Fraud's effect on an organization's bottom line is just the tip of the iceberg. Without a proactive approach to combating fraud, the ability to gain and to maintain customer loyalty is almost non-existent. According to Meridian Research, in 2005 alone, the cost of U.S. companies not using anti-fraud applications was $60 billion. Additionally, organizations are said to lose an average of six percent of their annual revenue to fraud and abuse committed by internal employees. An organization's loss of revenue is only the immediate issue involved in not dealing with fraud proactively. Lack of customer faith and of perceived security lead to long-term loss in revenue and the inability to stay competitive in a quickly changing market.
A proactive approach to fraud identification is the only way to address and to lessen the effect of fraud on organizations today. Aside from the security provided to customers, the amount of money saved by organizations is large considering the financial payoff of implementing a fraud analytics solution. This column addresses financial-based fraud; other related topics, such as the use of analytics for homeland security, etc., will be discussed in a subsequent acolumn. This column also identifies how fraud analytics differs from general analytics use within business intlligence (BI), the human factor required for effective fraud detection and the technical implications of implementing fraud analytics within an organization's current business intelligence environment.
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