For many banks, launching a virtual assistant[1] might be the first time they actually engage with their customers in open-ended conversations. In many ways, it’s like giving customers a blank text box or open mic and asking for their true “voice of the customer” – in real-time and across channels. Responding to all of the idiosyncratic ways people communicate puts all virtual assistants through their paces, as well as the teams that manage them – and that’s why it’s important to make sure you have a system that can rise to these challenges and exceed your customers’ expectations.
These virtual assistants and bots are designed, integrated, and deployed with conversational AI platforms. Whether a bank chooses to build their conversational AI systems internally à la Bank of America’s Erica or license a conversational AI platform with built-in deep financial expertise like Wells Fargo, TD Bank, J. P. Morgan, and DBS, it’s imperative that the executives and employees across functions are aligned about what it takes to deploy and maintain a virtual assistant. Some of the world’s largest banks are years into successful AI deployments[2] across many platforms and languages.
In fact, large banks are leading the AI revolution in financial services[3] – nearly half (48%) of banks with over $50 billion in assets have already deployed AI solutions, compared to just 7% of banks with $1-10 billion in assets.
Ensuring your bank is ready for conversational AI is a major consideration. Deploying virtual assistants[4] requires a myriad of functions at a bank to align – product lines, tech teams, customer care, compliance, and channels to name a few. Together, they
