Conversational Analytics: Breaking the Engagement Puzzle in the BFSI Space

Raghavendra M, VP-Sales &Customer Success, Mihup

BFSI institutions operate in a highly complex and challenging landscape. Being in a ‘transaction’ oriented domain makes banks, insurance companies, and other financial institutions extremely people-centric. However, it is this people-centricity of operations that can prove to be a double-edged sword if not managed efficiently.

The first and foremost priority of any BFSI enterprise is to keep its customers happy, and retain them for long-term business association. An ever-expanding range of products and services is being created by BFSI institutions all over the world with the aim of attracting customer attention and delivering a superior experience. However, when a new service is launched or an existing one is operated without factoring in the customer opinion, it becomes difficult to make it a success.Thus, institutions like banks, insurance companies and other financial companies regularly encourage their customers to communicate with them, share their feedback and inputs.

With the rising diversity of platforms that facilitate this brand-customer engagement, there is also a rapid surge in the need for quality support to make the whole exercise meaningful. In the conventional manually operated form, businesses are finding it increasingly challenging to consistently engage and delight the customers across platforms. As per an Accenture survey, nearly 79% of bankers believe in AI’s potential as a capable and accurate co-worker, collaborator and advisor for the contact center agents of the future.

Conversational intelligence is making that happen already. Smart AI-powered conversation intelligence platforms are boosting BFSI performance in all three core areas of operations: enhancing sales and revenues; delighting the customers; and ensuring customer retention.

BFSI engagement transformation through conversational intelligence

The diversity in communication channels and the 24*7 engagement avenues ushered in by social media platforms serve as greater opportunities for enterprises and customers to interact. However, they also lead to humongous data and conversation load.

Also Read: Conversational AI Platform as Digital Fabric for Banks

The manual process of quality analysis leads to only about 5% of the conversations getting analysed by the QAs. They randomly choose conversations and score them on various pre-defined parameters. However, it doesn’t mean that the other 95% of conversations hold no value for the business. In the same way, the manual rating-based feedback systems wherein customers are asked to rate the services on a 1-5 or 1-10 scale, are often not able to assess the exact customer sentiment or opinion for a service. One might give 5 which indicates that the concern was resolved in a single conversation, but does not reveal how the customer felt.

However, real-time listening by an AI-powered speech intelligence platform that is integrated with contextual, emotional and other analytical abilities, can reveal a much greater range of insights. Taking cues from the observations, the real-time conversational assistance provided by the platform can enhance agent performance. As a live agent-assist solution, the system presents relevant, customized and precise suggestions to the agents on their screen. For instance, it could suggest what more questions should an agent ask to accurately probe the need or prompt them to share information about another product that is similar to what the customer is looking for.

The efficiency that the automated voice intelligence ushers in is truly game-changing. The instant and timely sharing of relevant information or nudges reduces research and probing time for the agents, bringing down the overall Average Handle Time (AHT), reducing supervisory call transfers, and significantly enhancing the quality of conversation. The accurate understanding of the customer need and greater rapport building enabled by the system leads to likelihood of up-selling and cross-selling as well.

Even at the backend, the conversational intelligence platform is significantly reducing work for agents and Quality Analysts alike. The integration of Robotic Process Automation leads to the elimination of need for agents to segregate, and summarise the calls as that part is taken care of by the system. The conversational intelligence platform analyses 100% of conversations and delivers far superior, actionable insights that iron out engagement challenges for the brands.

Also Read: Importance of API Economy and Open Banking

This kind of digitally-driven conversational support by AI speech intelligence is rapidly gaining momentum in the BFSI arena and will be absolutely essential for the success of customer engagements in the times ahead!

This article has been authored by Raghavendra M, VP-Sales &Customer Success, Mihup

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