“Fraud detection is a topic applicable to many industries including banking and financial sectors, insurance, government agencies and law enforcement, and more. Fraud attempts have seen a drastic increase in recent years, making fraud detection more important than ever. Despite efforts on the part of the affected institutions, hundreds of millions of dollars are lost to fraud every year. Since relatively few cases show fraud in a large population, finding these can be tricky.
In banking, fraud can involve using stolen credit cards, forging checks, misleading accounting practices, etc. In insurance, 25% of claims contain some form of fraud, resulting in approximately 10% of insurance payout dollars. Fraud can range from exaggerated losses to deliberately causing an accident for the payout. With all the different methods of fraud, finding it becomes harder still.
Data mining and statistics help to anticipate and quickly detect fraud and take immediate action to minimize costs. Through the use of sophisticated data mining tools, millions of transactions can be searched to spot patterns and detect fraudulent transactions”.
Participants will learn:
- How to use analytic techniques to locate those leading indicators necessary for fraud detection;
- The construction of preventative measures, or, at worst, an early warning system, or “fraud monitoring” system;
- Detecting of money laundering schemes, human smuggling operations, narcotics trafficking, and exposing fraud patterns;
- What techniques have been used to successfully detect fraud and recover millions of dollars;
- Why data mining techniques, when combined with traditional audit techniques such as observation and confirmation, result in the most powerful, most effective audits;
- How to incorporate data mining techniques into their audit programs to detect the symptoms of fraud and error