Fraud Management via Analytics

Fraud analytics is an emerging tool as it relates to detecting anomalies and patterns within voluminous amounts of big data. Fraud prevention measures can  be used to look beyond the individual data points in an organization, to the connections that link them. Often these connections go unnoticed until it is too late. The sole objective of fraud analysis is to develop the most precise and valid inferences.The rationale being used here is that unexpected patterns can be symptoms of possible frauds.

Ratio analysis: It involves the calculation of ratios for key numeric fields. Like financial ratios that give indications of the relative health of a company, data analysis ratios point to possible symptoms of fraud. Three commonly employed ratios are: maximum/minimum, Maximum/Second highest and current year to the previous year. Unexplained deviations could be symptoms of fraud

Network analysis:Mapping relationships helps identify potential vulnerabilities within network between entities to identify association networks. As organizations grows, more complex relations get developed within and outside the establishments, which needs to be monitored, for any untoward development of ambiguity other than normal. It could reveal normal and anomalous patterns of interaction within and between people or groups, can expose facilitators of fraud.