Digital Transformation in Financial Services

Financial services has long been one of my top areas of interest (followed by healthcare) and so I love spending time with banks and credit unions to understand their current technology challenges and help them define a robust Digital Transformation and mobile strategy.

Digital Transformation is far beyond just moving from traditional banking to a digital world, and there are hundreds of functional and technical areas for Digital Transformation in a Financial Institution. My focus in this blog is going to be on the customer satisfaction and the associated competitive advantages for a Financial Institution.

Consumerization of IT has made it a vital change as to how banks and other financial institutions learn about, interact with, and satisfy customers. An effective Digital Transformation begins with an outside-in approach by understanding a digital customer’s spending patterns, balances, incomes, preferences, likes, dislikes, stated as well as unstated needs, offline as well as online context, etc. FIs and Banks never had access to this much data (and Big Data) for a customer in decades past. Now that they do have access to it, Financial Institutions must leverage it to their full extent by utilizing digital technologies such as mobile apps, personalized user experiences, artificial intelligence to cross and up sell, machine learning and BOTs to provide a dedicated personal banker facility to every customer and provide a 24/7 personal assistant, etc. Of course, this transformation leads to major changes in the FIs and a big shift from product-centric and back-end data availability to a more customer-centric view. FIs have no other option but to opt for a customer-centric view in today’s competitive landscape where customers have tons of options for banking.

CGI recently released the results from a study called, “Understanding Financial Customers in the Digital Era,” and the report provided some fascinating information.

what consumers want from their banks chart

Looking at this particular image, it’s surprising that merely 34% of the consumers surveyed are satisfied with the current service levels for “Reward me for my business.” These numbers clearly show a huge opportunity for banks to innovate and transform their businesses.

The most effective way to for organizations to move from traditional banking to digital banking is most likely an Omni-Channel approach. As customers switch to different channels (mobile, tablets, desktop, wearables, etc.), banks and credit firms need to focus on delivering a seamless customer experience across various touch points. Today’s customers are more sophisticated and tech savvy, and each customer wants a unique experience from their bank. They want the companies to understand their unstated needs as well as their likes. So, it should come as no surprise that these customers are expecting similar kinds of responses and services from banking institutions too. Be it researching new services, opening an account, checking balances, conducting transactions, checking loans, credit, wealth management, customer support, etc., delivering an Omni-channel experience has become a key to success in this competitive marketplace. Centennials, Millennials, and even Generation X and Baby boomers don’t like going to a branch for banking and rather prefer performing all their transactions using their smart phones. But are Banks ready for this? No, not yet.

There’s a difference in the treatment a millionaire gets when he visits a branch vs. another person who hardly has a few thousand dollars in his account. And as of yet, they don’t receive a similar personalized experience when they login into their apps.

Big Data could help with personalization, as Big Data analytics can help extend a single view to the consumer. Companies can use data from social media sites to understand their customers better. In addition to this, data available from previous online searches and purchases can help target the right individual. Digital transformation, if successfully implemented, can lead to improved brand recognition and revenues, increased customer base, enhanced customer experience, and competitive differentiation.

Using Big Data, information can be obtained from customer posts on social networking platforms, websites, past purchases, and browsing history. Data can be collected by tracking email IDs that customers use to log in to and access social networking sites that are linked to the email ID they use to register on the bank’s website. Internet browsing (such as looking at various investment options) and interacting with specific sectors or companies can also be considered. Using Big Data analytics, this information is processed and used to generate recommendations for customers when they log in to the retail banking app (via mobile, tablet, web, wearables). Software, which can pull product reviews from social networking sites or reviews given by financial experts, can be used to display reviews in the review section of the website. A database management software is required to record data obtained about customer activity/interaction and processed data. This software is linked with the cloud, so that the data can be accessed from anytime, anywhere.

BOTs with machine learning and AI flavors can be an ultimate solution to provide a personal banker and a 24/7 personal assistant to all customers—no matter the size of their bank account. Users don’t call customer care to check their balances or to conduct transfers—they can do that via a mobile app. The pain customers experience comes when trying to find out specific details, like a routing number for a wire transfer, how to do a wire, what does it cost to do a same day wire, send me my 12 months old statement, etc. BOTs can do a very good job handling those things and easing customers’ pain. Beyond that, though all customers want to feel as though they have a personal banker that can help them get educated on saving money, how to earn more rewards, and to provide wealth building advice. This is where machine learning and AI flavor on top of NLP would be a perfect fit.

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