Unifin Employs Prodigal’s Natural Language Engine for Improved Customer Service
Region
- America
Country
- United States
Product
- Prodigal’s Natural Language Engine
- Prodigal’s smart reports
Tech Stack
- Natural Language Processing
- Data Analytics
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Employee Satisfaction
Technology Category
- Analytics & Modeling - Natural Language Processing (NLP)
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Finance & Insurance
Applicable Functions
- Human Resources
- Sales & Marketing
Use Cases
- Speech Recognition
Services
- Data Science Services
About The Customer
Unifin is a company that provides support, assistance, and education to borrowers throughout the loan process. The company prides itself on its highly trained agents who engage and collaborate with borrowers over the phone. Unifin is committed to maintaining a high level of empathy towards borrowers, particularly those affected by the pandemic. The company has established a moral code of conduct for its agents to follow during such calls, and any violation of this code is taken seriously.
The Challenge
The coronavirus pandemic led to a sudden loss of jobs for approximately 15 million Americans. This situation led to a surge in stressful discussions between Unifin's agents and borrowers, particularly concerning loss of employment and health concerns among the elderly. Unifin identified a problem where some agents failed to empathize with the borrowers' stressful situations, which was considered a Level 4 infraction. Unifin needed a quick mechanism to identify these infractions among thousands of calls each day and educate the agents to drive more empathy towards borrowers.
The Solution
Prodigal’s Natural Language Engine was employed to identify stressful discussions related to loss of employment and health concerns among the elderly. The engine, with its expertise in the collections domain, was able to surface insights without specifically being asked to search for a list of keywords. It flagged all conversations of this nature and made the trends prominently visible on its interface. This made it easy to identify agents who were repeat offenders or needed coaching. Prodigal’s smart reports were shared with all clients for free within two weeks of the shutdown being enforced.
Operational Impact
Quantitative Benefit
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