This article was authored by Uday Akkaraju, CEO at BOND.AI
Reaching out to financial advisors can be a stressful for a customer already in need, and, for many, discussing money-related problems is daunting. Unfortunately, it gets worse when digitized communication processes break down. Moving from an automated chat bot to a representative without not, can unintentionally upset the consumer.
The US State of Multichannel Customer Service, found two-thirds of customers are frustrated with companies before they speak with agents. Often thanks to upsetting chatbots that ask customers to repeat information, with the solution remaining: Talk to an agent. And 91% are not willing to do business again after such a negative experience.
But the global chatbot market is growing for a reason. In 2019, valued at $494.68 million for banking, financial services, and insurance (BFSI) alone, the sector is predicted to reach $3.39 billion by 2027. So who’s succeeding in this market space?
Non-financial service brands are stepping up. The growing language capabilities of chatbots today enable companies to describe complex definitions such as application programming interfaces that a 5-year-old would understand. Whether it’s to differentiate a mobile network provider or to monopolize credible brands, digital-first companies are giving banks fierce competition.
Banks have tight regulations and risks to mitigate, but they also have the information to ensure they offer the best financial products. With the support of artificial intelligence (AI) and chatbot data, banks can lower risks and provide bespoke services—they just need to better understand how to apply these tools correctly and effectively for their audience.
Challenges banks face
At a global scale, consumers rate banking customer service at 3.84 out of 5. Interestingly, the highest scoring was in Indonesia, where services are predominantly online as brick-and-mortar banks are hard to find.
Yet, nearly half of institutions globally still need to offer a savings-account-opening journey in their mobile app, while less than a third have introduced investment sales. Understanding financial products and requirements can be confusing. Customers need a trusted channel to communicate with banks, ask questions and receive answers 24/7.
Top-performing banks see over thirty bank app log ins per month compared to the average universal bank that receives 18-22 log ins. Banks perform well when their customer’s needs are met, but as the banked society grows, technology bridges the gap to provide communication channels for each individual customer.
Bank’s chatbots have the power—and data—to communicate product information, regulations, parameters, and customer information, with the right workflows in place. Things like maintaining a minimum on credit scores and paying off unsecured loans might not be obvious to a customer, but they are to a bank.
At the same time, delaying processes cost banks several agents’ time and offers to expire, leaving customers unsatisfied with the service and without their desired products. Brands should prioritize resolving problems on the first contact, and artificial intelligence (AI) has the power to make this possible.
Banks must define the context
Some 43% of customers feel more comfortable sharing data with a chatbot, jumping to 60% for zoomers and millennials. But banks aren’t using this technology to build a contextual picture of their customers. They are missing out on improving their services and revenue growth as a result.
AI and chatbots today take everyone through a standard channel. There is no personalization of services from what is shared in a single chatbot interaction. However, when banks integrate multiple conversational data, they can generate unique AI profiles of customers behind the scenes.
Banks have multitudes of data, from income statements, outgoings, and end-of-month balances, to call history, chatbot conversations, and customer queries. With data cleansing analytics and product knowledge, banks can train AI to assess customers’ financial capabilities.
AI-generated customer behavioral profiles deliver a holistic view of customers while protecting their privacy. This helps banks to pre-determine what products customers are eligible for, what steps they can take to ensure qualification, and integrated chatbots can guide them on their journey.
Say the customer’s debt-to-income ratio is too high for a product. The individual will want to know what steps they should take to qualify. Rather than chatbots rejecting the potential loan customer, banks need to be asking: Why is it high? Can the customer pay it off by X point? These questions collect vital data required to understand the problem.
Banks must create simple workflows for high and low-income customers to gather the context, predict their customer’s needs, and cater their products and advice accordingly.
It’s OK to get personal at home
Credit is growing faster than deposits, and banks are struggling. They need to find ways to quantify loan risks more precisely and deliver in-house products.
To do so, banks must close the gap between in-house data and communication with the customer. Let’s go back to the mortgage customer. They share an ID or bank reference number, so the chatbot’s AI can follow the workflow.
With pre-mapped AI profiles, banks already know their customers’ financial capabilities and next steps, enabling the chatbot to ask simple questions and produce optimal scenarios. Options such as loans they could take today and loans they could afford if they do XYZ.
At the same time, banks can use AI to create workflows that assess their in-house products, where risk allowances lie, and ask questions that, with suitable responses, enable them to offer customers these solutions too.
When banks use AI to analyze their customer’s behaviors, they can identify their potential. This way, banks can prepare chatbots with simple next-step workflows, enhance the user experience, and build better products to support the economy’s financial health.
This article was authored by Uday Akkaraju, CEO at BOND.AI
This article includes a client of an Espacio portfolio company
