Tracing and Recovering Fraud Losses
Introduction to Tracing and Recovering Fraud Losses
This opening session will introduce you to asset recovery. The topics covered in this session will include defining assets, why people hide assets, hidden versus known assets, hiding versus money laundering, ways assets are hidden, and the steps you must take to expose and identify the methods of uncovering hidden controls over, and interest in, property.
Legal Aspects and Considerations
Sources of Information
Non-traditional Recovery Options
Using the Internet and Social Media to Locate People and AssetsLearn how to use Internet services and websites, such as social networking sites and other information resources, to obtain information about assets, people, businesses and fraud in general. Also, you will learn how to determine the location of a website’s server and a five-step approach to conducting an Internet investigation.
Enforcing a Judgment
Using Financial Records to Locate Hidden Assets Financial records are not only used as evidence for fraud, but also can be used to identify witnesses, criminal assets, localities where assets are stored, and more. This session will examine common types of financial records valuable to a fraud examination, ways to obtain and review financial records, and how to use financial records to locate assets.
Finding and Seizing Assets Held Abroad Locating and recovering assets sited abroad is a slow, arduous process that may take months or years due to the dependence on foreign assistance, which can be hindered by legal and cultural differences. This session will provide guidelines for fraud examiners seeking to find and recover assets stored abroad.
Using Data Analytics
to Locate Hidden Assets The use of data analytics to identify trends, patterns, anomalies and exceptions within data is an effective approach to combat fraud and such tactics are especially useful when fraud is hidden in large data volumes and manual checks are insufficient. This session will introduce you to the basics of using data analysis techniques to find hidden assets.