Michael Goh
Cofounder
About
Michael formerly worked alongside leading AI research labs, including Amazon, to benchmark and evaluate their speech models. He was also an Engineering Fellow and Investor (FinTech) at Quest Ventures, and a management consultant at Bain & Company. Michael earned his MS in Computer Science from the University of Chicago, where he was a Global Fellow, and his BA in Economics and Management from the University of Oxford, where he was a Fung Scholar.
Articles by Michael Goh
How can AI Reduce Operational Costs for 1st and 3rd Party Receivables Teams?
Delinquency management remains one of the most expensive and resource-heavy functions for 1st and 3rd party receivables teams. Staffing call centers, managing turnover, training agents, and monitoring compliance all add significant operational costs to recovering delinquent accounts. At the same time, rising delinquency volumes and customer expectations for faster, more flexible engagement make it increasingly difficult to scale collections operations without driving costs higher.
Read articleAI Receivables Workers for Higher Education Institutions
In today’s landscape, higher education institutions face mounting pressures to manage small-balance arrears, alumni donations, and other receivables - all while delivering an empathetic, student-centric experience. Traditional receivables teams are often stretched thin, relying on manual outreach and juggling compliance requirements that leave precious resources tied up in administrative busywork. Enter AI Receivables Workers: a new class of digital agents that operate 24/7, speak multiple languages, and integrate seamlessly with your existing systems to drive down costs and boost recovery rates.
Read articleEvaluating AI Workers in the Receivables Industry
As receivables teams look to boost efficiency and customer satisfaction, large language models (LLMs) like GPT-based chatbots are an exciting frontier. But before you hand over your most sensitive outreach to an AI agent, you need a straightforward way to vet providers - and make sure their tech lives up to your goals, compliance standards, and customer-care values. This guide gives you an 6-step framework for evaluating any AI partner in collections, without diving into code or AI research papers.
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