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A code-driven approach to legal debt collection

By Staff

Juggling multiple accounts at the same time can be a real “liability nightmare” for lawyers who do debt collection, says Toronto litigator François Sauvageau.

“Thankfully, machine learning and code-driven audit systems now exist to assist lawyers operating in that field,” says Sauvageau, president and CEO of CTL Law.

“This new approach offers a more predictable and auditable process, while also giving a best-in-class user experience to debtors,” he tells

“It also reduces the risk of complaints and other compliance concerns often associated with debt collection.”

CTL is a collection law firm with a mission to redefine the boundaries between law firms and collection agencies by using the most advanced technology.

“While human interactions will always remain an important part of the process,” says Sauvageau, “the traditional collection model is incomplete, outdated and broken.”

He says the process should be well-documented and process-driven “in ways that minimize and neutralize its weakest leak — humans making collection calls.”

Sauvageau isn’t saying that machine-based systems are more effective than people or that phone calls are obsolete. But to err is human, he says.

“For that reason, it is essential that phone calls be data- and script-driven and used only to complement and enhance the experience for the debtor,” he says.

“For example, a person may simply require some assistance making their payments — they may prefer to explain their concerns over the phone as opposed to in writing or they may simply want someone to listen to their story about a disputed debt prior to making financial arrangements,” says Sauvageau.

“All these interactions are crucial to a successful collection operation and require well-trained humans.”

But the system must be supported “by well-defined and tech-controlled communication schedules, escalation and litigation strategies, and scripts for phone calls and written correspondence,” says Sauvageau.

Communications should also be monitored by speech analytics systems “which can guide the humans in real time or protect them from ill-intended debtors baiting them,” he says.

“Ultimately,” says Sauvageau, “if a debtor refuses to pay after receiving a legal demand letter and the courtesy of a phone call to offer assistance in resolving a debt issue, collection agents and creditors must be prepared to commence litigation or abandon their claims.”

He says there’s too much risk in continuing to call someone who refuses to pay.

“If a proper litigation strategy is in place, the discussions between the parties can continue after legal proceedings begin, but in a way that’s designed to encourage proper discussions, exchange of information and timely progress,” says Sauvageau.

“Cutting-edge technology is an absolute necessity to manage a large, volume-driven legal collection operation,” he says. “With the proper technology, collectors — lawyers and non-lawyers alike — will always have a place in the process.”

Sauvageau says their assistance will still be needed for settlement and pre-trial conferences and mediation — all the tools needed to help parties reach settlements and avoid going to trial.

“Humans will always be a crucial part of the debt-collection process,” he says, “but their interactions must be better managed with improved technology so they take place at the right time, in the right context and between the right actors. Otherwise, debt collections will remain a compliance nightmare.”

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