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Development of Automated Procedures to Identify Data Anomalies in the Payment System Utilities

Student: Morozov Dmitry

Supervisor: Vladimir I. Grekul

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Master)

Year of Graduation: 2017

Nowadays during the process of financial audit, the auditing companies face the task of confirming the revenue from the provision of services or the sale of the goods. Most often, the company's revenue is directly related to the volume of sales of goods or services, for example, the revenue of an enterprise that sells gas to individuals is equal to the product of the volume of gas sold at a tariff established by the company or government agency. To account the charges and payments for services provided, companies use billing systems that store customer master data (addresses, number of people living in an apartment, property area, etc.), data on the accrual of services (volume, tariff, chronology) and payment data (accounts payable). In order to reduce the randomness of subscriber selection for further manual testing, it is suggested to use data analysis methods to identify potentially the most suspicious subscribers, charging them will almost certainly turn out to be incorrect or will result from fraudulent transactions. Within this master's thesis has been developed a method for determining anomalies in samples of data from billing systems of companies providing utility services.

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