When done manually, skip tracing takes an awful lot of time. Since finding individuals trying to vanish from any existing record isn’t easy, the support from AI-based software can be an actual game-changer. Hence in this article, we’ll review the key benefits of debt collection automation and how Alphamoon can help you and your team work more efficiently.
The recent news regarding the inevitable end of the start-up bubble will likely have an immense impact on the debt collection industry. Some argue it’s not all that grim, but start-ups in 2022 fall like dominos.
Think about the rise-and-fall story of Klarna.
After reaching its unicorn status back in 2014, and cementing its hegemony in the Buy Now Pay Later services market with its whopping $46 billion evaluation in 2021, Klarna collapsed and reached a $6.5 billion evaluation in the beginning of July this year.
To quote a brilliant sentence from a movie called “A Place Beyond The Pines” – if you ride like lightning, you crash like thunder.
Perhaps the essential information for debt collection companies is the industry that Klarna gave rise to. Buy Now Pay Later encouraged customers to escape the wrath of traditional credits by postponing payments. Customers made Buy Now Pay Later big because many business owners dreaded the delayed payments and cash flow issues. And that pretty much gives an insight into why debt collection may soon notice a surge in new cases.
For your debt collection business, that may mean the point where your usual operations will need to adapt quickly. Among the areas where you may look for process enhancement, there’s one that’s currently on the rise – skip tracing automation.
Let’s review the principles of the skip tracing process and see how automation improves it.
What is skip tracing?
Skip tracing is the part of the debt collection process where specialists try to establish the whereabouts of a debtor based on data from dozens of documents and databases. This refers to those debtors, who failed to respond to any previous calls for payment.
Usually, skip tracing ends with court proceedings – enforcing a judgment lien – and granting the creditor the right to collect the owed amount. That being said, building such a case requires lots of time.
It’s like playing hide and seek, isn’t it?
A skip tracer’s job is to find any relevant link to the debtor. This involves numerous points of contact, from known acquaintances of the debtor to official parties such as public sector institutions. What begins with the credit application morphs into a long journey.
The person who owes money, on the other hand, tries to cover the tracks, conceal any evidence and be in the wind.
The cat and mouse game.
Now, finding this one key piece of information often requires a massive amount of effort. Not only that but also generates errors and unnecessarily incurred costs along the way. Debt collection is an administrative-based activity where patience and meticulousness pay off.
If you – or your team – perform this needle-in-the-haystack job without any automation, then the pile of documents that require a deep scan can be overwhelming.
Intelligent Document Processing can help you automate part of the debt collection process – here’s how.
Intelligent Document Processing in automated debt collection
IDP, short for Intelligent Document Processing, revolves around the implementation of AI in document workflows.
The goal of IDP is to turn loosely connected, unstructured data from documents into an orderly, coherent set of data pieces, ready for further processing and knowledge extraction.
Now, how does it relate to debt collection?
Each debtor case means a variety of documents that store information about this particular individual. While the types of these documents vary, you’re likely to have experience with some of the following:
- Driver’s license information
- Court records, criminal background checks
- Bank account history (including loan applications)
- Public online registries
- Credit reports & credit card applications
- Real estate documentation (lease/rental, utility bills)
- Travel tracks (air travel records, recorded stays)
Skip tracers usually need to scrutinize each doc, looking for clues, addresses, phone numbers, and other pieces of information that can reveal a trace.
This is a complex, investigative line of work that takes time.
On the other hand, that’s hours of manual work too, filled with flipping pages, highlighting relevant information, and building a case.
Luckily, you’re in the right place to see how automation lifts that weight off your shoulders.
Applications of Alphamoon’s IDP platform in debt collection
Alphamoon helps companies in debt collection by cutting through the data noise and enabling teams to access relevant data much faster.
Take a look at the three core capabilities that empower teams to work smarter and with a focus on less monotonous tasks.
- OCR & Data extraction
AI-based OCR, which stands for Optical Character Recognition, deploys AI to “translate” all kinds of visual objects into data. This modern technology overcomes the rule-based models that were commonly used a few years ago. The application of AI in OCR empowers the tool to understand – as humans do – objects such as tables, handwritten signatures, and so on.
In the case of documents, the AI-base OCR function is supported by preprocessing stage of document classification. When a document is uploaded, the tool automatically recognises its layout and assigns a tag – an invoice, a contract, a purchase order etc. Alphamoon also includes the document parsing function for large PDFs with multiple scanned documents.
AI OCR pairs up with data extraction, which is the step in which the AI recognizes particular fields from the document and gathers it all in a structured set of data.
This set is often referred to as Knowledge Base. The extracted fields can be approved one by one or as an entire doc. Each Knowledge Base can be downloaded as a CSV file too.
Click below to read about the performance of Alphamoon’s data extraction feature on invoices and receipts.
- Full-Text Search (Skip Tracing case)
One of the most powerful applications of Intelligent Document Processing in skip tracing is the Full-Text Search feature. Each debtor’s case consists of dozens if not hundreds of documents that skip tracers use to establish means of locating the individual.
This is a long, complex process.
After Alphamoon’s software scans documents and extracts data from them, they can be stored in separate files. Whenever you or your team needs to return to a specific piece of information – furthermore, check the context of how it’s been used – this feature recognizes the query’s location.
This function also helps skip tracers cross-reference data from public databases with the sets of documents received for analysis. One of Alphamoon’s customers, Polish debt company KRUK S.A., has implemented the skip tracing solution and automated processing of over 400.000 documents monthly. This also resulted in a 70% faster process of data extraction and information collection.
- Document classification & document parsing
Compiling the documents into one case file often means sourcing them from various entities – courts, public registers, employment history and other types of info directories. As a consequence, the templates of these downloaded or received documents differ, depending on their type.
Alphamoon’s engine understands documents and classifies them, based on the powerful object recognition function. When they’re delivered as one clustered pdf, the tool can also conduct document parsing, which is the step required for classification.
- Data anonymization
The process of data anonymization is one of the most innovative applications of AI-based IDP. While its main target is consulting companies, data anonymization can help debt tracers too.
All of the docs used in the process of debtor info collection include sensitive data. Since potential prospects may be interested in seeing your previous success stories, data anonymization enables you to mask sensitive data in files you’d like to share with potential customers.
Other areas of debt collection automation
While IDP supports the work of skip tracers, there are other aspects of the entire debt collection process that you might want to optimize through AI and other advanced software.
- Automation of basic communication (calls, messages)
After data is collected and processed, the next time-consuming (and often frustrating) part of the process is validating the points of contact. In the past, skip tracers had to investigate by conducting phone screening, sending mail, but also knocking on doors, and meeting with relatives or close collaborators with the tracked individual.
Thankfully, a part of this process can be automated with tools such as Simplifai. Thanks to their virtual assistant, you’ll be able to automate calls and emails sent to the debtor’s addresses, as well as set automatic replies to your customers.
- Speeding-up the transactions
Automation of payments can be adjusted to the needs of debt collection businesses through payment notifications, streamlining payments, and providing numerous and convenient means of payment to ensure swift debt recovery.
- Debt surveillance
Debt surveillance supports a coherent overview of all the open cases and enables monitoring of each case’s stage. You will also provide customers with a better grip over their collection progress.
- Automation of debt purchased
Tools such as Aptic help debt collectors in smoothing things up with debt sales and purchases.
Benefits of Automation in Debt Collection
Perhaps you’re still wondering what long-term benefits stem from the implementation of automated debt collection. At the end of the day, it’s an investment that you need to be sure of.
Investment in process automation can be a part of a broader technological transformation, and you’re right to expect an overview of the potential gains for your company.
- Automation establishes a bulletproof process
That may sound cliche, but well-established processes are the beating heart of every successful business. When people operate within a given framework, with clearly indicated roles and expectations, they tend to be far more productive and organized.
Moreover, automation can ensure your work aligns with the Fair Debt Collection Practices Act and other regulating documents that set the standards for best practices in the industry. As a result, your team operates within legal boundaries at all times, which significantly reduces the space for mistakes and any abuse of information or privacy that may badly impact the judgment lien.
- Reduction of time spent on cross-referencing data
One particular pain point in the process of skip tracing is cross-referencing extracted data.
To establish means of contacting the debtor across various channels and angles, skip tracers often need to double-check that the given contact information appears in more than one document. An address that repeatedly appears in a set of docs has often a higher chance of bringing the company closer to reaching its debtor.
- Cloud access to files
There are several ways of storing digitized documents. The most basic solutions include G-Suite, Microsoft’s One Drive, and Dropbox – along with all the alternatives.
However, none of these tools enables any kind of document processing capabilities – such as Full-Text Search.
For that reason, it’s best to keep debtor files in cloud-based storage that offers intelligent automation.
- Future “prospecting” of delinquent payers
Debt collection has the bad rep of a business that deals with criminals who refuse to pay off their liabilities. It’s a hurtful image, bolstered by shady companies that “enforce” debt payments through the muscle, as well as loan sharks that entrap the neediest customers.
In reality, debt collection offers a valuable insight into a client’s liquidity and cash flow.
Automation of debt collection unlocks the prospecting aspect of such analysis too. By extracting data concerning a group of delinquent individuals or contractors, companies can profile customers – or vendors – with predictive analysis. Having that kind of risk assessment tool at hand largely pays off in moments of cash flow fluctuations.
- Reducing human-made errors
Last, but not least, automation often results in fewer errors. Say goodbye to erroneous debt write-offs, or delayed warning letters. By creating a tighter process, you’re also increasing the profitability of your business.
Conclusion
With the current economic trends, debt collection may experience exponential growth that will surpass the $17.9 billion market evaluation forecasted in the US. To fully benefit from the trends that are likely to boost this growth, you need to step up your game and automate repetitive processes and tasks.
Get in touch with Alphamoon and find the best way to implement automation in your debt collection business.
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