Observe.AI > Case Studies > Top Finserv Co. Optimizes Compliance and Agent Performance with QA Automation

Top Finserv Co. Optimizes Compliance and Agent Performance with QA Automation

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Technology Category
  • Analytics & Modeling - Machine Learning
  • Cybersecurity & Privacy - Security Compliance
Applicable Industries
  • Automotive
  • Equipment & Machinery
Applicable Functions
  • Procurement
  • Quality Assurance
Use Cases
  • Leasing Finance Automation
  • Personnel Tracking & Monitoring
About The Customer
The customer is a top financial services company that provides portfolio management, lending solutions, asset retention, and more, via proprietary underwriting and loan management technologies and systems. The company has a growing agent workforce and a limited QA staff. The company's agent teams are highly consultative, helping clients throughout the full process of loan procurement. Agents work with clients to sell loans, collect payments, and if needed, pursue collections. These multiple touchpoints provide opportunities for discovery and upsell on loan plans.
The Challenge
A leading financial services company was facing challenges in maintaining compliance and optimizing agent performance due to limited QA staff and increasing agent headcount. The company relied on spreadsheets and six-page QA evaluation forms to score and grade agent performance, which only allowed them to grade 10% of agent interactions each month. This limited QA coverage resulted in a lack of clear insights into how agents were successfully pitching lending solutions to clients, making it impossible to replicate successful strategies across their workforce. Additionally, as the company increased its agent headcount without growing its QA analyst headcount, it needed more compliance oversight. The challenge was to scale service, revenue, and performance while maintaining quality, compliance, and customer experience.
The Solution
The company adopted Observe.AI Auto QA, an AI and machine learning solution that automates the QA evaluation process. This allowed the company to increase QA volume and transform its agent performance improvement strategy to improve compliance and increase revenue growth across the business. The solution enabled the company to track agent performance and identify its top three QA attributes across all their calls, including monitoring agents for professionalism, agent disclosure of mandated compliance statements, and ensuring agents follow identity verification procedures. Observe.AI also helped the company unify their conversation analytics, QA evaluation process, and coaching workflows under one platform, reducing more than four different applications to one and cutting the time it takes to complete QA evaluations in half. The company was also able to optimize agent talk-tracks for revenue generation and close-rates, and gain 100% confidence in compliance.
Operational Impact
  • The implementation of Observe.AI’s Auto QA has resulted in significant operational improvements for the company. The automation of the QA process has freed up time for the company’s QA and supervisor teams to focus on measuring and improving agent performance on targeted use cases important to their business goals. The company now has visibility into performance across their entire workforce and can identify top-performing agents. The company has also gained 100% confidence in compliance, with visibility into 100% of calls and the ability to customize and calibrate the machine to become more accurate over time. Looking ahead, the company plans to automate the evaluation for even more compliance-related moments with Auto QA and is leveraging Auto QA to build a “kudos” incentive program that highlights top-performing agents and reinforces positive behaviors.
Quantitative Benefit
  • 83% increase in QA volume
  • 5x QA evaluation workflow speed
  • 30% greater speech analytics accuracy within 30 days via Calibration process

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