Skip tracing makes debt collection software much more effective. It helps the end-user track down delinquent customers to recover more bad debt. Thanks to API integration, it is also easy to use, requiring no changes to a software’s interface.
Companies offering debt management solutions should consider integrating skip-tracing into their software if not already doing so.
The Current State of Skip Tracing
Skip tracing, the process of tracking down a hard-to-find person, usually a debtor or someone who owes money, has evolved in recent decades. Whereas it once was a process used to locate debtors who had physically “skipped” town, hence the name, it has since gone entirely digital. Even if a debtor is seemingly off the grid, using paper currency, or eschewing the internet and not maintaining a presence on social media, an effective skip tracer can find them.
The speed and effectiveness of quality skip tracers make them the perfect addition to a piece of receivables management software. The end-user saves time and energy once wasted on tracking down debtors, dialing disconnected and wrong numbers, and sending letters and emails to the wrong addresses. The time they used to spend on tracking down bad leads can, instead, be refocused on establishing contact with known leads.
Best of all, the process is almost entirely automated, relying on an array of technology components such as Application Programming Interfaces (APIs), credit reports, loan and job applications, and other types of digital footprints.
Want more tech news? Subscribe to ComputingEdge Newsletter Today!
Big Data’s Role in Skip Tracing
The most advanced skip tracing programs leverage Big Data to pick up the trail of a bad debtor and stay on it until the person is found. They do it in somewhat of a circular fashion. Once the software picks up on a single piece of data, that piece of information often produces one or more additional pieces, each offering clues that lead closer to the elusive debtor.
For instance, a successful skip trace might start with a hit on a recent background check pulled as part of a job application. This might lead to list of previous employers along with one or more addresses where the debtor has lived. The skip tracing software can mine this additional data to produce the names of former roommates, romantic partners, and workplace supervisors. It can then dig into those leads, contacting people who know or once knew the debtor and gleaning more information. The process continues until the debtor is found, and most importantly, it is fully automated.
Common data sources used by skip tracers to locate elusive debtors include property deeds and taxes, bankruptcies, liens, judgments, arrest reports, civil suit filings and enrollment data from colleges or trade schools. This information not only helps find the debtor but also paints a more complete picture of their current financial situation and life circumstances. This can help the end-user prioritize which leads to contact first. The debtor who just bought a big house and deposited money in three different bank accounts, for instance, is likely a better lead than the one knee-deep in bankruptcy and facing multiple lawsuits.
With the help of Big Data, skip tracing software can also locate assets a debtor might have stashed away, such as bank accounts, investments, credit lines, real estate, and more. Skip tracers can access this information from an array of sources, including credit bureaus, electronic transactions, tax filings, court records, and financial disclosures.
Skip Tracing API Integrations
APIs allow computers in disparate locations to share information quickly and securely, and they are vital for efficient skip tracing.
With the use of APIs, it is easy to integrate skip tracing features into debt collection software. When a user initiates a skip trace, a request from the collections software goes out to the skip tracer’s API, which returns the relevant information in a format that the software can read and display.
Without API integration, it would be difficult to offer to skip tracing as part of a piece of receivables management software without overhauling the interface. The end-user might have to juggle the software and the skip tracing program, making the process less user-friendly.
API integration also keeps control of the entire process in-house, obviating the need to depend on potentially unreliable third parties. It also allows for seamless inclusion of skip tracing functionality without the need for a major redesign or, in fact, any tweaks to one’s software interface at all. That is because the entire process happens on the skip tracer’s server. The server, via the API, then returns the relevant information to the software.
Perhaps the biggest advantage of API integration is 24/7 access to up-to-date, real-time data. Skip tracing APIs are constantly being updated with the latest information, as well as purging inaccurate or irrelevant data.
Essential Skip Tracing Features
When building skip tracing functionality for one’s receivables management software, the following features are essential:
Flexible Account Upload
Collections software should allow for manual entry of debtor information along with batch uploading and information sharing via APIs.
Phone System Integration
Once a debtor is found, a receivables management software program should make it easy to contact that person. One-click dialing and the auto-loading of phone numbers returned from successful skip traces make this process fast and efficient.
Intelligent Data Scoring
Intelligent data scoring allows for the scoring of accounts, prioritizing them based on urgency.
When potential new information about a debtor is identified via skip tracing, the software should be able to send a notification right away. Ideally, the end-user should be able to configure these notifications, selecting the level of new information sufficient to trigger a text or email.
Contact Time Suggestions
With the information returned from skip tracing APIs, collections software should be able not only to track down debtors but also to use real-time data and analytics to identify the time of day the end-user is most likely to have success contacting the person.
Timeline-Based Account View
A timeline-based account view organizes the data returned in an organized way that makes it easy to track the process from beginning to end.
Integrating skip Tracing Functionalities
Skip tracing integration is one of the most critical additions to a high-quality debt collection suite. As with recent technological advances, modern skip tracing software is capable of tracking down even the most elusive debtors.
By leveraging big data and using API integration, skip tracing produces the most up-to-date debtor information. Any provider not currently using skip tracing in their debt collection software is missing out on an incredible opportunity to optimize their receivables management systems.