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How to increase the effectiveness of a call-center by 5 times?

In December 2019, we completed a test pilot project with MBA Consulting in Indonesia. The task was to unload the client's call-center and test how debtors would react to the robot and communicate with it.

In a few months of Smart Voice Operator work, we have received excellent results: debtors are willing to communicate with the robot, and moreover, more than 98% of negotiations were held in full confidence on the part of debtors that they were communicating with a human person. In this way, we have reduced costs while increasing the amount of calls.

Results

The call-center's efficiency increased by 5 times, the response latency was reduced to less than 1 second, and the cost reduction was about 60%. The robot works 24/7 – it is always in touch, and is ready to work when the number of calls increases, it is already trained to communicate correctly with customers and strictly complience with the law, which improves the quality of the company's services, eliminates any risks of violations in the conversation with customers.


Smart Voice Operator

Smart Voice Operator is a voice robot that works on the basis of a neural network. The robot was developed and improved based on the logic of debt collection process and working with financial products, derived from years of experience in the field of financial services and debt recovery. We launched our first pilot projects in Europe and Russia, where the market was more ready to implement this technology. Working with the first clients, the results were pleasantly surprised us: the mimicry of human speech was so well that the robot's recognition was approximately 1%. In 5% of cases, the robot could not answer customers ' questions and calls were transferred to human operators.


In the middle of last year, we entered the Asian market. The first pilot project was launched with MBA Consulting Indonesia. In December 2019, the agreement was signed. After completing the first test project and based on the obtaining results, we realized that the Asian market is ready for a wider application of technologies based on neural networks, and companies are interested in how to improve the quality of their services and to optimize costs. In Indonesia, we have already started working with some Telecom and FINTECH companies. Our next step is entering the Philippines market: we are negotiating with MBA Consulting Philippines and are preparing to launch a pilot project.