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Posted May 12, 2012 by RhoBeta in Analytics
 
 

Fraud Analytics: How it saved for Santam

Fraud Analytics Santam
Fraud Analytics Santam

According to recent news Fraud Analytics from IBM has saved short-term insurer Santam $2,4m in fraudulent claims. As claimed in the reports the analytics software has enhanced Santam’s fraud detection capabilities. IBM’s predictive analytics software has enabled Santam to automatically assess if there is any fraud risk associated with incoming claims and allows the insurer to distribute claims to the appropriate processing channel for immediate settlement or further investigation, which optimizes operational efficiency. With the enhanced claims segmentation, Santam is also able to reduce the number of claims that need to be assessed by mobile operatives visiting the customer or claim site, resulting in further considerable cost savings for the company.

So Let’s have a brief look at the issue of Fraud Analytics

Fraud is a big problem for many businesses and can be of various types. Inaccurate credit applications, fraudulent transactions (both offline and online), identity thefts and false insurance claims are some examples of this problem. These problems plague firms all across the spectrum and some examples of likely victims are credit card issuers, insurance companies, retail merchants, manufacturers, business-to-business suppliers and even services providers. A predictive model can help removing fraud and reduce a business’s exposure to fraud.

Predictive modeling can also be used to detect financial statement fraud in companies, allowing auditors to gauge a company’s relative risk, and to increase substantive audit procedures as needed. The Internal Revenue Service (IRS) of the United States also uses predictive analytics to try to locate tax fraud. Recent advancements in technology have also introduced predictive behavior analysis for web fraud detection. This type of solutions utilizes heuristics in order to study normal web user behavior and detect anomalies indicating fraud attempts.

Fraud Analytics software combines predictive data modeling technology, identity search technologies, fraud indicator business rules, company claims information and industry data sources to help flag suspicious claims as early as the first notice of loss. Fraud Analytics tools allows an organization to    Detect the fraud in early stage, Identify the right claims, automate time-consuming processes of claim verification, Streamline the workflow and quickly identify suspicious participants or patterns in claims.


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