The increasing sophistication of mobile technology has helped us exchange details, authenticate and conduct transactions seamlessly. Information is literally available at our fingertips, eliminating the need for human support. The only area where human interaction has had a lead over technology is the personal touch during a conversation, especially in the case of relationship-based interactions. However, with all major innovators, including technology giants,1 putting their weight behind technology that provides human-like conversation experiences, even that edge seems to be diminishing. A platform designed to understand, learn and converse like a human and answer ad-hoc queries in real time is commonly referred to as a chatbot. Chatbots have attracted the attention of firms across industries and are being viewed as a means to create differentiation in an increasingly crowded landscape.
With the augmentation of computing power, the chatbot has managed to create a larger impact for stakeholders over time.
With chatbots gaining more traction, many firms across the globe have started offering off-the-shelf products that help developers to build, test, host and deploy these programs using Artificial Intelligence Markup Language (AIML), an open source specification for creating chatbots3. A few platforms support integration with payment providers for seamless processing of customer payments based on a customer’s interaction with the bot.
Increasingly, chatbots are also attracting interest in the world of FinTech, and a number of companies have developed their own chatbots using proprietary technology and algorithms. Chatbots utilise application programming interfaces (APIs) to integrate with data management platforms. This allows them to analyse the extracted data as well as web- and mobile-based user interfaces and deliver the necessary insights to the end customer.
The typical architecture of a chatbot platform is shown below:
Consumers of information in the financial services sector range from end customers of the bank to CXOs. Forward-looking financial institutions have taken a leap of faith by investing in chatbots to deliver ‘contextual insights’ to the right person at the right time and through the preferred channel. They have begun transitioning to ‘conversational banking’ and are viewing chatbots as new age contact centre executives, minimising TAT and costs along the way4. Chatbots are designed to answer queries such as:
Financial institutions across the globe are assessing the viability of deploying chatbots for varied objectives
Financial institutions with a digital-savvy customer base are testing out various approaches to proactively deliver insights to the customer based on her/his transactional history and digital profile:
The days of entering multiple options on an interactive voice response (IVR) system for customer service seem numbered. Firms are experimenting with chatbots that allow customers to authenticate based on voice samples from natural conversation and help complete transactions quickly.
Typically, 30% of senior management time is spent on operations and other miscellaneous tasks. Out of this 30%, 60% is taken up in getting the desired metrics from MIS/IT team/multiple departments and follow-up on the same.
Chatbots can reduce the time spent by CXOs on operations and provide readily available information quickly, thus allowing them to focus more on strategic business objectives. Queries can be as varied as:
In their current form, chatbots have reached a certain level of maturity. They are developed for specific tasks and are unable to suitably handle specialised queries requiring knowledge outside the functional domain. The time is now ripe for financial institutions to enhance the capabilities of chatbots to create a completely differentiated experience for their customers by combining knowledge across all relevant segments and providing better insights. This will give rise to a new level of conversational banking where results are delivered instantly through real-time conversations, thus facilitating better decision making.
Chatbots can add a new dimension to the power of ‘personal touch’ and massively enhance customer delight and loyalty.
Such an enhanced level of customer engagement and satisfaction will help drive customer loyalty without the need for any manual intervention.
Chatbots could be channelled to create an ‘insights-driven bank’. A typical day in the life of such a bank’s business user would involve decision making that is driven only by data-based analytics. The queries may be related to sales and marketing, impact of global trends, new product launches, and internal metrics such as employee attrition and sales targets.
A chatbot can be designed to respond to all kinds of requests and queries. Some examples are given below:
Real-time responses to such queries through predictive analytics and recommendations based on prescriptive analytics can significantly enhance the quality of decision making in the firm.
Having achieved a certain degree of maturity in chatbot deployment, financial institutions can seek newer ways to partner with technology firms and leverage innovative technologies.
These are a few potential areas of exploration:
It will become imperative to think beyond the obvious to assess use cases for chatbots in the future.
In order to fully realise the RoI from chatbot deployment, it is critical for a financial institution to define its business requirements and identify the use cases to be met through the chatbot. KPIs should be identified and measured to gauge the performance of the bot, and necessary alterations need to be made based on these in order to achieve the desired results. A data analytics driven Centre of Excellence (CoE) with a strong data operating model and with representation across business and product and technology teams can be established to adopt a centralised pan-entity approach towards the utilisation of chatbots for solving business needs and generating predictive insights.