So much was made of artificial intelligence in 2017—yet so much puzzlement generated—that you could compare the resulting scenario to asking Siri for an analysis and getting one of two responses: “Here are some AI articles I found on the internet” or “I don’t quite understand what you said, Debbie.”
But we don’t need Siri or Amazon’s Alexa or Google Home to tell us this: As machine learning continues to accelerate at a breathtaking clip, so too will human learning about how AI works—and how we can work it in turn. To set the stage for 2018, we can travel back to 1965, when Intel co-founder Gordon Moore developed “Moore’s Law.” After careful observation of integrated circuits, Moore presaged the modern digital revolution when he predicted that computing would dramatically increase in power, and decrease in relative cost, at an exponential pace.
As we play off Moore’s Law in financial services today, a related question arises: How can we expect banking AI to multiply in speed and complexity while it drops in price? This sets the stage for BAI declaring artificial intelligence as the Trend of the Year for 2018.
For starters, this is what we know: The attention paid to AI over the last 18-24 months would certainly have us believe that we’ve reached a historic tipping point for adoption. PwC’s Financial Service Institute describes the landscape thus: “With advances in big data, open-source software, cloud computing and processing speeds, more firms will use cognitive computing and machine learning to perform advanced analysis of patterns or trends.”
And here is what we predict: 2018 promises to be a breakthrough year for AI. Larger banks will drive much of the forward movement given their financial advantages. But we could also see regional and smaller banks bring AI to the table in partnership with solutions providers and consultants who provide expertise.
Big bank or small, there of course exists the temptation to regard AI as the “bright, shiny new tech toy of banking.” To be certain, the industry has faced this in the past including in mobile banking, which had a similar growth curve. The difference might be that mobile banking was closely linked to the fast adoption of the smartphone—and the changing ways consumers relied on this device.
AI is different. It’s not a gadget but a pathway to redefine delivery and optimize banking technology. While that may not be as tangible or sizzle as much as the latest consumer gadget, AI holds just as much rich potential. It fuels creative thinking and action to drive cost efficiency with more intellectual horsepower. And it touches just about every area of the industry, from risk management, to the loan decision process, to talent management, to the creation of positive, powerful customer experiences.
That last category in particular excites me. Think about connecting customers with your financial institution in much more meaningful ways. We will begin to see various voice-activated devices respond to more than just questions and demands: They will interact conversationally. What a proposition: giving customers the chance to embrace a technology that helps better understand all that is available, enabling them make smart financial decisions.
That said, pitfalls exist, especially for those who rush to market. AI for consumers must be carefully executed or it could have a backlash effect, writes Daniel Hong, Vice President, Research Director for Forrester: “Customer satisfaction levels will drop as companies drive more traffic to chatbots, self-service and chat that are not fully optimized to engage customers effectively.”
In fact, 24.4 percent of banks in the report stated, “We have no plans to consider an AI solution in the next 18 months.” None. Another 38.1 percent said, “We have it on our roadmap to consider AI within the next 18 months”—though “consider” and “implement,” it should be noted, are two different things entirely.
In all fairness, talent remains a key part of unlocking AI’s power and there is some scarcity of expertise; banks compete with businesses across all sectors for AI-savvy hires. Yet from scarcity can arise opportunity for banks to collaborate on how AI is used and applied.
In 2018, we might also ask: Is there a way to form a syndicate or coalition where banks can understand how to set strategies for approaching AI? Here’s hoping. Insofar as artificial intelligence and banking, we may find no better time to apply the exponential wisdom of Moore’s Law to more cooperation.
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