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BANKING

Employees Speed Finance Claims With Azure Virtual Agent


The Challenge

A large banking enterprise was looking for an intelligent solution to reduce the high call and request volume routed to its finance department by internal employees. The company wanted an intelligent virtual assistant capable of responding to queries related to financial claims status, payments and approval workflow. 

Leaving repetitive tasks to the chatbot would free up the finance department to focus on areas where people add the most value, such as conflict resolution, problem solving, defining policies and strategic decision making.


Our Approach

They chose Cognizant because of our strong Microsoft AI competency for consulting, implementation and employee adaptation. We introduced an employee virtual assistant (EVA) for finance inquiries. Employees engage with the EVA using both voice and text to resolve common financial claims questions. 

The intelligent assistant leverages the enterprise’s single sign-on capabilities to authenticate users and retrieve relevant details from the related SAP module using prebuilt data connectors. EVA identifies the queries it cannot answer and escalates them. It then collects all pending issues, uploads them to the finance document repository and assigns them to a particular user for follow-up and closure. 

This Microsoft Azure AI solution uses custom speech and cognitive linguistic models to respond appropriately to user inquiries. Conversation transcripts and user feedback are stored and regularly analyzed to recalibrate cognitive models to continuously improve the accuracy and performance of the EVA over time.

Virtual Agent Reduces Calls and Queries

Because it’s available 24x7 and scales to handle increasing workloads on demand, the intelligent assistant boosts accessibility, efficiency and employee satisfaction for our client's business. At the same time, the conversational assistant has cut the demand on its finance department by 50%.

35% drop

in emails and calls to the finance department in the first month of operation

50% reduction

in emails and calls after two months of operation

43% decrease

in ticket resolution time


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