Skiptrace

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Skiptrace (also skip tracing, or debtor and fugitive recovery[1])[2] is the process of locating a person's whereabouts. A skip tracer is someone who performs this task, which may be the person's primary occupation. The term "skip" (as a noun) refers to the person being searched for, and is derived from the idiomatic expression "to skip town", meaning to depart (perhaps in a rush), leaving minimal clues behind to "trace" the "skip" to a new location.

Skip tracing tactics may be employed by a Skip tracer, debt collector, process server, bail bondsman or bail agency enforcer (bounty hunters), repossession agent, private investigator, lawyer, police detective, journalist, stalker or by any person attempting to locate a subject whose contact information is not immediately known. Similar techniques have also been utilized by investigators to locate witnesses in criminal trials.[citation needed]

Methods[edit]

Skip tracing is performed in stages. The first step is to verify the information provided by the client to understand who the subject is and if the client has any misinformation. Then the skip tracer will start collecting as much information as possible about the subject. The information is then analyzed, reduced, and verified. Sometimes the subject's current whereabouts are in the data, but are obfuscated by the sheer amount of information or disinformation. Often, the job becomes more than mere research since one must often employ methods of social engineering, which involves calling or visiting former neighbors, or other known contacts to ask about the subject, sometimes under false or misleading pretenses.

Records that "skiptracers" use may include phone number databases, credit reports (including information provided on a loan application, credit card application, and in other debt collector databases), job application information, criminal background checks, utility bills (electricity, gas, water, sewage, phone, internet, and cable), social security, disability, and public tax information. While some of these records may be publicly available, some cannot be accessed without an appropriate search warrant, which is generally only available to law enforcement or licensed private investigators.[citation needed]

Even when no specific information is returned, public and private databases exist that cross-reference skiptracing information with others the "skip" may have lived with in the recent past. For instance, if previous records show a "skip" lived in the same house as a third party, the third party may also be skiptraced in an effort to locate the primary target.[3]

In the past skip tracing used to include things like “Dumpster Diving” and “Pretext calls” to utility companies. These days a lot of skip tracing is conducted online with using paid search sites[4] and phone calls[5]. Websites like Facebook and Myspace have made a skip tracers life a lot easier[6]. Skip tracers will subscribe to a number of paid databases to help them gather and verify information[7].

Predictive Skip tracing[edit]

Predictive Skip tracing uses advanced analytics to make predictions on where "skips" are located. The use of PAM models (Probable Address Models) are vital to businesses who have a large number of customers that skip[citation needed]. PAM modeling can be used to locate people and identify customers who have a high probability to skip.

Predictive Skip tracing was started in Australia by Brad Lyons who conducted talks around the area of predicted skip tracing and data in collections[8][9]. Brad Lyons is also involved in developing OSINT tools and also helps to keep Fravia' alive by hosting a number of backups of searchlores[10] and is the author of Vanish[citation needed].

Predictive Skip tracing uses a mix of historical and current data to help deduce a person's current location or probability to skip. In the early days, PAM models would show results with a 70% probability of the person's current address[citation needed]. Now PAM modeling can return a 100% confidence score on the likelihood the customer is living at the predicted address[citation needed].

PAM models were designed for the Debt collection industry and law enforcement, however multiple industries, including charities) are starting to explore how PAM modeling can be used to help them with customer retention[citation needed].

See also[edit]

References[edit]