for them. PyOD is an open-source Python library developed specifically for anomaly detection. [56] scikit-learn is an open-source Python library that contains some algorithms for unsupervised anomaly detection.
Detailed guidance about performing the TDRA is included with PCAOB Auditing Standard No. 5 (Release 2007-005 "An audit of internal control over financial reporting that is integrated with an audit of financial statements") [1] and the SEC's interpretive guidance (Release 33-8810/34-55929) "Management's Report on Internal Control Over Financial ...
Hunter Fraud Score is a rating score in India prepared by the credit information company Experian to help detect fraud in credit applications through analytical approach. The score was launched in 2016 and is used by Indian banks and insurance companies to help them lower their losses.