A Study on Prevention and Detection of Financial Frauds

Exploring the Benefits of Data Mining in Financial Fraud Detection

Abstract

Data mining aims to discoverhidden knowledge, unknown patterns, and new rules from large databases that arepotentially useful and ultimately understandable for making crucial decisions.It applies data analysis and knowledge discovery techniques under acceptablecomputational efficiency limitations, and produces a particular enumeration ofpatterns over the data. The insights obtained via a higher level ofunderstanding of data can help iteratively improve business practice. Data mining is able to uncoverunknown patterns and predict future trends and behaviors in financial markets.It creates opportunities for companies to make proactive and knowledge-drivendecisions in order to gain a competitive advantage. Data mining has beenapplied to a number of financial applications, including development of tradingmodels, investment selection, loan assessment, portfolio optimization, frauddetection, bankruptcy prediction, real-estate assessment, and so on. Thecompetitive advantages achieved by data mining include increased revenue,reduced cost, and much improved marketplace responsiveness and awareness.