It’s that time of the year again! Jane’s calendar is marked for April 15th. Her morning coffee today does not seem refreshing as her thoughts float towards the dreadful tax season approaching.
She logs into her app and uses the bank bot to transfer money to her daughter as she typically does at the beginning of every month. She then listlessly browses through her bank’s website to search for tax-saving retirement plans. With the overload of information, she sighs into her empty cup of coffee.
Coming to her rescue, the AI bank bot on the website comes to life and says,
“Good morning Jane, how could I be of assistance today?”
Her earlier conversations with the AI bot have been pleasantly smooth so she decides to ask,
“How can I cut my tax bill?”
This is an example of how an AI bank bot can be proactive conversation starters with the aim of urging the customer to interact, providing assistance and identifying opportunities to increase revenue.
When processing this type of question, the bank bot first assesses the information available from the knowledge base it has access to.
In Jane’s case, based on the knowledge base provided and programmed by the bank, her bank transactions and through earlier interactions with the bot, the AI bank bot uses certain facts to possibly make inferences and responds:
“You could choose from the following tax-saving plans:”
• 401(k) savings plan
• New York 529 Direct Plan
• Flexible spending account (FSA)
• IRFC bonds
Using machine learning (ML) and deep learning the AI bot makes strategic recommendations so that Jane can make an informed decision. Jane’s interest is piqued and she asks, “How much would I save if I choose a 401k plan?”
AI bank bot: “How much would you like to invest?”
Jane: “$ 5,000”
AI bank bot: “Let me work my magic. Based on your preference, If you contribute $5,000 in a 401(k) savings plan and your tax rate is 30%, you’ll save $1,500 in taxes just like that!
Shall I arrange for a callback on your registered number?
Yes / No”
Jane: “Yes connect me”
AI bank bot: “Great, connecting you to our customer service agent right now…”
The AI bank bot immediately connects Jane with a customer service agent. The agent who receives the call has the complete history of Jane’s conversation with the chatbot and continues the conversation.
This transition from text to voice communication is smooth without expecting Jane to repeat her request. The customer service agent takes off where the AI bank bot left, making the experience for Jane seamless.
How an AI Bank Bot Can Cross-Sell Successfully
In this 3 part Conversational AI Solution Series, the 1st part of the series covered Smart Discovery, Smart Recommendations, and Smart Conversion solutions useful to upsell banking products and services.
Take a peek In this 2nd part of the series, we will cover Smart Conversion solutions useful in cross-selling of banking products and services.
AI in banking uses machine learning to find patterns in customer behavior, memorizes their preferences, and analyzes their interactions to follow through with opportunities in real-time.
A bank bot built on a robust AI platform is a natural multi-tasker. It not only ensures 24/7 assistance and accessibility to information instantly, it intelligently guides customers to consider relevant offers which are suitable to their needs.
To deploy an AI bank bot that cross-sells, upsells and assists in customer support successfully, banks must focus on three core aspects, platform, people and potential.
Make Your AI Bank Bot a Super Salesman
Around every corner of a minute, your customers are faced with offers. How many seconds or minutes does it take for customer service agents to identify and respond to an opportunity to cross-sell and upsell? Is real-time marketing a reality? Now it is, with AI in banking.
By combining NLP, NLU, ML, deep learning with predictive analytics, an AI bank bot can be designed to predict your customers’ behavior and preferences. Like humans, the personality of your bot will be as bright as the knowledge you provide and the training you give through programming. It could sell ice to Eskimos if you program it to do so.
The way your AI platform is built, the people you employ to deploy AI bots and the technology you use to support implementation will determine the extent to which you can align AI bots to your customers’ ethos.
On the digital banking highway, AI bank bots are driving the future of banking. It is no longer a ‘wait and watch’ game. With AI adoption, the pace at which possibilities can be materialized demands that you ride along and join the race. Or you could wait at the pit stop until your ride arrives. Although, it may be too late!
‘Democratize Assisted Banking’.
Let smart AI agents drive your goals. Get to know how.
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