As the nation gradually moves towards achieving an ambitious target of 100 percent bank accounts for its citizens – the challenges are also quite enormous

India’s recent financial upheaval, in the form of demonetisation, left no household untouched. And why would it not? After all, banning of high denomination banknotes had instantly phased out 86 per cent of the cash circulating within the economy. The truest inferences of the economic move are yet to be drawn, but one conclusion is evident already. It has explained the importance of banking services to all of the socioeconomic classes in India. As the nation gradually moves towards achieving an ambitious target of 100 percent bank accounts for its citizens – the challenges are also quite enormous.

The increasing consumer base along with snowballing economic transactions have further stressed the B2C financial services in India. For instance, a loan request of INR 10,000 (US$156) by a farmer requires equal amount of paperwork, verification, and even greater level of bankside assistance than an INR 50 lakh (US$77,600) loan by a rich businessman.

The relative fixed cost of transaction is hence considerably higher for the small ticket loan instrument than its big ticket counterpart. In other words, the cost to execute one INR 50 lakh transaction would be much cheaper and considerably less time-consuming than executing 500 INR 10,000 transactions. Since, latest additions largely avail similar small ticket services as well as low ROI products, financial institutions are facing the challenge to minimise their overhead expenses while improving their time-efficiency.

Heading towards an AI-driven digital era

Conventional operations are receiving a digital makeover to counter the prevailing challenges in India. And AI is fast-becoming an integral part of the digital banking model which is also rapidly evolving with time.

From our own practical experiences, we know that digital functions are very different from the conventional banking operations that we previously were acquainted with. While macro environments have been transformed into an era of smartphone-based and even feature phone-based services, the facilities offered today are a lot more comprehensive than the time-consuming branch offices that prevailed for decades.

As 15-20 per cent of the population of the country is still unbanked, the only way that financial services can build scale is by the application of this AI technology. Process optimisation leading to improved efficiencies while eliminating operational bottlenecks is also only possible through the adoption of this technological marvel.

Also read: Has demonetisation in India met its purpose, or is it just another failure?

A big opportunity for B2C financial services

AI technology grants B2C financial services an opportunity to automate various customer-centric processes including customer acquisition, customer on-boarding, and client servicing. Chatbots or virtual assistants – one of the mainstream deployments of AI technology – can be extensively used as they are emerging as the frontrunners in the present commercial landscape. This can, moreover, take customer servicing to an unprecedented level in terms of service quality, time-efficiency, as well as cost optimisation.

Chatbots, however, are driven by customer conversations and engagements. Like in everyday life, there is no better way to understand a human being than by getting into an engaging discussion with him or her. Similarly, users engage in detailed conversations with automated chatbots, thus enabling the former to gauge customer intent in a profound way. But the depth at which intent can be understood largely depends on the AI capabilities of the chatbot.

A majority of chatbots are NLP-only (Natural Language Processing) tools, which are based on limited predefined use cases. This extends quite an erratic service experience to the user since they give the same set of answers for different customer queries. Conversely, the AI-driven chatbots leverage Machine Learning technology along with NLP and build fresh use cases through constant engagement with different users. This enables them to have an engaging discussion with the customer without giving them a hint of being engaged in a conversation with a technological product. Such chatbots act as a new generation of customer agents featuring consistent quality of service and almost no incremental cost for scaling operations.

Also read: Is India shifting toward a cashless economy after cash demonetisation?

Solving cost and scale

The chatbots equipped with AI capabilities make banking literally mobile and conversational as all banking functions are readily available through such interfaces. This is making financial institutions develop a renewed interest in these digital channels as they resolve multiple challenges faced by them. Adoption of such intuitive and state-of-the-art interfaces will evidently be a natural progression from now on. This will also solve the cost and scaling-related problems encountered while serving the bulging bottom of the customer pyramid in the current financial landscape.

Moving forward, support of voice conversations and multiple regional languages through such programs will lead to the adoption of next generation conversational interfaces. Even in the present-generation of chatbots, basic functions such as customer on-boarding, account and transactional details, analysis and subsequent recommendations, transactional statements, alongside other functions are already provided with. Once regional language support and more importantly voice format support make their entry, adoption of these services is going to gather an unparalleled pace across the B2C financial services industry.

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