Solving for Blind Spots in Bank M&A

Mergers and acquisitions are a major driver of change and returns in the banking industry. As banking leaders head into mission-critical strategic planning sessions for 2023, now is the perfect time for boards and executives to map out the coming year’s organizational and budgetary priorities. Recognizing that M&A can be a principal platform for growth, what are the key considerations empowering banks of all sizes to increase their influence and scale their organizations?

Reducing Risk
Mitigating institutional risk is at the top of the list of priorities as banks begin exploring M&A opportunities. Ensuring your bank has a comprehensive plan, inclusive of division of labor, is critical for successful M&A. Does your bank have the right staff with expertise and experience at the planning table, so nothing gets missed?

Tapping into the knowledge base of current customers and how the bank plans to maintain those relationships is a smart first step. But what about potential prospects the bank wants to reach – what do those people want? What’s relevant to them?

Well-designed research programs are table stakes for successful M&A. Data on markets and prospects will give decision-makers insights beyond their customer base. Even if bank leaders feel familiar with a market, updated data-based intelligence provides a true picture of opportunity and risk, so banks can form a plan suited to their particular circumstances. Smart data will also help uncover if another financial company using similar branding and overlapping media, or presents other legal and reputational exposure before the deal is done. 

Enhancing Efficiency
Data and insights will also produce efficiencies in M&A by helping executives discover whether their brands and names bring unneeded baggage. Having a brand that requires exhaustive explanation can be an opportunity cost, resulting in time not spent focusing on a prospect’s needs and the bank’s options for meeting them. Likewise, marketing’s return on investment can be negatively impacted when brand elements are limiting or nondescript.

For example, brand names with specific vocations or cities may cause a prospect to wonder if that bank is truly designed to help someone like them; they may eliminate the bank from their list of options before exploring the institution’s breadth of services. Also, if banks with similar branding or name invest in advertisements or community sponsorships, a consumer may mistakenly assign the message or public relations value to a competitor because they miss the distinction between local banks with similar names.

Competitive research will help boards and executives take a comprehensive look at their brand to identify what parts of their story prospects don’t know and what is meaningful to them. Leveraging data can help ensure messages and communications are spotlighting parts of the brand story that will have the most resonance with consumers, and have distinct and competitive value propositions in that market.

While it’s true that a financial institution may have to change its name because of a merger, research will help identify names that represent a hurdle to overcome both legally and reputationally. In our experience, brand research can become a downstream activity executives assume they’ll take care of later, but we think of it as a critical part of due diligence. Further, a powerful research program helps ensure banks can make the most of the brand launch, when people may be more open to hearing a renewed brand story that’s relatable and relevant.

Targeting Growth
M&A allows institutions to elevate their expansion efforts and future-proof their organizations. Oftentimes when executives consider marketing and brand research in light of M&A, they point to customer satisfaction data. While this is an important measure for retention and engagement, a more comprehensive data set is indispensable to help ensure organizations aren’t operating on biases and blind spots.

Smart banks leverage robust research in the M&A process to help uncover opportunities, eliminate friction and help distinguish, define and differentiate their brands. A crucial component of retention and growth pre-and-post merger is employees. Research insights can predict potential turbulence and inform strategies to equip employees to champion change and maintain performance. They can also be key factors in recruiting the best talent to fuel growth in new markets.

While bank executives may be satisfied with their current positioning and their current markets, data-driven insights will help institutions leverage their assets and increase the influence of their brand in the merger process — allowing them to grow and go further.

Identifying Customer Needs, Sans Small Talk

For such a seemingly trivial aspect of social gathering, small talk has provided significant economic value to banks over the years.

Transactions allowed bank staff to interact with customers and to learn about their lives, anticipate their needs, provide information or a listening ear, or to offer a well-timed referral to a personal banker or loan officer. Even when those conversations didn’t result in new business, they still cultivated a relationship and trust.

Consumers Stop Conversing
The pandemic hastened what was already a longtime trend: Consumers want a bank with a branch nearby, but most prefer not to visit that nearby branch unless they must.

In 2020, the cohort of customers who still preferred the branch received a new incentive to begin using their bank’s mobile app — safety. Branch sign-up lists and capacity caps only made using a branch that much more inconvenient. Although some customers have returned to visiting the branches, the pendulum shifted for many who are now acclimatized to digital banking.

Customers now also clearly prefer to do digital research on banking products, according to 600 banking customers polled by Total Expert.
They say they’re nearly twice as likely to search for a lender online versus contacting a lender directly. They are four times more likely to search online rather than ask a real estate agent for a referral for a mortgage lender. And they go to their financial institution’s website first when they have a new financial need.

Web activity, however, is not a two-way conversation. Unlike a teller who can ask follow-up questions, interpret customer responses and make referrals to a personal banker or mortgage loan officer, knowing what customers need depends on their activity: applying, initiating a chat, filling out a form or contacting a banker. Customers are increasingly “going dark” on small talk; where they do show interest, the bank must wait for them. Bank leaders should be wondering how to revive two-way, active conversations.

But where to start? Consumers can sense sales quotas in a branch. And they can’t be forced to fill out a form on a website any more than they can be forced to volunteer their financial needs. Banks must look to another way of conversing: data.

Data as Conversation Starter
Customers volunteer opportunities to serve them every day through their data. As account holders and borrowers, they provide significant information to their bank in exchange for financial services.

Understanding and using this data, though, has long seemed too intricate for local, community-focused banks. Advances in technology have changed that; using data to inform and to initiate customer engagement is far more attainable than ever before. Banks are moving back into active engagement because data allows them to intuit needs not vocalized by customers.

For example, every bank has an address for their retail depositors’ home. But when does that matter? It’s central to selling a home; when a customer’s home goes up for sale, the address is listed on a Multiple Listing Service (MLS), and it sends a signal to their bank. Customers selling a home often buy a new one, or they need to safely invest the proceeds of the sale. The MLS listing is the customer vocalizing a set of possible needs. Once a bank catches that signal, technology can allow staff to advise, interpret, engage or refer, depending on the bank’s strategy.

Even outside of mortgages, knowing a customer is selling a home can be both a revenue and relationship opportunity. The National Association of Home Builders found that customers are more than 2.5 times more likely to make large purchases within a year of buying a new home — items like appliances, furniture and home improvements — compared to consumers who did not. Would these customers appreciate savings through credit card rewards? Do they want to use their equity to buy appliances? Were they waiting until their new mortgage closed to purchase a commuter car? Even simple, widely available data points can become the basis for highly engaging and productive interactions between a bank and its customers.

Eighty-four percent of Americans report stress about their finances, according to a recent ValuePenguin survey; bank customers want help reaching their financial goals. Banks may not be able to stop the decline in small talk, but they can revive and even surpass it with new tools made for banking. There are so many more opportunities for banks to use their data to anticipate needs and to engage customers about their desired outcomes. The upside is lifelong loyalty within each customer relationship.

Recapturing the Data That Creates Valuable Customer Interactions

Before the end of 2021, regulators announced that JPMorgan Chase & Co. had agreed to pay $200 million in fines for “widespread” recordkeeping failures. For years, firm employees used their personal devices and accounts to communicate about business with their customers; the bank did not have records of these exchanges. While $200 million is a large fine by any account, does the settlement capture the true cost of being unsure about where firm data resides?

In 2006, Clive Humby coined the phrased “data is the new oil.” Since then, big tech and fintech companies have invested heavily in making it convenient for consumers to share their needs and wants through any channel, anytime — all while generating and accumulating tremendous data sets makes deep customer segmentation and target-of-one advertising possible.

Historically, banks fostered personal relationships with customers through physical conversations in branches. While these interactions were often triggered by a practical need, the accumulated knowledge bankers’ had about their customers, and their subsequent ability to capitalize on the power of small talk, allowed them to identify unmet customer needs with products and services and drive deeper relationships. Fast forward to the present day: Customer visits to branches have dropped to unprecedented levels as they embrace digital banking as their primary way of managing their finances.

But managing personal finances is different from banking. While most bank interactions revolve around checking balances, depositing checks and paying people and bills, the valuable interactions involve open-ended conversations about the desire to be able to buy a first home, planning for retirement or education, and funding large purchases like cars. These needs have not gone away — but the way consumers want to engage with their institution has completely transformed.

Consumers want to engage their banker through channels that are convenient to them, and this includes mobile messaging, SMS, Facebook messenger and WhatsApp. JPMorgan’s bankers may not have been trying to circumvent securities regulations in engaging with customers on their terms. Failing to meet your customers where they are frustrates both customers and bankers. Failing to embrace these digital channels leads to less valuable data the bank can use.

Banking platforms — like digital, payment and core banking — can capture data that provides insight into consumers’ saving and spending behavior, but fails to capture latent needs. Institutions that make it more convenient for customers to ask their personal banker something than Googling it opens up an entirely new data source. Allowing customers to ask open-ended questions augments transactional insight with unprecedented data on forward-looking needs.

In a recent case study, First National Bank of Omaha identified that 65% of customers expressed interest in exploring new products and services: 15% for credit cards, 12% for home loans, 9% for investments, and 7% for auto loans.

If “data is the new oil,” the real value lies is in the finished product, not the raw state. While data is exciting, the true value is in deriving insights. Analyzing conversational data can provide great insight. And banks can unlock even greater value when they analyze unprocessed conversational data in the context of other customer behavior, like spending patterns, propensity to use other engagement channels and socio-demographic changes.

At present, most of this data is owned and guarded by financial processors and is not readily available for banks to access and analyze. As banks extend their digital engagement model, it is imperative they own and can access their data and insights. And as banks increasingly see the benefits of allowing customers to engage with their banker in the same way they talk to their friends, key considerations should include:

  • Conversation aggregation. Is a customer’s conversation with multiple bankers aggregated to a single thread, avoiding data lost through channel switching?
  • Are conversations across channels retained within a dedicated and secure environment?
  • Can conversations transition from one relationship banker to another, avoiding the downfall of employee attrition?
  • Are suitable tools powered by artificial intelligence and other capabilities in place to ensure a real-time view of trending topics and requests?
  • Data access. Is raw conversational data readily available to the bank?

Engaging customers through digital channels presents an exciting opportunity for banks. No longer will data live within the mind of the banker: rather, insight that are derived from both individual and aggregate analysis can become a key driver for both strategic and tactical decisioning.

3 Ways Customer Data Benefits Financial Services

The financial service sector has seen sweeping changes in the past few years, due in large part to breakthroughs in technology and adaptations made in response to the pandemic, and banks are under a tremendous amount of pressure to cater to customers whose wants and expectations are dramatically different from before.

For financial firms to succeed, they must embrace digital transformation and set their strategy based on analyzing and using the mass of data at their fingertips. This data can help them in three crucial ways.

1. Gaining a deeper understanding of clients to cater to their needs

Banks, more so than other companies, have enormous datasets to wrangle. Every swipe someone makes with their debit or credit card is a piece of transactional data for financial companies — not to mention engagement with banking apps, calls to service centers and visits to branches. If banks are able to organize the data properly, they can understand their customers, predict their needs, personalize interactions and more.

No matter if you’re a boutique bank, or a large well-known brand — the key to success is customer loyalty, and that can be fostered by a positive experience. Customers expect their banks to predict their needs and tailor their interactions. With legible customer data, banks can identify and predict trends in customer behavior and create personalized approaches. Historically, banks have been more product-centric, for example focused on pushing credit cards or specific types of accounts. To build value, firms should move toward customer-centricity and concentrate on building brand value. This extra effort will result in happier customers, skyrocketing loyalty and retention, higher engagement and conversion rates and a more substantial return on investment.

2. Connecting with customers at pivotal life moments

Financial services is a lifecycle-based sector. To effectively serve customers, banks must understand what products and services will be of use to their clients at what stage in their lives. Customers don’t make big financial decisions when their banks want them to, but rather when pivotal life moments happen, such as marriage, moving out of state, or purchasing a home. By examining their data, banks can look at different indicators like customer engagements with other products or spending patterns, to anticipate important life events and prepare a product or offer for them in the right time frame.

3. Building a stronger business

If banks can form a complete view of their services based on customers’ usage and transaction data, they can discover where they fall short and how they can improve their business across multiple dimensions. There are many use cases that fall under the data and analytics category: Brands can develop new products and services, have better risk management capabilities and save money with more efficient internal operations. Using data even extends to financial investments: Brands can predict how the market may move and decide which companies or stocks to invest in.

Unlocking the potential of customer data in financial services depends on having a solid foundation of customer data. With that in place, banks can make informed decisions to drive adoption, increase revenue and boost customer satisfaction. But first, they must collect, clean, combine and analyze internal and external data from a variety of different sources. Without the right tools and guidance, this can be quite difficult, and often trips banks up; this is where a customer data platform (CDP) comes in.

A good CDP will help a bank make sense of messy data and turn it into valuable insights, allowing financial service companies to fuel their marketing efforts, cut back on costs and serve their customers better.

How to Modernize Your Payments Strategy

2020 induced widespread digital transformation in response to the coronavirus pandemic.

In payments, we saw the rise of options for contactless payments, digital wallets, P2P transfers and more. The challenge for banks was that consumers often did not have to go through their bank to use any of these solutions.

The developments in the payment space over the past year make one thing clear: Banks should keep up with the newest available consumer technology to retain and attract customers, and modernize their digital payments strategy for future success as well.

Consumer demand remains strong, and the experience companies provide matters more than ever. After leaning so heavily on digital solutions for the past year and a half, they expect everything to be easy and instant. It is now relatively easy to find payment apps that provide real-time payments, P2P, bill pay and more. Banks that don’t offer similar solutions runs the risk of losing market share to non-banks that do.

Customers are weighing their banking experience against their experience with fintech apps as well as  any other experience they have when shopping online, ordering food or taking a rideshare. Any good customer experience — no matter the industry — is one that the bank must now measure up to.

Take artificial intelligence (AI) and machine learning, for example. While not every financial institution is using AI and machine learning today, retailers like Amazon.com use AI and machine learning to predict consumer behavior, knowing what they need and when they will need it. They estimate when consumers will repurchase a product or try something new. A bank that is not doing the same is falling behind in providing the experiences that many consumers are growing accustomed to.

Where to Start?
By leveraging technologies like AI and machine learning, banks can use the tremendous wealth of customer data at their disposal to provide a more personalized experience. This is a tremendous advantage over non-bank competitors that do not have access to the same consumer information. It can seem like a challenge to effectively put customer data to use, but there are a few steps banks should take to make the change a successful one.

First, a bank must set clear goals for what it wants to achieve when updating its payment platform or adding a technology like AI and machine learning. For most, the goal will be to provide a better experience, but it is helpful to dig even deeper than that. Ask: Do we want better customer satisfaction? More engagement with the platform? More bill pay users? More account-to-account (A2A) transactions? More P2P transactions? Be as specific as possible with goals, as these form the roadmap for the remainder of the process.

Once goals are set, find the partner that can help achieve those goals. Look for a partner that shares the bank’s vision for payments and has the right skill sets and capabilities to achieve those goals. Finding the right vendor partner will ensure the bank is successful in the end.

Clear goals and a like-minded vendor ensure that the tech a bank uses can help meet its goals. Just as Amazon uses AI and machine learning to predict a consumers’ purchases or recommend a product, banks can predict customers’ payment habits or make proactive payment recommendations to manage their financial health. The use cases of AI and machine learning are versatile, and can serve many different purposes to help banks reach their unique goals.

Finally, do not lose sight of the future. It is easy for banks to get concerned with what will make them successful now, but keep looking ahead. Work with your vendor to think about where both the industry and your bank are going. Be sure to choose solutions that can grow and change with the bank and its customers for years to come, rather than focusing too heavily on the here and now.

Change can be intimidating, but following the right steps to implement a tool like AI will ensure success by creating a better customer experience. Revitalizing your bank’s digital payment strategy is a process, but done right, the stronger digital relationships you build with your customers will be worth it.

Unlocking the Value of Customers’ Data

A customer data platform is at the heart of the most cutting edge, customer-centric digital programs at leading financial institutions. This platform should clean, connect and share customer data so the business lines that need it most can create distinctive and relevant experiences. Amperity’s Jill Meuzelaar details the four key features banks should look for in a customer data platform, as well as common issues they may encounter when evaluating a current or prospective system.

  • How to Connect Customer Data
  • Incorporating Flexibility for Maximum Functionality
  • Avoiding Common Pitfalls

Rethinking the FICO Score


FICO-6-20-18.pngFor decades, pre-dating many banking careers today, the tried and true method to evaluate credit applications from individual consumers was their FICO score. More than 10 billion credit scores were purchased in 2013 alone, a clear indicator of how important they are to lenders. But is it time for the banking industry to reconsider its use of this metric?

The FICO score, produced by Fair Isaac Corp. using information from the three major credit bureaus—Equifax, TransUnion and Experian—has been considered the gold standard for evaluating consumer credit worthiness. It focuses squarely on the concentration of credit, payment history and the timeliness of those payments. FICO scores have generally proven to be a reliable indicator for banks and other lenders, but in an age operating at light speed, in which many purchases can be made in seconds, a score that can fluctuate in a matter of days might be heading toward obsolescence.

Some believe a person’s credit score should be considered only in parity with other, more current indicators of consumer behavior. A study released in April by the National Bureau of Economic Research says even whether people choose an Apple or Samsung phone “is equivalent to the difference in default rates between a median FICO score and the 80th percentile of the FICO score.”

Consider the following example. A consumer pays off an auto loan, resulting in a reduction in their FICO score. This is largely due to the reduced amount of credit extended. That reduced score could become a deciding factor if the customer has applied for, but not yet closed, a mortgage 60 or so days before paying off the vehicle and could affect the interest rate of the applicant.

That leaves a bitter taste for anyone with average or above average credit who has demonstrated financial responsibility and, it could be reasonably argued, would be a much better candidate for credit extension than someone with the same score who doesn’t give two flips about the regular ebbs and flows in their credit.

For all its inherent benefits to the industry, the traditional credit score isn’t perfect. Banks could be using their own troves of customer data to evaluate their credit applications more accurately, more fairly or more often. This could be a boon for institutions hoping to grow their deposit base or enhance their loan portfolios. Some regulators have indicated their attention to this approach as well. The Federal Deposit Insurance Corp.’s Winter 2017 Supervisory Insights suggests data could be a helpful indicator of risk and encouraged member institutions to be more “forward-thinking” in their credit risk management.

“As new risks emerge, an effective credit [management information system] program is sufficiently flexible to expand or develop new reporting to assess the effect those risks may have on the institution’s operations,” the agency said.

That suggests the FICO score banks are currently using might not tell the full story about how responsible credit applicants might be.

“My personal opinion is that among most people, if you have someone who thinks about [their digital footprint and credit], you’re already talking about people who are financially quite sophisticated,” Tobias Berg, the lead author of the NBER study and an associate professor at Frankfurt School of Finance & Management, told Wired Magazine recently. The study examined a number of data points that go far beyond what is incorporated in a FICO score.

That certainly has value for banks. The data they already collect about their customers could be used to determine credit worthiness, but there’s a counter argument to be made. Digital footprints are much easier to manipulate more quickly over time by changing usernames, search history, devices and the like. Using an Android over a more expensive iPhone could be a negative in the study’s findings, for example, which might not reflect the customer’s true credit profile.

But FICO scores are not reviewed as regularly as they could be, and a swing of a couple dozen points from one moment to another can significantly sway some credit applications.

For now, fully abandoning the FICO score isn’t a likely or manageable option for banks, nor one that’s favored by regulators, but the inclusion of digital data in credit applications is something that could be adapted and be beneficial to both the bank and customers eager to expand that relationship with their institution.