Debt Relief Leader Leverages IoT to Improve Efficiency and Reduce Costs
Technology Category
- Cybersecurity & Privacy - Security Compliance
Applicable Functions
- Quality Assurance
Use Cases
- Behavior & Emotion Tracking
- Leasing Finance Automation
Services
- Testing & Certification
About The Customer
The customer is a leading debt relief company based in New York City, NY. Founded in 2009, the company is committed to providing financial assistance and solution options to hundreds of consumers seeking to reclaim their financial freedom. The company is recognized as the most-trusted and best-rated debt settlement option in the country. They are dedicated to improving operational efficiency and mitigating compliance risk to better serve their clients and maintain their industry-leading position.
The Challenge
The company, a leading debt relief firm, was facing significant challenges in monitoring customer interactions and improving agent performance. They were only able to monitor a small percentage of calls, which was not providing enough data for meaningful business insights. This lack of visibility was leading to high compliance risk and potential loss of client trust. The company was in dire need of a data-driven solution to enhance agent performance, reduce risk, and build client trust. The potential revenue loss due to these challenges was estimated to be up to $15M industry-wide.
The Solution
The company adopted a comprehensive solution that provided business insights from 100% of calls, significantly improving efficiency and empowering agents to perform better. This solution helped the company reduce overhead costs by automating manual operational tasks, leading to faster processes and a 62% reduction in overhead costs. This cost saving allowed the company to allocate more budget towards upskilling and hiring for strategic roles. The solution also provided full visibility into customer interactions, improving compliance monitoring efforts by 97%. This helped in reducing litigation costs, compliance breaches, and preventing revenue loss. Furthermore, the company leveraged Observe.AI’s automated workflows to enable teams to work smarter and more efficiently. This resulted in the Quality teams being able to double their output, running 14,000 Quality evaluations per month instead of the previous 7,000.
Operational Impact
Quantitative Benefit
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