July 19, 2023
Tech Talk: Unlock the future of banking personalization to win and retain customers
Financial institutions can win and retain more customers by building the hyper-personalized experiences customers want and expect. The key is turning existing messy transaction data into actionable insights, driving engagement and improving customers’ financial health. Vicky Margolin, Product Marketing at Plaid, recently sat down with Neeraj Jindal, VP of Banking & Head of Fintech Practice at Infosys and Revanth Reddy Bairi, Head of Digital, Data & Analytics at Credit Union of Texas (CUTX) to discuss the evolution and use cases of personalization in banking.
Driving the conversation:
Changing customer expectations and their impact on the future of banking
How to harness your transaction data to unlock actionable customer insights
What financial institutions need to do to deliver real-time personalized insights and offers to customers
Key takeaways:
Banking and credit union customers expect a personalized banking experience. [4:20] They don’t just want product offers, they want personalized insights that support their financial health. That’s especially true for younger, more digitally native consumers like millennials who are more likely to quit banking relationships that aren’t working for them. These expectations are often set by their personalized experiences with media companies (like Netflix and Spotify), retailers (like Amazon), and technology companies (like Apple). These consumers are more likely to stay at their primary bank if they’re offered more relevant insights, offers, and rewards.
As Head of the Fintech Practice at Infosys, Jindal helps senior leaders at large banks with their digital transformation. Jindal sees four buckets of personalization use cases with his clients.
“One is financial advice, especially as responsible finance has become more and more important. The second is bringing real-time event-based offers to the client,” explained Jindal. “The third is around a customized experience based on a consumer’s financial status and lifecycle stage…Finally, we’re seeing more customized third-party offers.”
We’ve entered the era of ‘hyper personalization’ which means providing services and advice that anticipate customer’s needs. [12:30] This requires providing customers with the best message, at the right time (often real-time), and on the right channel (digital, branch, or something in between). As we fully embrace this new age of personalization, this shift in behavior will naturally create winners and losers. Hyper personalization is the best way to support your customer’s financial well-being and goals. BCG studies have shown that personalization in banking can lower rates of user churn and increase sales, leading to annual revenue uplifts of 10%.
“Personalization in banking is not just about selling anymore. It’s about providing valuable information and advice that’s embedded into the customer’s daily life and building that relationship and trust,” noted Margolin.
Clean transaction data is foundational for tailored insights because it sheds light on a customer’s spending habits, needs, and interests. [16:10 ] Clean transaction data is fundamental to creating meaningful, personalized experiences, and offers. Financial institutions already have an abundance of transaction data for their customers, but they’re not fully utilizing this information. Fewer than 1 in 5 financial institutions feel they are prepared to deliver personalized experiences at scale.
“Our customers crave insights that match their personal goals. That’s why we’re diving into our transaction data. We want to help a small business owner spot expense trends which can cut costs and boost profits,” said Bairi.
Raw transaction data is messy, incomplete, and challenging to understand and use. [16:35] Transaction data isn’t easy to categorize for several reasons. Data formats can vary, merchant names are often incomplete or unclear, and merchant details are missing. Advanced modeling and tools are often needed for data categorization and to inform analytics. Infosys has also seen banking clients have a difficult time using transaction data due to four key internal limitations: their technology systems aren’t compatible, they already have significant tech debt, their siloed data is difficult to access, or they need the right partner to get started.
Plaid Enrich helps banks and credit unions transform internal transaction data into clear, actionable insights. [18:25] Enrich is a secure, API based solution that cleanses, categorizes, and enriches companies’ internal transaction data (from their banking or card products for example). To create Enrich, Plaid applied the same technology that today processes 500 million external transactions a day for top fintechs and banks. It’s designed to be easy to implement so that current partners can be up and running in days and start to leverage the insights almost immediately.
“With personalization, customers should come away from every interaction thinking ‘Wow! My bank really knows me. They reward me and our relationship with unique offers and opportunities that make me feel valued and understood,’ ” said Margolin “It’s personalization for a segment of one.”
Clean transaction data can be used to engage users with services like subscription management tools and personalized spending insights. [23.20] CUTX uses transaction data as a clue to understanding its member’s lives, hobbies, and needs and then offering useful, timely advice and offers. With help from Plaid, CUTX is building “Subscription Insights” to assist customers in spotting subscriptions they no longer need - like an unused gym membership or a seldom used music subscription. Subscription management tools support users’ financial health, giving them real value, and helping them to save money. CUTX initially explored building a transaction cleansing and enrichment system in-house, but ultimately chose to partner with Plaid to reduce effort and resources, tapping into Plaid’s expertise to get to market faster.
“Building a full fledged data processing system from scratch would demand significant time, resources, and expertise. That’s when we decided to look externally and chose Enrich,” explained Bairi. “It took only a couple of days to get operational once we received API access.”
The ultimate vision for hyper-personalization is seamlessly embedding into users' daily lives for moments big and small. [32:00] What if a customer starts your online mortgage application but doesn’t finish? Using transaction data, you can see that your customer has relationships with two other mortgage providers. This prompts a lending advisor to quickly follow up by phone, offer a competitive rate, and let the customer easily finish the process online. It's a win/win. The customer experiences a seamless process and feels rewarded for their relationship with a competitive rate. Your institution avoids losing a loan to a competitor. By using transaction data, you’re able to deliver just-in-time personalization that’s cross-product and cross-channel.
“I think 10% revenue uplift for banks from personalization is an underestimate. It will be significantly higher. My dream is to provide value back to the customer that also brings revenue uplift to banks. We should be able to identify individual needs and customize our offerings based on that,” said Jindal.
Transaction data can bolster internal analytics, reduce disputes, and drive better decisioning. [35:20] Transaction data has a multitude of use cases outside of customer-facing benefits. Use it to understand spending trends and improve cross-sell targeting. With improved transaction recognition, reduce time and money spent handling customer disputes. You can also integrate transaction data into the authorization flow - setting rules and monitoring spend based on defined categories.
Building a personalization strategy with phased stages will gradually deliver improvements. [42:20] First, set your vision and decide what your customer experience should look like once you implement your strategy. Next, evaluate your current personalization capabilities and identify gaps and areas of strength and differentiation. Champion your vision across the organization so everyone is onboard. Invest in the right foundation to fully leverage transaction data. Consider partnering to speed up your roadmap and bring in the right expertise. Finally, test, learn, and adjust by trying different offers and using different technologies.
“Typically, a bank will have billions of data points on their customer (transactions, purchase history, IP addresses) which they can use to personalize offers. Just put it to use,” said Jindal. “This is a place where you won’t reach from A to Z immediately. Let’s not go for perfection. Start the journey and learn from that.”