Community
If the past three years have shown us anything, it’s that consumers have adapted to self-serve. More self-reliant than ever before, they’ve learned to meet their own needs with CX tools and services that businesses have provided to eliminate in-person interactions and accommodate social distance, both required and desired.
These changes in customer service did not come and go; there was a permanent shift that forever changed consumer expectations. According to Forrester, “The pandemic created a trend — an increased reliance on online shopping, digital financial services, and telehealth (virtual care) options — and that genie ain’t going back in the bottle.”
At the same time that a new taste for digital convenience developed during the pandemic, a desire for humanness percolated. In fact, in 2020 MIT reported that people crave social interactions in the same way that they crave food when hungry. So, how can banks and credit unions marry the two? Artificial intelligence, or AI.
Consumers now expect speed, accuracy, flexibility, and seamlessness from their financial institutions, as delivered by the Silicon Valley giants who’ve cornered a place in their lives. But AI can’t achieve this elevated customer experience on its own. Three additional pillars must be combined with AI technology to support instant, human-like understanding and communication in financial services:
In Part One of this Three-Part Series, I’ll first address collection and understanding of quality data, which is essential for financial institutions to have lift-off with their AI investments.
Quality and Access
An essential capability of AI, quality data about specific users and use cases must be accessible in a real-time, secure fashion. Data makes the magic happen with AI, and without it, AI falls flat.
Banks and credit unions have struggled to enhance the quality of data and create seamless, secure access to it for many years. Not only is handling potentially sensitive data due to the nature of the financial services business a hurdle, but financial institutions don’t often have a deep bench of technology experts able to oversee such an undertaking.
Whether internally or with the help of fintech partners, institutions must overcome these challenges if they’re going to deliver AI-based experiences that move the CX needle. Arduous answer-seeking caused by siloed data, multiple data connection hops and antiquated back-ends that haven’t been modernized to today’s standards cause disjointed service. AI won’t solve your problems if access to quality data isn’t part of the solution.
Collection and Understanding
Big data, or the collection of very large data sets that can be analyzed computationally to reveal patterns, trends and associations, enables the personalized customer experience that only AI can achieve. According to J.D. Power's 2022 U.S. Retail Banking Satisfaction Study, only 44% of banks are delivering the personalized support that 78% of respondents say would compel them to continue using their bank. I guess I’m not the only one who wishes I had an AI virtual assistant looking out for me.
With consumer banking, all customer interaction information – from words used to interact with the bot to actions taken by the user – should be stored by or for the institution, so that it can be analyzed and utilized in future interactions. This includes behavioral, transaction and preference data. As users communicate with the bot, again and again, the bot is increasingly better equipped to respond to user requests. This learning loop means that the technology gets smarter over time, as the collection of data grows.
The right data points are the ingredients for a successful AI-powered interaction. But with customer experience in banking, AI doesn’t start and end with quality data. In my next two articles of this series, I’ll cover complementary customer experience solutions and the need for strong security measures.
Four in five senior banking executives agree that effective use of artificial intelligence will distinguish winners from losers in the industry. But look before you leap: Some AI solutions don’t include everything they need to succeed in the context of consumer banking. Done right, however, AI technology can launch your financial institution to the highest level of consumer satisfaction.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
David Smith Information Analyst at ManpowerGroup
20 November
Konstantin Rabin Head of Marketing at Kontomatik
19 November
Ruoyu Xie Marketing Manager at Grand Compliance
Seth Perlman Global Head of Product at i2c Inc.
18 November
Welcome to Finextra. We use cookies to help us to deliver our services. You may change your preferences at our Cookie Centre.
Please read our Privacy Policy.