Prodigal Technologies Inc.
![Prodigal Technologies Inc. Logo Prodigal Technologies Inc. Logo](/files/vendor/prodigal-technologies-inc.6687520b38f35_1.jpg)
Overview
HQ Location
United States
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Year Founded
2018
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Company Type
Private
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Revenue
$10-100m
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Employees
51 - 200
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Website
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Twitter Handle
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Company Description
Prodigal maximizes payments for lenders and debt collectors by building dynamic strategies and motivating consumers with highly engaging, personalized treatments. Our advanced genAI has been trained on over 400 million consumer finance conversations, delivering unmatched industry expertise so you can drive record recovery rates. Experience the power of intelligent debt resolution with Prodigal’s AI that pays.
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Case Studies.
Case Study
Healthcare Debt Collections Agency Boosts Productivity with AI
A leading Illinois-based collections agency, specializing in healthcare and retail receivables, was facing a significant challenge in managing their after-call work. The agency wanted to minimize the time their agents spent on after-call tasks and increase their in-call productive time. The goal was to enable their agents to work on more accounts and focus more on talking to borrowers, rather than getting distracted by other tasks. The agency was looking for a solution that could help them streamline their operations, increase productivity, and ultimately, improve their bottom line.
Case Study
Boosting Call Efficiency and Profitability: Rash Curtis & Associates' Experience with ProNotes
Rash Curtis & Associates, a collections agency, was grappling with the challenge of losing significant agent call time daily to repetitive tasks such as comprehensive note-taking. The agents were required to swiftly move from one call to another, build relationships with consumers, and document each call meticulously, all without any assistance. This situation often led to a conflict between the need for detailed note-taking and maximizing call time within a day. Upon learning about Prodigal’s ProNotes, an AI-driven, real-time call summary assistant, Rash Curtis & Associates hypothesized that automated call note transcription could potentially reduce collection costs, standardize after-call notes, and proactively route calls to the most suitable collections teams.