Image
October 27, 2020

NLP to Save 7,000 Hours on Calls every month

Sber is to use Natural Language Processing (NLP) to improve its Centre for Corporate Solutions (CCS) and save over 7,000 hours of time spent on calls every month.

The single work space (SWS) system for operators has added a service using NLP, which transcribes the voice of callers into text in real time, analyses and classifies the query, finds the required information, and advises the operator on how to help the customer.

Sergey Lekhanov, Director of Centre for Corporate Solutions, Sberbank, said, "Businesses address CCS on a broad range of issues across more than 1,000 topics….The SWS.Assistant simplifies this task drastically by doing all the rough work for the operator, who can now focus on communicating with the client. As a result, we not only save time – for both the client and the operator – but also improve the quality of service."

The solution is supposed to save the entire bank an aggregate of over 7,000 hours a month.


Popular
Most Viewed

Image

Related Articles


June 30, 2022

SIMM Falls Short says PRA Letter to Banks




2 MIN



Risk Management


June 28, 2022

FMSB Statement of Good Practice on Trading Platform Disclosures




2 MIN



Regulation


June 20, 2022

Regulatory change and data fragmentation are key challenges for 85% of firms




2 MIN



Regulation