What 2022 Holds for Community Banks

All banks need to prepare now for inevitably more change. As the year draws to a close, a quick look back provides some insightful clues about the road ahead. There are some trends that are well worth watching.

Changing Customer Habits
The coronavirus pandemic accelerated digitalization efforts and adoption. A recent PACE survey reveals that 46% of respondents changed how they interact with their bank in the last year. It is no surprise that consumers across generations continue to use new channels over in-branch banking.

  • The demand for drive-through banking doubled for young millennials.
  • The demand for phone banking tripled for Generation Z.
  • The percentage of young millennials communicating with their banks via email and social media rose by four times over the previous ten months.

Customers are more likely to visit a branch to receive advice, review their financial situation or to purchase a financial product. Many bank branches are being repurposed to reflect this new dynamic, with less emphasis on traditional over-the-counter services.

The way people pay has also changed, probably forever. Businesses encouraged digital and contactless payments, particularly for micropayments such as bus fares or paying for a coffee. In contrast, check use declined by about 44%. Forty-seven percent of community bank customers surveyed say they have mobile payments wallets, according to FIS’ PACE PULSE Survey for 2021.

Bank as a Partner
In addition to providing traditional services, many community banks elevated their position to financial partner, offering temporary services when and where they were needed. The immediate relief including increased spending limits on credit cards, payment deferral options on mortgages, personal loans based on need and penalty fee waivers for dipping below account minimums.

Since then, community banks have continued taking steps to boost financial inclusion. The unbanked and underbanked are prime candidates for new, low-cost financial services delivered through mobile channels and apps. Providing such services is likely to be well rewarded by enduring customer loyalty, but the banks need the right technologies to deliver them.

The State of the Industry
The last year has seen a flurry of M&A deals. Many recent mergers involved banks with mature brands, loyal customers and strong balance sheets. These institutions’ interest in deals reflects a need to reduce the cost of doing business and the universal need to keep pace with technology innovation.

Digital technologies and data are increasingly the baseline of success in banks of all sizes. Merging with a peer can jump-start innovation and provide a bigger footprint for new digital services.

Robotics Process Automation and Data
Although much of the discussion around digitalization has focused on customer services, digital technologies can also boost automation and efficiency. With the right approach, robotic process automation, or RPA, can automate high-volume repeatable tasks that previously required employees to perform, allowing them to be redeployed to more valuable tasks. But to maximize value, RPA should not be considered in isolation but as part of a bank’s overall data strategy.

The Road Ahead
Although the road ahead may be paved with uncertainty, these are things FIS expects to see across the industry:

Customers have rising expectations. They want banking services that are intuitive, frictionless and real time. Big Tech, not banks, are continuing to redefined the customer experience.

Crypto will become mainstream. Many consumers already hold and support cryptocurrencies as investments. Banks must prepare for digital currencies and the distributed ledger technology that supports them.

The branch must evolve. Banks need to reinvent the branch to offer a consistent smooth experience. Human services can be augmented by technologies that automate routine retail banking tasks. For example, video tellers can conduct transactions and banking services with customers, using a centrally based teller in a highly engaging real-time video/audio interaction. Banks must persevere to draw people back into their branches.

Investing in data and technology is essential. Banks must eliminate guesswork and harness data to drive better decisions, increasing engagement and building lifetime loyalty. Smart banks can use customer data to gain unique insight and align banking with life events, such as weddings, school and retirement.

The new age of competition is also one of collaboration. At a time when community banks and their customers are getting more involved with technology, every bank needs to adopt a fintech approach to banking. Few banks can achieve this alone; the right partner can help an institution keep up the latest developments in technology and focus on its core mission to attract and retain customers.

Three Things to Do Now for Success During Tax Season

After the holiday season, many people go back to work refreshed and ready to take on a new year. However, for banks and their vendors, January is one of the busiest times of the year.

Tax season kicks off every January. Customers must receive tax documents for reporting income, loan interest payments and other financial data required by the IRS. The process of collecting the proper data, building the documents and sending them to customers can often be stressful, unorganized and prone to mistakes. Banks have the charge of getting their customers the right information, at the right time, designed in a familiar way. This process is crucial to reinforcing the trust institutions actively work to build each day with their customers.

Many banks accept this stressful process as “just the way it is.” However, there are things leaders can do now, before the federal government even releases the annual tax data fields, to prepare for the January rush.

Create a Game Plan
Banks know that the biggest frustration with tax documents is that the IRS typically does not release the current year’s data fields and form requirements until late fall. While the forms do not typically change dramatically year-to-year, there are always some changes that must be mapped from the core into any document generation processes. Banks must then match that form with their individual system.

To begin taking a more proactive approach to tax season, the first step is to treat tax preparations like any other project. Identify what your team can control and what it cannot. What worked well last year, what didn’t? It is important to think critically — remember, the goal of this exercise is to streamline the process.

Work through the process and timeline step by step with your team, including all key employees who work closely on this project. Discuss pain points, things you can control and possible action items that can be taken ahead of time.

Once you have successfully identified all dependencies, fill in your project timeline. It is important to start sooner rather than later. Luckily there are two vital steps you can take right now.

Contact Your Core
Get in contact with your core provider as early as possible to discuss any changes. Discuss timelines and deadlines that can be shared internally and added to your project timeline. If your bank can receive test data from the core to proactively work through the process, that can prove incredibly valuable.

One of the larger obstacles of the tax process is the data matching and correct application of the data on the form. Janine Specht, senior vice president of business applications and innovation officer at Kearny Bancorp in Kearny, New Jersey, makes a point of coordinating with her core as early as possible to avoid these pain points.

“We have experienced missing data and wrong boxes which leads to the files being received by our core processor getting input incorrectly,” says Specht. “Then we realized we weren’t ready to print and send.”

Specht recommends creating a calendar with alerts for when to expect certain steps, so nothing is overlooked.

Contact Your Document Vendor
Once the core data is set and properly mapped, your team should prepare document vendors for a smooth workflow. If possible, coordinate any changes with vendors ahead of time. Securing the test data from your core will help with this; however, there are still steps you can take to prepare with your vendor if you cannot get any test data.

Communicate the deadlines and timelines you received from your core to the vendor, and be sure to get any deadlines or important steps from them to add to the internal project timeline.

Discuss any design issues that need to be solved outside of data fields. It is important to send customers a form that looks like the tax form they will be filling out, since the familiarity makes it easier to figure out what they need to do with the documents and reduce calls to customer service.

Tax season is stressful, but there are steps bankers can take ahead of time to ease some of those pain points. The more bank leaders can work through and plan for, the more prepared their employees will be. As banks are working through the process and create the project timeline, remember to think critically and outside of the box. This proactive mindset will make the New Year start more efficiently and reduce the stress associated with tax season.

Data is the Secret Weapon for Successful M&A

The topic of data and analytics at financial institutions typically focuses on how data can be used to enhance the consumer experience. As the volume of M&A in the banking industry intensifies to 180 deals this year, first-party data is a critical asset that can be leveraged to model and optimize M&A decisions.

There are more than 10,000 financial institutions in the U.S., split in half between banks and credit unions. That’s a lot of targets for potential acquirers to sift through, and it can be difficult to determine the right potential targets. That’s where a bank’s own first-party data can come in handy. Sean Ryan, principal content manager for banking and specialty finance at FactSet, notes that “calculating overlap among branch networks is simple, but calculating overlap among customer bases is more valuable — though it requires much more data and analysis.” Here are two examples of how that data can be used to model and select the right targets:

  • Geographic footprint. There are two primary camps for considering footprint from an M&A perspective: grabbing new territory or doubling down on existing serving areas. Banks can use customer data to help determine the optimal targets for both of these objectives, like using spend data to understand where consumers work and shop to indicate where they should locate new branches and ATMs.
  • Customer segmentation. Banks often look to capturing market share from consumer segments they are not currently serving, or acquire more consumers similar to their existing base. They should use data to help drive decision-making, whether their focus is on finding competitive or synergistic customer bases. Analyzing first-party transaction data from a core processor can indicate the volume of consumers making payments or transfers to a competitor bank, providing insights into which might be the best targets for acquisition. If the strategy is to gain market share by going after direct competitors, a competitive insight report can provide the details on exactly how many payments are being made to a competitor and who is making them.

The work isn’t done when a bank identifies the right M&A target and signs a deal. “When companies merge, they embark on seemingly minor changes that can make a big difference to customers, causing even the most loyal to reevaluate their relationship with the company,” writes Laura Miles and Ted Rouse of Bain & Co. With the right data, it is possible that the newly merged institution minimizes those challenges and creates a path to success. Some examples include:

  • Product rationalization. After a bank completes a merger, executives should analyze specific product utilization at an individual consumer or household level, but understanding consumer behavior at a more granular level will provide even greater insights. For example, knowing that a certain threshold of consumers are making competitive mortgage payments could determine which mortgage products the bank should offer and which it should sunset. Understanding which business customers are using Square for merchant processing can identify how the bank can make merchant solutions more competitive and which to retain post-merger. Additionally, modeling the take rate, product profitability and potential adoption of the examples above can provide executives with the final details to help them make the right product decisions.
  • Customer retention. Merger analysis often indicates that customer communication and retention was either not enough of a focus or was not properly managed, resulting in significant attrition for the proforma bank. FactSet’s Ryan points out that “too frequently, banks have been so focused on hitting their cost save targets that they took actions that drove up customer attrition, so that in the end, while the buyer hit the mark on cost reductions, they missed on actual earnings.” Executives must understand the demographic profiles of their consumers, like the home improver or an outdoor enthusiast, along with the life events they are experiencing, like a new baby, kids headed off to college or in the market for a loan, to drive communications. The focus must be on retaining accountholders. Banks can use predictive attrition models to identify customers at greatest risk of leaving and deploy cross-sell models for relationships that could benefit from additional products and services.

M&A can be risky business in the best of circumstances — too often, a transaction results in the loss of customers, damaged reputations and a failure to deliver shareholder value. Using first-party data effectively to help drive better outcomes can ensure a win-win for all parties and customers being served.

What Banks Missed

It’s a classic case of a couple of upstarts upending the business of banking.

Increasingly familiar names such as Affirm Holdings, Afterpay Ltd. and Klarna Bank, as well as few household names such as PayPal Holdings, are busy taking credit card business away from banks by offering interest-free, installment loans at the point of sale.

Almost overnight, this type of lending has grown into a national phenomenon, starting with online merchants and then spreading throughout the industry, as Bank Director Managing Editor Kiah Haslett wrote about earlier this year.

C + R Research reports that of 2,005 online consumers, nearly half are making payments on some kind of buy now, pay later loan. More than half say they prefer that type of lending to credit cards, citing ease of payments, flexibility and lower interest rates as their top reasons why they prefer to buy, now pay later.

The amount of money flowing into the space is substantial. In August, Square announced that it would purchase Afterpay for $29 billion. Mastercard is trying to get into the game as well, announcing a deal in September to partner with multiple banks such as Barclays US, Fifth Third Bancorp and Huntington Bancshares to bring buy now, pay later to merchants.

Whatever your skepticism of the phenomenon may be, or your lack of interest in consumer lending, it’s clear that financial technology companies are chipping away at bank business models. This phenomenon begs the question: Why are fintech companies having such success when banks could have taken the opportunity but did not?

Banks have the data. They “know their customer” — both in the regulatory and relationship sense. Yet, they didn’t anticipate consumers’ interest or demand because they already had a product, and that product is called a credit or debit card.

Few companies cannibalize their business models by offering products that directly compete with existing products. But increasingly, I believe they should. Banks that don’t acknowledge the realities of today’s pressures are vulnerable to tomorrow’s innovation.

When we think about the business of banking today, I think about a glass half empty. It doesn’t mean we can’t put a little bit more water into it. But it does require an honest assessment of gaps in your current strategy and an assessment of the team you’d need — not necessarily the team you employ.

As I head into Bank Director’s Audit & Risk Committees Conference in Chicago this Monday through Wednesday, these are some of the themes on my mind. In some ways, having a glass half empty is sometimes the best thing for you.

It gives you the chance to do something positive to change it.

How a Data-Driven Sales Methodology Can Help Banks Grow

Two issues are challenging banks to capitalize on any sales momentum and risk sales inertia. Without data and analytics, banks will struggle to scale sales methodology and grow revenue — even if they have an effective sales methodology and highly trained team in place.

Current market dynamics are creating a new set of obstacles for financial institutions to meet commercial revenue targets in the face of economic uncertainty and deteriorating industries and sub-segments. In addition, frontline sales resources at banks have become consumed by servicing and monitoring activities as institutions refocused relationship managers to portfolio management during the coronavirus pandemic

While banks might experience short-term growth, they will struggle to find long-term success given the absence of a focused, cost-effective and scalable process aimed at the ideal, targeted customer. That’s because the traditional, historical methods for selling are largely ineffective in today’s environment. Commercial banking sales have been rooted in selling through relationships and networking with “centers of influence,” such as accountants or attorneys. This is challenging approach in today’s climate because of a lack of a methodical plan to expand, repopulate, curate and filter the network on an ongoing basis to insure ample and effective referrals. The financial results prove this out with historically low win rates, sporadic cross-sale success and — in many cases — heightened levels of sales personnel attrition.

Without a standardized methodology, banks are generally unable to unlock the magnitude of their organization. Sales efforts are not repeatable and must be reinvented with each new sale, proving both costly and ineffective in business development. Without scalability, as banks grow inorganically, these challenges compounded and complicate further growth.

Banks have historically failed to leverage their disparate data sources to drive the methodology and optimize execution of sales plans. It is nearly impossible for bankers to identify and prioritize relationships in a meaningful way, given how data is typically stored in disparate data houses across multiple non-integrated systems.

The lack of coordination around data means that banks typically fail to effectively, easily and accurately align product revenue, whether interest or fee income, to an individual borrower or relationship. Executives face a challenge in planning and segmenting holistic, high-opportunity sales calls through proper segmentation and targeted sales activities without a clear understanding of the 360-degree profitability view.

Why is this important? Now more than ever, banks require a new scalable method to effectively identify, pursue, and sell to targeted existing and new prospective clients who offer new opportunities within optimal, performing industry segments.

A data-driven sales model is the key to scalability. Scalability is a sought-after state of operations, and provides the foundation for rapid, cost-effective growth. At the core of scalability is repeatability — the ease with which results can be reproduced even as bank operations change and adapt to varying conditions. Scalability is often made possible through technology enablement while leveraging automation.

Banks have explored scalability through technology and tools such as loan origination systems, base level CRM systems, and integrated third-party tools to automate the credit underwriting and scoring processes. But this alone does not create or generate scalability. Scalability is constructed by standardized, streamlined policies and procedures, and is evidenced by its repeatability and simplicity.

Scalable organizations benefit from economies of scale, processing greater volumes with fewer resources. The direct result of top line revenue growth is increased net profits and reduced operating expenses. A bank’s DNA must be central to the intersection of sales methodology and technology to drive support and insight, leading to greater scalability and accelerated growth.

In our view, banks should operate with a delivery model that leverages data and analytics, provides scalability and identifies the following: advanced customer segmentation, early-stage opportunity identification, early detection of significant cross sell opportunities and pre-defined sales targets supported by actionable and tactical workplans. With the right tool, banks also unify the sales management process and drive user adoption and experience through customized automated dashboards and reporting, accelerating success and driving sales accountability and transparency. With this approach, banks can manage relationship managers’ sales activity in ways that create scalable, sustainable sales success and ultimately achieve higher growth rates.

Smart Ways to Find Loan Growth

In a long career focused on credit risk, I’ve never found myself saying that the industry’s biggest lending challenge is finding loans to make.

But no one can ignore the lackluster and even declining demand for new loans pervading most of the industry, a phenomenon recently confirmed by the QwickAnalytics® National Performance Report, a quarterly report of performance metrics and trends based on the QwickAnalytics Community Bank Index.

For its second quarter 2021 report, QwickAnalytics computed call report data from commercial banks $10 billion in assets and below. The analysis put the banks’ average 12-month loan growth at negative -0.43 basis points nationally, with many states showing declines of more than 100 basis points. If not reversed soon, this situation will bring more troubling implications to already thin net interest margins and stressed growth strategies.

The question is: How will banks put their pandemic-induced liquidity to work in the typical, most optimal way — which, of course, is making loans?

Before we look for solutions, let’s take an inventory of some unique and numerous challenges to what we typically regard as opportunities for loan growth.

  • Due to the massive government largess and 2020’s regulatory relief, the coronavirus pandemic has given the industry a complacent sense of comfort regarding credit quality. Most bankers agree with regulators that there is pervasive uncertainty surrounding the pandemic’s ultimate effects on credit. Covid-19’s impact on the economy is not over yet.
  • We may be experiencing the greatest economic churn since the advent of the internet itself. The pandemic heavily exacerbated issues including the e-commerce effect, the office space paradigm, struggles of nonprofits (already punished by the tax code’s charitable-giving disincentives), plus the setbacks of every company in the in-person services and the hospitality sectors. As Riverside, California-based The Bank of Hemet CEO Kevin Farrenkopf asks his lenders, “Is it Amazonable?” If so, that’s a market hurdle bankers now must consider.
  • The commercial banking industry is approaching the tipping point where most of the U.S. economy’s credit needs are being met by nonbank lenders or other, much-less regulated entites, offering attractive alternative financing.

So how do banks grow their portfolios in this environment without taking on inordinate risk?

  • Let go of any reluctance to embrace government-guaranteed lending programs from agencies including the Small Business Administration or Farmers Home Administration. While lenders must adhere to their respective protocols, these programs ensure loan growth and fee generation. But perhaps most appealing? When properly documented and serviced, the guaranties offer credit mitigants to loan prospects who, because of Covid-19, are at approval levels below banks’ traditional standards.
  • Given ever-present perils of concentrations, choose a lending niche where your bank has both a firm grasp of the market and the talent and reserves required to manage the risks. Some banks develop these capabilities in disparate industries, ranging from hospitality venues to veterinarian practices. One of the growing challenges for community banks is the impulse to be all things to all prospective borrowers. Know your own bank’s strengths — and weaknesses.
  • Actively pursue purchased loan participations through resources such as correspondent bank networks for bankers, state trade groups and trusted peers.
  • Look for prospects that previously have been less traditional, such as creditworthy providers of services or products that cannot be obtained online.
  • Remember that as society and technology change, new products and services will emerge. Banks must embrace new lending opportunities that accompany these developments, even if they may have been perceived as rooted in alternative lifestyles.
  • In robust growth markets, shed the reluctance to provide — selectively and sanely — some construction lending to help right the out-of-balance supply and demand currently affecting 1 to 4 family housing. No one suggests repeating the excesses of a decade ago. However, limited supply and avoidance of any speculative lending in this segment have created a huge value inflation that is excluding bankers from legitimate lending opportunities at a time when these would be welcomed.

Bankers must remember the lesson from the last banking crisis: Chasing growth using loans made during a competitive environment of lower credit standards always leads to eventual problems when economic stress increases. This is the “lesson on vintages” truism. A July 2019 study from the Federal Deposit Insurance Corp. on failed banks during the Great Recession revealed that loans made under these circumstances were critical contributors to insolvency. Whatever strategies the industry uses to reverse declining loan demand must be matched by vigilant risk management techniques, utilizing the best technology to highlight early warnings within the new subsets of the loan portfolio, a more effective syncing of portfolio analytics, stress testing and even loan review.

2021 Technology Survey Results: Tracking Spending and Strategy at America’s Banks

JPMorgan Chase & Co. Chairman and CEO Jamie Dimon recognizes the enormous competitive pressures facing the banking industry, particularly from big technology companies and emerging startups.

“The landscape is changing dramatically,” Dimon said at a June 2021 conference, where he described the bank’s growth strategy as “three yards and a cloud of dust” —  a phrase that described football coach Woody Hayes’ penchant for calling running plays that gain just a few yards at a time. Adding technology, along with bankers and branches, will drive revenues at Chase — and also costs. The megabank spends around $11 billion a year on technology. Products recently launched include a digital investing app in 2019, and a buy now, pay later installment loan called “My Chase Plan” in November 2020. It’s also invested in more than 100 fintech companies.

“We think we have [a] huge competitive advantage,” Dimon said, “and huge competition … way beyond anything the banks have seen in the last 50 [to] 75 years.”

Community banks’ spending on technology won’t get within field-goal distance of JPMorgan Chase’s technology spend, but budgets are rising. More than three-quarters of the executives and board members responding to Bank Director’s 2021 Technology Survey, sponsored by CDW, say their technology budget for fiscal year 2021 increased from 2020, at a median of 10%. The survey, conducted in June and July, explores how banks with less than $100 billion in assets leverage their technology investment to respond to competitive threats, along with the adoption of specific technologies.

Those surveyed budgeted an overall median of almost $1.7 million in FY 2021 for technology, which works out to 1% of assets, according to respondents. A median 40% of that budget goes to core systems.

However, smaller banks with less than $500 million in assets are spending more, at a median of 3% of assets. Further, larger banks with more than $1 billion in assets spend more on expertise, in the form of internal staffing and managed services — indicating a widening expertise gap for community banks.

Key Findings

Competitive Concerns
Despite rising competition outside the traditional banking sphere — including digital payment providers such as Square, which launched a small business banking suite shortly after the survey closed in July — respondents say they consider local banks and credit unions (54%), and/or large and superregional banks (45%), to be the greatest competitive threats to their bank.

Digital Evolution Continues
Fifty-four percent of respondents believe their customers prefer to interact through digital channels, compared to 41% who believe their clients prefer face-to-face interactions. Banks continued to ramp up their digital capabilities in the third and fourth quarters of last year and into the first half of 2021, with 41% upgrading or implementing digital deposit account opening, and 30% already offering this capability. More than a third upgraded or implemented digital loan applications, and 27% already had this option in place.

Data Dilemma
One-third upgraded or implemented data analytics capabilities at their bank over the past four quarters, and another third say these capabilities were already in place. However, when asked about their bank’s internal technology expertise, more than half say they’re concerned the bank isn’t effectively using and/or aggregating its data. Less than 20% have a chief data officer on staff, and just 13% employ data scientists.

Cryptocurrency
More than 40% say their bank’s leadership team has discussed cryptocurrency and are weighing the potential opportunities and risks. A quarter don’t expect cryptocurrency to affect their bank; a third haven’t discussed it.

Behind the Times
Thirty-six percent of respondents worry that bank leaders have an inadequate understanding of how emerging technologies could impact their institution. Further, 31% express concern about their reliance on outdated technology.

Serving Digital Natives
Are banks ready to serve younger generations? Just 43% believe their bank effectively serves millennial customers, who are between 25 and 40 years old. But most (57%) believe their banks are taking the right steps with the next generation — Gen Z, the oldest of whom are 24 years old. It’s important that financial institutions start getting this right: More than half of Americans are millennials or younger.

To view the full results of the survey, click here.

Taking Model Risk Management to the Next Level

A financial institution’s data is one of its most valuable resources. Banks constantly collect data on their loans, deposits and customer behaviors. This data should play a key role in how financial intuitions manage their risks.

Yet, developing a data strategy can be seen as too complex based on the sheer amount of data an institution may have, or as an unnecessary burden if the objective is solely to use the information to satisfy regulatory requirements. But a holistic data strategy can enhance value across all model risk management (MRM) platforms, both for regulatory and strategic purposes. On the flip side, being inconsistent or not updating data and inputs in a timely manner can lead to inaccurate or inconsistent results. Executives need to continually update and review information for consistency; if not, the information’s relevancy in assessing risk across various platforms will decrease.

Currently, the most common data strategy approach for banks is using individual tools to measure risk for regulatory purposes. For instance, financial institutions are required to calculate and monitor interest rate risk related to their balance sheet and potential movements in future interest rates. Typically, one team within the institution extracts data and transfers it to another team, which loads the data into an internal or external model to calculate the various interest rate profiles for management to analyze and make decisions. The institution repeats this process for its other models (credit, capital adequacy, liquidity, budgeting, etc.), adjusting the inputs and tools as needed. Often, banks view these models as individual silos — the teams responsible for them, and the inputs and processes, are separate from one another. However, the various models used to measure risk share many commonalities and, in many aspects, are interdependent.

Integrating model risk management processes require understanding a bank’s current data sources and aggregation processes across all of its current models. The first step for executives is to understand what data is currently used across these platforms, and how your organization can utilize it other beyond just checking the regulatory box. In order to enhance data quality, can one data extract be used for multiple platforms? For example, can the same loan-level data file be used for different models that use similar inputs such as asset liability management (ALM) and certain CECL models? While models may utilize some different or additional fields and inputs, there are many fields — such as contractual data or loan prepayment assumptions — that are consistent across models. Extracting the data once and using it for multiple platforms allows institutions to minimize the risk of inaccurate or faulty data.

From here, bank executives can develop a centralized assumption set that can be modeled across all platforms to ensure consistency and align results between models. For instance, are the credit assumptions that are developed for CECL purposes consistent with those used to calculate your ALM and liquidity profile under various scenarios? Are prepayment assumptions generated within the ALM model also incorporated into your CECL estimate? Synchronizing assumptions can provide more accurate and realistic results across all platforms. The MRM dashboard is a tool that can be configured to alert bank executives of emerging risks and ensure that data shared by different models is consistent.

One common method of gaining insights using MRM is through scenario and stress testing. Today’s environment is uncertain; executives should not make future decisions without in-depth analysis. They can develop scenarios for potential growth opportunities, modeling through the integrated platforms to calculate impacts to profitability and credit and interest rate risk. Similarly, they can expand deposit data and assumptions to assess high-risk scenarios or future liquidity issues apart from normal day-to-day operations. Whatever the strategy may be, assessing risk on an integrated basis allows management to gain a better understanding of all impacts of future strategies and make stronger business decisions.

Once institutions begin centralizing their data and model inputs and streamlining their monitoring processes using MRM dashboards, management can shift their focus to value-added opportunities that go beyond compliance and support the strategic vision of the institution.

The Key to Upgrading Digital Experiences

The pandemic has accelerated a number of trends and digital roadmaps, momentum that continues today.

Microsoft Corp. Chairman and CEO Satya Nadella put it best when he said “We’ve seen two years’ worth of digital transformation in two months.” In banking, 59% of consumers said the pandemic increased their expectations of their financial institutions’ digital capabilities. How can banks respond?  

A Non-Negotiable Experience
As customers, haven’t we all had an experience that left us confused? Many times it’s something obvious, like a marketing email urging us to download an app that we’ve had downloaded for years and use weekly. Customers expect that when they share their data, they get a better experience. A recent survey of Generation Z consumers reported that nearly 40% give a business only one chance to provide a satisfactory digital experience before moving onto a competitor.

Customers also expect their bank to be a strategic partner in money management, offering relevant services based on the data they have. These experiences can build loyalty by making customers feel taken care of by their financial institutions.

Common Challenges
When it comes to managing and optimizing their customers’ digital experiences, we see banks dealing with a few major issues:

  • Difficulty effectively cross-selling between products.
  • Disparate services where data lives in disconnected silos.
  • The scale of data, often exceeding legacy capabilities.

These challenges, along with many others, stem from the fact that customer data often live in numerous different systems. When data is scattered and siloed, it’s impossible to tie it together to understand customers or create personalized digital experiences that engender loyalty. This is why many banks are turning to customer data platforms (CDP).

Upgrading the Digital Experience
CDPs are powering some of the most cutting edge, customer-centric digital programs across leading financial institutions. An enterprise CDP makes data accessible and useful by bringing disparate data sources together, cleansing the data, and creating a singular view of the customer that can be used across the entire organization. It can become a bank’s single source of truth on customers. Marketing can connect to customers with personalized offers, analytics can explore data to find trends and areas of opportunity, customer service can access relevant information to assist customers, and finance can forecast with customer key performance indicators.

Should you consider a CDP?
Here are a few questions executives should ask to determine if their bank’s current setup is working:

  • Are customer data points and interactions centralized in one location?
  • How much time are analysts spending gathering customer data for reporting?
  • Is marketing able to easily use the same customer data to drive personalization?
  • How confident are teams in the data?
  • Is it easy to bring in a new data source?

If there is hesitation around any of the answers, looking at CDP options could be a really smart idea.

Capabilities to Look for

There are many companies using CDP terminology to describe products that aren’t exactly that. Banks should focus on a few key features when evaluating a CDP.

Speed to value. How long does it take to pull data together for a customer 360 degree view? When will data be ready to serve customers and power initiatives across the organization? The best way to accelerate these timelines is with a CDP that uses artificial intelligence to unify and organize records, which is much faster and more stable than rules-based data unification systems.

Enterprise functionality. A CDP should serve as the single source of truth for the entire organization, with a suite of tools that can accommodate the needs of different teams. Multiple views means teams are only presented with the data they need, with the methods that they prefer: robust SQL query engine for analysts, point-and-click segmentation for less technical users and dashboards for executive visibility.

Flexibility and interoperability. A CDP should work with your bank’s current technology investments, connecting easily to any tools or systems you add in the future. One sign of this is a CDP having many partnerships and easy integrations that can quickly allow you to take action.

You need to trust that a CDP can scale to the enterprise and compliance demands of a bank, accommodating vast stores of data that will only continue to grow.

A critical opportunity
There is unprecedented demand from banking leaders to stand up a CDP as a critical business driver. And no wonder. With so many customers using digital channels and generating more data, banks need to double down on increasing the lifetime value of existing customers while finding ways to attract new customers.

Can Banks Afford to Be Short-Sighted With Real-Time Payments?

The industry’s payments ecosystem is developing rapidly in response to increasing consumer demand for faster, smarter payments.

The need for real-time payments was accelerated by the global pandemic — but most banks are moving far too cautiously to respond to market demand, whether that is P2P, B2B, B2C or other segments. Currently, The Clearing House’s RTP® network is the only available real-time payments platform, while the Federal Reserve’s instant payments service, FedNow℠, is in a pilot phase with plans to launch in 2023. FedNow will equip financial institutions of all sizes with the ability to facilitate secure and efficient real-time payments round the clock.

For most banks, operating on core legacy technology has created a payments infrastructure that is heavy-handed, disjointed, costly and difficult to maintain, with no support for future innovation. Most banks, fearing the cost and effort of modernization, have settled for managing multiple payment networks that connect across disparate systems and require the support of numerous vendors. With the introduction of real-time payments, can these new payment rails afford to be a mere addendum to the already-byzantine payment architecture of banks?

Answering “yes” begets more questions. How resilient will the new offering be on the old infrastructure? Can banks afford to be myopic and treat real-time payments as a postscript? Are short-sighted payment transformations elastic enough to accommodate other innovations, like the Central Bank Digital Currency (CBDC) that are in the offing?

Preparation starts with an overhauling of payments infrastructure. If banks are to place themselves at a vantage point, with a commanding perspective into the future of payments, they should consider the following as part of the roadmap to payments modernization:

  1. From transactions to experience. Payments are no longer merely functional transactions; they are expected to provide qualitative attributes like experience, speed and intelligence. Retail and business customers increasingly demand frictionless and intuitive real-time payments, requiring banks to refurbish the payment experiences delivered to clients.
  2. The significance of payment data. The ISO20022 data standard for payments is heavier and richer compared to legacy payments data, and is expected to be the global norm for all payments by 2025. Banks are under increasing pressure to comply, with players like SWIFT already migrating to this format and more than 70 countries already using ISO20022. Payment solutions that can create intuitive insights from centralized data stored in ISO20022 format, while also being able to convert, enrich and validate legacy messaging into ISO20022, are essential. Banks can benefit from innovative services like B2B invoices and supply chain finance, as Request for Payment overlay services is a key messaging capability for customers of real-time payments.
  3. Interoperability of payment systems. The interoperability between payment systems will be an imperative, especially with the ecosystem of different payment rails that banks have to support. Interoperable payment rails call for intelligent routing, insulating the payer and payee from the “how” of payment orchestration, and paving the way for more operational efficiency. Operating costs account for more than 68% of bank payment revenues; centralizing the management of multiple payment networks through an interoperable payment hub allows bankers to minimize these costs and improve their bottom lines.
  4. Streamlining payment operations. Work stream silos lead to fragmented, inefficient and redundant payment operations, including duplicated fraud and compliance elements. This is where payment hubs can add value by streamlining payment operations through a single, consolidated operation for all payment types. Payment hubs are a great precursor for subsequent modernization: intelligent payment hubs can handle omnichannel payments, as well as different payment types like ACH, Fedwire, RTP and FedNow in the future. This takes care of the entire payment lifecycle: initiation, authorization, clearing, settlement and returns.
  5. Future-proofing payment systems. Following the path of trendsetters, banks have to equip themselves with future-proof solutions that can adapt to real-time domestic and cross-border payment systems processing multiple currencies. As open-banking trends gain traction, it is important to consider that the winds of change will eventually find payments, too. It is imperative that banks are cloud based and API driven, so they can innovate while being future-ready.

The opportunity cost of not offering real-time payments is becoming more evident for banks, as they wait for their core providers to enable real-time payments. Calls for banks to modernize their payments infrastructure are swelling to a roar; now is the time for banks to define their payments modernization strategy and begin to act.