Artificial intelligence is now rippling through the finance industry, so it’s important for us to take stock of which players are doing the most to stay ahead of this digital transformation. That’s because this critical sector of fintech could well determine the fate of the top financial players for the next decade.
At the moment, it seems that bigger is better.
According to a recent Mercator Advisory report, large financial institutions such as Wells Fargo (NYSE:WFC), BNY Mellon (NYSE:BK), and Capital One (NYSE:COF) seem to hold a clear edge over their smaller counterparts. Large banks as a whole have been surprisingly fast and adept at integrating artificial intelligence into processes and departments such as regulatory compliance, legal, and payments fraud detection.
The same holds true in Canada, where Royal Bank (TSX:RY) and Toronto-Dominion Bank (TSX:TD) seem to lead the pack. In January, TD snapped up Layer 6 AI, a startup that uses AI to analyze data in order to learn and anticipate customer needs. Royal Bank, in particular, stands out, having delved into AI early on, incorporating the technology into its RBC Capital Markets research arm since 2016. Just last year, RBC announced a plan to spend $3.2 billion in artificial intelligence and digital products and has since internally developed an AI-powered NOMI tool that can help retail customers better manage their finances and track spending.
But arguably the most promising deployment of banking AI is through its customer-facing applications. That is, leveraging tools such as NOMI to talk to customers through cognitive messaging. Ever since 2017, when Bank of America Corp. (NYSE:BAC) and Mastercard (NYSE:MA) first launched their chatbots, the banking industry has proliferated with these ‘automated customer experiences.’
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In the past two years, banks have been deploying chatbots, to varying degrees of success. JPMorgan Chase (NYSE:JPM), for instance, uses its COIN chatbot for back-office purposes, to analyze contracts and handle basic IT requests, while Wells Fargo incorporates chatbots into Facebook Messenger.
There are several reasons to use chatbots in banking. First of all, they can deliver on cost savings, being much less expensive than their human counterparts. Juniper Research recently released a study claiming that cost savings for banks from chatbots should reach $7.3 billion by 2023 (up from $209 million in 2019). Second, they enhance operational efficiencies while boosting engagement rates with customers and prospects.
Bank of America is currently the US leader in the use of mobile banking and artificial intelligence implementation with its chatbot erica, a platform that sends personalized financial recommendations to customers from within the Bank of America mobile app, after analyzing the customer’s data using predictive analytics and cognitive learning. Although customers mainly use it to search their monthly transactions at the moment, its capabilities have only grown since launch.
Banking platforms such as erica have moved beyond being mere chatbots to developing cognitive AI functionality. While simple chatbots tend to be scripted, these platforms interact with customers in a way that’s personalized and data-driven, with a deep understanding of the underlying banking context—what the industry refers to as ‘conversational banking.’
Conversational banking platforms understand an individual’s financial situation based on an analysis of their personal banking information, and respond with suggestions on complex questions such as whether to consolidate personal loans, how best to send money to a colleague and what accounts to open—questions that would normally require a call to customer service or a trip to the bank.
While banking chatbots are now everywhere, most are still limited in functionality, scope, and geography. Financial institutions that can ultimately deploy this type of conversational banking holistically will likely ride at the crest of the next fintech wave.
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