Case Study | Mortgage Services

Discover how a mortgage provider transformed customer engagement by answering questions, solving problems, and delivering services through Sutherland Conversational AI.

Services Conversational AI
Industry Mortgage Services
MAY 31, 2021

Improving the Customer Experience

Servbank is a mortgage servicer that was committed to “grow happiness” for its customers and help them "own a piece of the American pie" by offering a one-stop solution for all their homeownership needs. This meant that a large part of their customer experience revolved around the speed and efficiency of their customer care team.

The team’s biggest challenge was servicing large spikes in account-related calls that coincided with payment due dates at the start of each month. Despite the simple, easily solvable nature of the calls and the availability of an online payment option, the overwhelming volume resulted in many customers’ issues going unresolved.

Customer reviews also revealed problems with payment processing and frequently lost paperwork. In addition, they showed that customers expected faster email responses, believed that Servbank was not working around customers' schedules for inspections, and were unsatisfied with outcomes involving recurring payment cancellations.

Delivering Results with Greater Efficiency

Working with Servbank, Sutherland identified customer and business pain points and scanned agent-customer interaction in real time, across all channels to predict which customer interactions were likely to lead to negative outcomes. They then developed and implemented a tailor-made, customer-facing “chatbot” application powered by conversational Al and machine learning (ML).

The chatbot offered customers a self-service option for finding answers to the company’s high volume of simple, frequently asked questions via messaging while freeing up the customer service team to address more nuanced, complex problems and tasks, including those discovered in their customer reviews, all without adding more full-time employees.

The Sutherland solution also provided Servbank agents with a great training opportunity by providing them with insights gained from other agent-customer interactions as well as tips to help direct a customer down the best path for solving their problem.

Since launching chatbot, Servbank has handled about 3.5X the volume of inquiries with positive customer feedback from customers who said they were able to get help and information more quickly through the chatbot than traditional service channels like phone calls.

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