Platform improves closure rate of loan collection by 25% through better prioritization
Bengaluru: Bengaluru-based Convin.ai, a leading AI-driven platform that reimagines virtual assisted selling for businesses, today announced that it has launched an AI-powered agent assist platform that helps them better prioritize their collection accounts resulting in a 25% increase in the closure rate. The new platform also has a proactive alert mechanism and sentiment analysis that triggers a red alert in case of any shouting or abuse during the call so that necessary steps can be taken to tackle such a situation. The proactive alert mechanism has helped Convin’s BFSI customers improve their CSAT scores by 30%. Three main pillars supporting the just launched platform are – 1. Automated quality management, which scores the call performance and identifies training opportunities for agents; 2. Call behaviour analysis which uncovers the behaviour outcome of calls (wins and losses) and 3. Automated quality coaching based on the above two that completely removes the dependency on archaic coaching methods. Convin offers a holistic platform that allows customers to interact at multiple channels in different ways, automates conversation analysis, assists agents to sell better, improves agent productivity, and enhances end-customer experiences.
Speaking on the platform, Ashish Santhalia, Co-founder & CEO, of Convin, said, “Over 70% of customer interaction in the BFSI space in India still happens on calls. Even a delta improvement in the quality of these have a huge impact on business output. Convin is helping the BFSI companies improve their business output on the same lines.”
As widely known, in the BFSI industry support, collection, and sales processes are mainly run by high-volume call centres. With the world resuming normality, most players in the space have already resumed their call centre operations for lead capturing and old loan collections. Convin with its solution disrupts the old and outdated call centre process and empowers the agents to self-learn from their mistakes with the help of automated call reports and coaching suggestions. And provide their end customers with the best experience possible. The platform easily integrates with agents’ calling platforms and other stacks employed by the call centre.
