Project description

Not long after Janelle Duncan\’s Florida real estate agency failed in February 2018, she collapsed and was rushed to the hospital, vomiting bile. Her dreams of entrepreneurship were dashed by a loan company that seized $52,886.93 from her bank account without warning. Duncan had borrowed from what\’s known as a merchant cash-advance company. Completely unregulated, and largely unreported on, the industry has boomed since the financial crisis, luring restaurant owners, truckers, and florists who\’ve been turned away from banks with offers of quick cash.
Through a first-of-its-kind investigation into New York state court records, Bloomberg News was able to uncover an industry that loaned small-business owners an estimated $15 billion last year at interest rates often higher than mafia loan sharks once demanded.

Bloomberg News reporters Zachary Mider and Zeke Faux learned about Duncan\’s story while investigating how cash-advance companies had co-opted New York\’s court system and turned it into a high-speed debt-collection machine. Duncan, like most borrowers, had signed an arcane legal document called a confession of judgment as part of her loan application. By signing, she\’d forfeited her legal rights, allowing the lender to file a court case against her without her knowledge and to win it without a hearing or proof.

But Duncan’s case wasn’t unique. Over a six-month period, with data analysts David Ingold and Demetrios Pogkas, Bloomberg compiled and analyzed hundreds of thousands of New York State court documents to create what’s likely the first database of New York confession of judgment cases. The data revealed a billion-dollar lending industry that leveraged the New York court system to collect on predatory loans in nearly every U.S. state and Puerto Rico.

Mider and Faux interviewed dozens of other borrowers who described lenders forging documents, lying about how much they were owed, or fabricating defaults out of thin air. They developed sources within the industry and convinced them to reveal their tricks. They traced the history of confessions of judgment, from Charles Dickens’s 1837 novel The Pickwick Papers to a boiler room in downtown Manhattan run by the man who inspired the stock-scam movie Boiler Room.

Bloomberg’s five-part series included stories focusing on a New York City marshal who earned $1.7 million last year collecting debts for cash-advance companies, making him the highest-earning city official; on the role of New York county clerks in rubber-stamping the confessions; on one of the industry\’s worst offenders, a convicted marijuana trafficker who built a business-loan empire while out on bail; and on an ex-convict who made intimidating house calls for a cash-advance companies when borrowers fell behind on their debt.

What makes this project innovative?

To facilitate its investigation, Bloomberg compiled and analyzed hundreds of thousands of New York State court documents to create what’s likely the first database of New York confession of judgment cases. The state of New York keeps court documents in a public database called the New York State Courts Electronic Filing System (NYSCEF). But New York court employees were unwilling to provide the bulk data necessary for this story, and the terms of service of the NYSCEF prohibit the use of automated bots or scrapers to access case information. To overcome these challenges, Bloomberg assembled a list of more than 500 cash-advance company names from sources including industry publications and lawyer client lists. Each name was then searched on the New York State Unified Court System’s electronic filing database to identify more than 30,000 civil court cases associated with these companies since 2012. A custom web interface was built by the Bloomberg data team to allow reporters to rapidly access and download documents for each court case without violating the site’s terms of service rules. The system reduced the time it took to acquire documents by months. Court documents from each case were then analyzed using natural language processing scripts to identify those in which the plaintiff filed a confession of judgment and the court entered a judgment in the plaintiff’s favor. The dollar value of about one-third of the judgments was available in the state court database. Additional judgment values were obtained directly from court documents using a combination of optical character recognition and natural language processing scripts. Bloomberg then estimated the value of the remaining cases using a model that combined known values with an additional 1,200 randomly sampled cases to estimate the entire size of the industry. Prior to the Bloomberg News coverage, this amount had never been reported.

What was the impact of your project? How did you measure it?

The series triggered an investigation by the New York attorney general's office, a mayoral review of the city marshals, and calls for reform in the state and federal legislatures. Bipartisan bills were introduced in the U.S. Senate by Sherrod Brown and Marco Rubio, and in the House by Nydia Velazquez and Roger Marshall, calling for a ban on the use of confessions. Clerks in three New York counties have refused to process confession of judgment loans submitted in their court systems. In January, New York Governor Andrew Cuomo outlined a three-part plan to prohibit the use of confession of judgments for small business loans and out-of-state lending activity in New York.

Source and methodology

See project description.

Technologies Used

Python, R, optical character recognition, natural language processing, Javascript, QGIS, Adobe Illustrator, d3.js

Project members

Zachary Mider, Zeke Faux, David Ingold, Demetrios Pogkas



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