Three Bank Data Plays That Accelerate Real Sales Gains
By Nicole Volpe, Contributor at The Financial Brand
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Need to Know:
- Banks using behavioral signals in account opening workflows can identify and remove abandonment triggers. One institution saw immediate engagement gains after eliminating a single uncomfortable income question.
- Analyzing usage patterns helped multiple institutions identify a growing “gig worker” profile, enabling tailored offerings that blend personal and business functionality for underserved customers.
- Apple Bank’s Candescent implementation cut application processing time by 50 minutes, tripled productivity (800 more apps/month), and reduced manual review time from 80% to 30%.
Fueled by three decades of increasingly powerful and accessible technology capabilities—from the earliest CRMs to Big Data to today’s Gen AI—data analytics have found their way into every aspect of modern sales and marketing. Yet even today, many financial institutions struggle to capitalize: Their operations may be throwing off more data than ever, but they’re not able to harness it in ways that consistently move the needle on sales performance.
For institutions looking to level up, the challenge is daunting, especially with large national competitors and digital-first players looming. Opportunities to optimize performance using data exist throughout the sales process and customer workflow. But community banks and credit unions in particular know that success often hinges on finding and focusing on the areas that make a difference for their institution—its served community and its core products.
So which entry points hold out the highest potential for an institution that’s looking to wring more value from its data? To answer that question, The Financial Brand spoke with Reid Downey, Chief Revenue Officer of the digital banking platform Candescent, and Erin Keller, head of Candescent’s Terafina sales team. They identified three high-impact areas that could deliver results while also forming the basis of a go-forward strategy.
Want more insights like this? Check out Candescent’s content portal: Illuminating Insights in Digital-First Banking
Use Real-Time Journey Analytics to Remove Friction From Account Opening
One of the clearest opportunities for banks to unlock high-value insights from their data is to analyze what customers do inside digital workflows. The idea is to use real-time journey data to progressively refine critical processes, reduce abandonment, and increase conversions.
New account opening is one of the most sensitive friction points in digital banking. Small design and process decisions can dramatically influence whether a consumer completes an application or drops off.
In fact, customers will hesitate if an inquiry feels too personal or irrelevant. A bank that isn’t seeing sufficient organic growth in the digital channel should start by paying closer attention to behavioral signals already present in the data.
Keller offered the example of a bank that saw increased abandonment on its checking-account application page. The bank asked to add a new field to the application that requires the customer to provide their average income. “Users didn’t feel comfortable answering that question,” Keller said. “The bank was able to pinpoint that specifically, remove it, and they immediately saw customer engagement go up.”
While most banks measure abandonment, fewer are using real-time behavioral signals to redesign workflows. Looking ahead, the next step is to systematize and automate such improvements, predicting friction points and resolving them before the customer drops off.
Uncover New Customer Segments and Design User Journeys to Engage Them
Another powerful use of data is uncovering segments that don’t fit typical banking categories. New customer types often reveal themselves through behavior long before institutions decide to explicitly recognize or target them. By studying usage patterns and demographics—including self-provided data as well as preferences suggested by online activities—banks can identify new personas and craft products and services tailored to how they live and work.
Downey told the story of how Candescent, working with several of its bank and credit union clients, noticed an emerging “gig worker” profile. With Candescent analysts, these institutions realized that such account-holders represented a unique hybrid use case. It includes the growing ranks of freelancers, sole proprietors, and entrepreneurs whose financial needs don’t neatly fit traditional retail and commercial customer personas.
“All these banks are saying, ‘We’ve got this strange profile of a user that’s not quite a retail end user, but not quite a full business user, and we want to create a different experience for that group,'” Downey said. “We want to be able to reach them and create a different experience for that group, so that we can attract more of them.”
Through data analysis of usage patterns and customer feedback, banks saw which customers relied heavily on mobile devices, managed multiple income streams, or indicated they could benefit from business banking tools. They were able to leverage these insights to design a new service offering that includes mobile-first invoicing, project tracking, access to a credit reporting service (so these workers can vet potential new clients), and other tools that blend personal and business functionality.
“Some gig workers are probably working part-time. Maybe they have three to five jobs. They can’t afford high-end commercial services because they’re not big enough. A tailored platform helps this group track all of their self-employed activities, separately from their personal accounts,” Keller said.
Dynamic, data-driven segmentation holds particular promise for community banks and credit unions, which have long differentiated themselves through deep market knowledge. Such approaches enable these institutions to accelerate growth while still meeting the expectation that they will excel at understanding and anticipating customer or member needs.
Automate Complex Multichannel Workflows for Businesses
Data analysis can help banks and credit unions increase efficiency and client satisfaction for their business banking operations, where requirements and expectations vary significantly by industry, introducing opportunities for compliance lapses and increasing pressure on client-facing teams.
High-value business clients such as medical practices, money services businesses, farming enterprises, and even companies owned by private equity firms all have specialized onboarding and compliance needs. Most of them also like their banking affairs handled in person. Yet remembering these unique requirements can be a challenge for bank employees.
The first step is to build a standardized workflow for each served business segment, mapping client profiles with transaction patterns and regulatory requirements, Keller said. These workflows, accessible on branch consultants’ desktops, automatically present the right questions, forms, and checks. In some implementations, specific workflows might be made available only to specialized teams or locations, ensuring that only trained bankers handle higher-risk or more complex relationships while still following a consistent process every time.
Following this model, New York-based Apple Bank partnered with Candescent to implement a next-generation onboarding platform, centered on streamlining and automating its commercial account opening process, including application review, document archiving, and transmitting data to monitoring systems. These systems included the bank’s Bank Secrecy Act (BSA)/anti-money laundering (AML) compliance tool, as well as other governance, risk, and compliance systems.
Data analytics played a significant role. The banks’ analysts reviewed each sector’s business requirements, validating data feeds and ensuring regulatory compliance. The new toolset focused on the following improvement areas:
- Onboarding: Automation of tasks like the initial application review enables a significantly faster and more efficient account opening experience.
- Fraud prevention: The platform’s built-in fraud mitigation, including continuous identity verification, provides stronger security for business accounts.
- Convenience and control: The implementation complements existing digital business banking services that allow clients to manage finances on the go, transfer funds, pay bills, and set team-member access levels.
According to Apple Bank, the rollout led to a 50-minute reduction in average application processing time. Productivity tripled, enabling the bank to process around 800 more applications per month without adding staff. Team members’ time spent on manual reviews dropped from 80% to 30%, and training time fell from three months to two weeks.
“With so many special circumstances, it’s extremely easy for well-meaning teams to miss something. And when compliance issues come up after the fact, they can add delay and start the customer relationship on the wrong foot,” Keller said. “The alternative is to identify the pattern and automate.”
Your Mileage May Vary
Every institution has its own markets, history, and customer priorities. What works for one won’t automatically translate to another. The key is to balance analysis of proprietary data with data and insight from expert providers. Banks can maintain internal competency in analytics, exploring their own usage data and evaluating workflow trends, while outside partners help structure the data, benchmark performance, and extract new insights.
“It’s one thing for a financial institution to look at its own data, but partners have the advantage of knowing other customers’ information and can see trends in the context of larger baseline data sets,” Keller said.
A successful data-informed sales strategy doesn’t require sophisticated AI or massive business model transformation. It requires a clear focus on identifying the high-impact opportunities, a willingness to examine customer behavior, and the discipline to align tools and workflows around what that data reveals.
“It’s not the data: it’s the intelligence you get from the data that lets you better meet clients where they are,” Downey said.
