How can AI and human agents work together in FinTech customer service?

AI-powered chatbots can handle routine customer inquiries, such as balance inquiries, transaction history, and basic account management tasks.By leveraging the strengths of both AI and human agents, FinTech companies can create a customer service ecosystem that delivers efficient, personalized, and empathetic support to their customer

Continuous Learning and Improvement: AI systems can learn from human-agent interactions, customer feedback, and historical data to continuously improve their performance and accuracy. Human agents can provide feedback and insights to AI systems, helping them refine their responses, understand customer preferences, and adapt to changing customer needs over time.

From a use case perspective, in the wealth tech domain we see that most enterprises are keen on reducing speed bumps in core processes such as Onboarding, Servicing and Lead generation. For onboarding, legacy processes and fragmented tools results in NIGOs - not in good orders and customer churn, which AI assisted workflows can help with intelligent data pull and interactive guidance. The same goes for new financial professional (Financial advisors, insurance agents, home office SME etc.) onboarding as well.

Speaking from a wealth tech perspective, we see the key value of a wealth/financial/insurance advisor is their close and trusted relationship with clients. AI can enrich this by two ways- Firstly, by automating most of the manual, repetitive tasks in relationship management(think scheduling, drafting follow ups, action items, etc.) it generates more time for the Agent/Advisor to research on the client's larger objectives. Secondly, by providing key insights into the customer helps the Agent/Advisor to make the client interviews more effective. We envision both AI and Human actors working to achieve the common goal- building customer centered high quality relationships.

Whilst AI can automate volume based heavy admin tasks through either chatbots or automated credit & fraud checks. However, due to bias in data it is important to have human intervention baked into the workflow process. So for example, AI can automate credit checks for a bank, Humans can analyse, investigate and add an element of creativity to investigate claims that the bank's data is skewed and may have a bias against a certain strata of society.

When we designed a contact experience for a client in wealth management firms, using a cloud contact center platform (such as NICE incontact, Genesys etc.) we used a tiered approach that leverages a context aware, domain specific AI assistant at the front, which escalates on specific topics to call queues that matches the skill levels of agents that are briefed by Agent facing AI Assistant before bringing in them to the live session. We see that hybrid service is the future, and the companies that get it right by starting early and iterating constantly, win big with CSAT ratings vs the others that delay or create point solutions that either fully automated or fully human are loosing out.

Knowledge management and reduced Agent training time are some of the benefits we have seen, apart from the obvious wins of speed and scale. Even experienced agents, use our solutions to ensure compliance with respect to the latest guidelines so that the customer gets the most updated and relevant information. In addition to reduced AHTs (Agent Handling Times), this gives opportunity to cross sell products that the customer might be interested in.

Adoption. It can be made organic, if the solution addresses the key pain points of Agents - getting customer context and organization policies in one place than to screen switch. Followed by adoption, the personalization of AI assistant to the Agent(experienced vs novice) and helping with their key tasks(post call notes, executing action items) etc. are important. Often we see Financial Institutions has different departments in silos that can make this a challenge to integrate different aspects of service delivery and execution into the Agent's desktop. This is where organizational leadership can help to unblock impediments in budget/tech barriers.