Using Intelligent Automation to Bank Smarter, Not Harder


technology-5-4-19.pngBy this point in 2019, most consumers and companies are somewhat familiar with the concept of artificial intelligence. Executives and consultants have discussed its application in financial services for years; lately, the conversations have been brisk and some organizations are doing more than just talking. Many tangible AI use cases have emerged at financial institutions of all sizes over the last 12 months, and intelligent technology is beginning to make an impact on banks’ productivity and bottom lines.

Still, AI remains a largely abstract concept for many institutions. Some of the biggest challenges these banks face in preparing and executing an AI strategy starts with having a too-narrow definition of these technologies.

Technically, AI is the ability of machines to use complex algorithms to learn to do tasks that are traditionally performed by humans. It is often misrepresented or misunderstood in broader explanations as a wider range of automation technologies — technologies that would be more appropriately characterized as robotics or voice recognition, for example.

Banks interested in using intelligent automation, which includes AI, robotic process automation, and other smart technologies, should target areas that could benefit the most through operational efficiencies or speed up their digital transformation.

Banks are more likely to achieve their automation goals if executives shift their mindsets toward thinking about ways they can apply smart technologies throughout the institution. Intelligent automation leverages multiple technologies to achieve efficiency. Some examples include:

  • Using imaging technology to extract data from electronic images. For example, banks can use optical character recognition, or OCR, technology to extract information from invoices or loan applications, shortening the completion time and minimizing errors.
  • Robotic process automation, or RPA, to handle high-volume, repeatable manual tasks. Many institutions, including community banks with $180 million in assets up to the largest institutions in the world have leveraged RPA to reduce merger costs, bundle loans for sale and close inactive credit and debit cards.
  • Machine learning or AI to simulate human cognition and expedite problem solving. These applications can be used in areas ranging from customer service interactions to sophisticated back-office processes. Some industry reports estimate that financial institutions can save $1 trillion within the next few years through AI optimization. Several large banks have debuted their own virtual assistants or chatbots; other financial institutions are following suit by making it easier and more convenient for customers to transact on the go.

What are next steps for banks interested in using AI? Banks first need to identify the right use cases for their organization, evaluating and prioritizing them by feasibility and business need. It’s more effective to start with small projects and learn from them. Conduct due diligence to fully assess each project’s complexity, and plan to build interactively. Start moving away from thinking about robots replacing employees, and start considering how banking smarter – not harder – can play out in phases.

The Key To Creating A Profitable Deposit Strategy


deposit-5-6-19.pngSmall and mid-size banks can leverage technology to retain and grow their retail relationships in the face of fierce competition for deposits.

Big banks like JPMorgan Chase & Co., Bank of America Corp. and Wells Fargo & Co. continue to lead the battle for deposits. They grew their domestic deposits by more than 180 percent, or $2.4 trillion, over the past 10 years, according to an analysis of regulatory data by The Wall Street Journal. To survive and thrive, smaller institutions will need to craft sustainable, profitable strategies to grow deposits. They should invest in technology to become more efficient, develop effective marketing strategies and leverage data and analytics to personalize products and customer experiences.

Banks can use technology to achieve efficiencies such as differentiating net new money from transfers of existing funds. This is key to growing deposits. Traditionally, banks and their legacy core systems were unable to distinguish between new deposits and existing ones. This meant that banks paid out promotional interest and rewards to customers who simply shifted money between accounts rather than made new deposits. Identifying net new money allows banks to offer promotions on qualified funds, govern it more effectively, incentivize new termed deposits and operate more efficiently.

To remain competitive, small and mid-sized banks should leverage technology to create experiences that strengthen customer retention and loyalty. One way they can do this is through micro-segmentation, which uses data to identify the interests of specific consumers to influence their behavior. Banks can use it to develop marketing campaigns that maximize the effectiveness of customer touchpoints.

Banks can then use personalization to execute on these micro-segmentation strategies. Personalized client offerings require data, a resource readily available to banks. Institutions can use data to develop a deeper understanding of consumer behaviors and personalize product offers that drive customer engagement and loyalty.

Consumers deeply valued personalization, making it critical for banks trying to attract new customers and retain existing ones. A report by The Boston Consulting Group found that 54 percent of new bank customers said a personalized experience was “either the most important or a very important factor” in their decision to move to that bank. Sixty-eight percent of survey respondents added products or services because of a personalized approach. And “among customers who had left a bank, 41 percent said that insufficient personalized treatment was a factor in their decision,” the report read.

Banks can use data and analytics to better understand consumer behavior and act on it. They can also use personalization to shift from push marketing that promotes specific products to customers to pull marketing, which draws customers to product offerings. Institutions can leverage relationship data to build attractive product bundles and targeted incentives that appeal to specific customer interests. Banks can also use technology to evaluate the effectiveness of new products and promotions, and develop marketing campaigns to cross sell specific, recommended products. This translates to more-informed offers with greater response, leading to happier customers and improved bottom lines.

Small and mid-sized banks can use micro-segmentation and personalization to increase revenue, decrease costs and provide the kind of customer experience that wins customer deposits. Building and retaining relationships in the digital era is not easy. But banks can use technology to develop marketing campaigns and personalization strategies as a way to strengthen customer loyalty and engagement.

As the competition for deposits heats up, banks will need to control deposits costs, prevent attrition and grow deposits in a profitable and sustainable way. Small and mid-size banks will need to invest in technology to optimize marketing, personalization and operational strategies so they can defend and grow their deposit balances.

Three Tech Strategies for Banks, Based on Size


strategy-5-3-19.pngHow should you position your bank for the future—or, for that matter, the present?

This is one of the most perplexing questions challenging leadership teams right now. It is not a new consideration; indeed, the industry has been in a constant state of evolution for as long as anyone on our team can remember. Yet lately, it has taken on a new, possibly more existential sense of urgency.

Fortunately, there are examples of banks, of different sizes and a variety of business models, keeping pace with changing consumer expectations and commercial clients’ needs. The industry seems to be responding to the ongoing digital revolution in banking in three ways.

The biggest banks—those like JPMorgan Chase & Co., Bank of America Corp. and Wells Fargo & Co.—have the resources to forge their own paths on the digital frontier.

These banks spend as much as $11 billion a year each on technology. They hire thousands of programmers to conceptualize digital solutions for customers.

The results are impressive.

As many as three-quarters of deposit transactions are completed digitally at these banks. A growing share of sales, account openings and money transfers take place over these banks’ digital channels as well. This allows these banks to winnow down their branch networks meaningfully while still gaining retail deposit market share.

The next step in their evolution is to combine digital delivery channels with insights gleaned from data. It’s by marrying the two, we believe, that banks can gain a competitive advantage by improving the financial lives of their customers.

Just below the biggest banks are super-regional and regional banks.

They too are fully embracing technology, although they tend to look outside their organizations for tailored solutions that will help them compete in this new era rather than develop the solutions themselves.

These banks talk about integration as a competitive advantage. They argue that they can quickly and nimbly integrate digital solutions developed elsewhere—growing without a burdensome branch network while also benefiting from the latest technologies without bearing the risk and cost of developing many of those solutions themselves. It is a way, in other words, for them to have their cake and eat it too.

U.S. Bancorp and PNC Financial Services Group fall into this category. Both are reconfiguring their delivery channels, reallocating funds that would be spent on expanding and updating their branch networks to digital investments.

In theory, this makes it possible for these banks to expand into new geographic markets with far fewer branches.

U.S. Bancorp announced recently that it will use a combination of digital channels and new branches to establish a physical retail beachhead in Charlotte, North Carolina. PNC Financial is doing the same in Dallas, Texas, among other markets.

Finally, smaller community banks are adopting off-the-shelf solutions offered by their core providers—Fidelity National Information Services (FIS), Fiserv and Jack Henry & Associates.

This approach can be both a blessing and a curse. It is a blessing because these solutions have enabled upwards of 90 percent of community banks to offer mobile banking applications—table stakes nowadays in the industry. It is a curse because it further concentrates the reliance of community banks on a triumvirate of service providers.

In the final analysis, however, it is important to appreciate that smaller banks based outside of major metropolitan areas still have a leg up when it comes to tried-and-true relationship banking. Their share of loans and deposits in their local markets could even grow if the major money-center banks continue fleeing smaller markets in favor of big cities.

Smaller regional and community banks dominate small business loans in their markets—a fact that was recently underscored by LendingClub Corp.’s decision to close its small business lending unit. These loans still require local expertise—the type of expertise that resides in their hometown banks. The same is true of agriculture loans.

Banks are still banks, after all. Trust is still the top factor cited by customers in the selection process. And loans must still be underwritten in a responsible way if a bank wants to survive the irregular, but not infrequent, cycles that define our economy. The net result is that some community banks are not only surviving in this new digital era, they are thriving.

But this isn’t a call to complacency—far from it.

To compete in this new era of heightened digital competition, it is more important than ever for banks of all sizes to stay committed to the quest of constant improvement. That is why our team at Bank Director is thrilled to host bank executives and board members at the JW Marriott Nashville on May 9 and 10 for our annual Bank Board Training Forum, where we will talk about how to tackle these challenges and remain relevant in the years ahead.

Drafting a Data Strategy


data-4-29-19.pngBanks need to be aware of trends in data analytics that are driving decision-making and customer experience so they can draft an effective data plan. Doing so will allow them to compete with the biggest banks and non-bank technology competitors that are already using internal customer data to predict behavior and prescribe actions to grow those relationships. These approaches leverage concepts like machine learning and artificial intelligence — buzzwords that may seem intimidating but are processes and approaches that can leverage existing information to grow and deepen customer relationship and profitability.


analytics-4-29-19-tb.png10 Data and Analytics Trends Banks Should Consider
Current trends in analytics include focusing on the customer’s experience, using artificial intelligence and machine learning in analysis, and storing and organizing information in ways that reduce risk. Banks also need to know about threats like cybersecurity, long-term developments like leveraging blockchain, and how to build a governance program around the process. Knowing the trends can help companies make educated choices when implementing a data strategy.

datat-trends-4-29-19-tb.pngHow Banks Can Make Use of Data-Driven Customer Insight
Banks can use machine learning and artificial intelligence to gain insights into customer behavior and inform their decisions. These data-driven approaches can efficiently analyze the likeliness of future events, as well as suggest actions that would increase or decrease that likeliness. Many institutions recognize the need for new technical capabilities to improve their customer insight, but a significant percentage struggle to embrace or prioritize the technology among other priorities at their bank. These institutions have an opportunity to establish a data strategy, map out their internal information and establish appropriate governance that surrounds the process.

Consolidating Technology for a Merger of Equals


merger-4-24-19.pngMergers of equals are gaining in popularity, judging by the flurry of recently announced deals, but a number of tough decisions about technology have to be made during the post-merger integration phase to set up the new bank for success.

After every deal, management teams are under a great deal of pressure to realize the deal’s projected expense savings as quickly as possible. While the average industry timeline to select and negotiate a core processing contract is nine months, a bank merger team has about a third of that time—the Cornerstone framework estimates 100 days—to choose not just the core, but all software as well, and to renegotiate pricing and contract terms for the most critical systems so that integration efforts can begin.

Start with the Core
A comparison of core systems is often the first order of business. These five factors are the most relevant in determining which solution will provide the best fit for the post-merger institution:

  • Products and services to be offered by the continuing bank. If one institution has a huge mortgage servicing portfolio or a deeper mix of commercial lending, complex credits and treasury management, the core system will need to support those products.
  • Compatibility and integration with preferred digital banking solutions. If one or both merger partners rely on the delivery channel systems offered by their core providers, the integration team should evaluate the core, online and mobile solutions as a bundled package. On the other hand, if the selection process favors a best-of-breed digital channel solution with more-sophisticated service offerings, that decision emphasizes the need for a core system that supports third-party integration.
  • Input from system users. The merger team must work closely with other departments to evaluate the functionality of the competing core systems for their operations and interfacing systems.
  • Contractual considerations. The costs of early contract termination with a core, loan origination, digital channel or other technology provider can be significant, to the point of taking priority over functionality considerations. If it is going to cost $4 million to get out of a digital banking contract, the continuing organization may be better off keeping that system, at least in the near-term.
  • Market trends. Post-merger, the combined bank will be operating at a new scale, so it may be instructive to look at what core systems other like-size financial institutions have chosen to run their operations.

A lot of factors come into play when the continuing bank is finalizing what that solution set looks like, but at the end of the day, it is about functionality, integration, cost and breadth of services.

Focus on the Top 20
The integration team should use a similar process to select the full complement of technology required to run a modern financial institution. Cornerstone suggests ranking the systems currently in operation at both banks by annual costs, based on accounts payable data sorted by vendor in descending order. Next, identify contract lifecycle details to compare the likely costs of continuing or ending each vendor relationship, including liquidated damages, deconversion fees and other expenses.

That analysis lays the groundwork to assess the features, functionality and pricing of like systems and rank which options would be most closely aligned with customer service strategies, system capabilities and cost efficiencies. It might seem that an objective, side-by-side comparison of technology systems should be a straightforward exercise, but emotions can get in the way.

A lot of people are highly passionate and have built their bank on being successful in the market. That passion may come shining through in these discussions—which is not necessarily a bad thing.

Working with an expert third party through the processes of system selection and contract negotiations can help provide an objective perspective and an insider’s view of market pricing. An experienced business partner can help technology integration teams and executives set up effective decision-making processes and navigate the novel challenges that may arise in realizing a central promise in a merger of equals—to create value through vendor cost reductions.

Toward that end, the due diligence process should identify about 20 contracts—for the core, online and mobile banking, treasury management, card processing and telecom systems, to name a few—to target for renegotiation in advance of the official merger date. A bank has hundreds of vendors to help run the enterprise, but it should focus most of the attention on the top 20. The bank can drive down costs through creative economies of scale by focusing on those contracts that are the most negotiable.

With its choice of two solutions for most systems and the promise of doubling volume for the selected vendors, the new bank can negotiate from an advantageous position. But its integration team must work quickly and efficiently to deliver on market expectations to assemble an optimal, cost-effective technology infrastructure—without cutting corners in the selection process and contract negotiations.

Think of this challenge like a dance. It is possible to speed up the tempo, but it is not possible to skip steps and expect to end up in the right place. The key components—the proper due diligence, financial reviews and evaluations—all still need to happen.

Download the free white paper, “Successfully Executing a Merger of Equals,” here.

Integration: Keeping The Best



Bank leadership teams that approach an acquisition with an open mind will have the best odds for successfully integrating the target, says Kim Snyder of KBS Results. In this video, she shares the three most common misconceptions held by acquirers. She also outlines how banks should communicate to employees and customers about an acquisition, and explains how to approach technology integration—so acquirers can ensure the target’s customers stay with the merged institution.

  • Common Misconceptions
  • Communicating to Employees
  • Explaining Benefits to Customers
  • Getting Technology Integration Right

 

The Transformative Impact Of Data & Voice



The biggest banks are spending billions on technology, but community banks can level the playing field by choosing technologies that personalize and enhance their interactions with customers, as Michael Carter, executive vice president at Strategic Resource Management, explains in this video. He shares how data and voice-enabled technologies could help community banks provide the digital experience that customers want.

  • Leveraging Data to Enhance the Customer Experience
  • Growing Use of Voice-Enabled Technologies
  • Opportunities for Community Banks

 

The Flawed Argument Against Community Banks


deposit-4-5-19.pngA few weeks ago, The Wall Street Journal published a story that struck a nerve with community bankers.

The story traced the travails of National Bank of Delaware County, or NBDC, a $375 million asset bank based in Walton, New York, that ran into problems after buying six branches from Bank of America Corp. in 2014.

It’s not that things were going great for NBDC prior to that, because they weren’t. Like many banks in small towns, it had to contend with stiff economic and demographic headwinds.

“As in other small towns that were once vibrant, decades of economic change altered the fabric of Walton,” Rachel Louise Ensign and Coulter Jones wrote in the Journal. “The number of area farms dwindled and manufacturing jobs disappeared.”

“Being located in, and serving, an economically struggling community could bring any bank down,” wrote Ron Shevlin, director of research at Cornerstone Advisors, in a follow-up story a week later.

NBDC hoped the branches acquired from Bank of America, for a combined $1 million, would revive its fortunes. But the deal only made things worse.

The branches saddled NBDC with higher costs and $12 million in added debt. Even worse, half the acquired deposits quickly went elsewhere, provoked by a poorly executed integration as well as, ostensibly, NBDC’s antiquated technology.

“Technology is causing strains throughout the banking industry, especially among smaller rural banks that are struggling to fund the ballooning tab,” Ensign and Jones wrote. “Consumers expect digital services including depositing checks and sending money to friends, which means they don’t necessarily need a local branch nearby. This increasingly means people are choosing a big bank over a small one.”

This echoes a common refrain in banking: that smaller regional and community banks can’t compete against the multibillion-dollar technology budgets of big banks—especially JPMorgan Chase & Co., Bank of America and Wells Fargo & Co.

Community bankers took issue with the article, Shevlin noted, because it seemed to portray the story of NBDC, which was acquired in 2016 by Norwood Financial Corp., as representative of community banks more broadly.

“This is so misleading,” tweeted Andy Schornack, president of Security Bank & Trust in Glencoe, Minnesota. “Pick on one under-performing bank to represent the whole.”

“Community banks are profitable and thriving,” tweeted Tanya Duncan, senior vice president of the Massachusetts Bankers Association. “Most offer technology that makes transactions seamless.”

Schornack and Duncan are right. One doesn’t have to look far to find community banks that are thriving, with many outperforming the industry.

A textbook example is Germantown Trust and Savings Bank, a $376 million asset bank based in Breese, Illinois.

Germantown has generated a higher return on assets than the industry average in 11 of the past 12 years. The only exception was in 2013, when it generated a 1.52 percent pre-tax ROA, compared to 1.55 for the overall industry.

 Germantown-Bank-chart.png

Germantown’s performance through the financial crisis was especially impressive. While most banks reported lower earnings in 2009, with the typical bank recording a loss, Germantown experienced a surge in profitability.

Germantown has gained local market share, too. Over the past eight years, its share of deposits throughout its four-branch footprint in Clinton County, Illinois, has grown from 27.8 percent up to 29.7 percent.

This is just one example among many community banks with a similar experience. For every community bank that’s ailing, in other words, you could point to one that’s thriving.

Yet, there’s another, more fundamental issue with the prevailing narrative in banking today. Namely, the data doesn’t support the claim that the biggest and most technologically-savvy banks are gobbling up share of the national deposit marketTwitter_Logo_Blue.png

In fact, just the opposite has been true over the past five years.

Let’s start with the big three retail banks—JPMorgan Chase, Bank of America and Wells Fargo—which are spending tens of billions of dollars a year on technology.

These three banks saw their combined share of domestic deposits swell in the wake of the financial crisis, climbing from 21.7 percent in 2007 up to 33.2 percent six years later. Since 2013, however, this trend has gone in the opposite direction, falling in four of the past five years. As of 2018, the three biggest banks in the country controlled 31.8 percent of total domestic deposits, a decline of 1.4 percentage points from their peak.

 Deposit-share-chart.png

The same is true if you broaden this out to include the nine biggest commercial banks. Their combined share of domestic deposits has dropped from a high of 47.6 percent in 2013 down to 45.6 percent last year.

Given the number of branches many of these banks have shed over the past decade, it’s surprising they haven’t lost a larger share of domestic deposits. Nevertheless, it’s worth reflecting on the fact that, despite the gloomy sentiment toward community banks that’s often parroted in the press, their current and future fortunes are far from bleak.

Applying the 1-10-100 Rule to Loan Management


data-4-2-19.pngImplementing new software may seem like an expensive and time-consuming challenge, so many financial institutions make do with legacy systems and workflows rather than investing in robust, modern technology solutions aimed at reducing operating expenses and increasing revenue. Unfortunately, banks stand to lose much more in both time and resources by continuing to use outdated systems, and the resultant data entry errors put institutions at risk.

The Scary Truth about Data Entry Errors
You might be surprised by the error rates associated with manual data entry. The National Center for Biotechnology Information evaluated over 20,000 individual pieces of data to examine the number of errors generated from manually entering data into a spreadsheet. The study, published in 2008, revealed that the error rates reached upwards of 650 errors out of 10,000 entries—a 6.5 percent error rate.

Calculating 6.5 percent of a total loan portfolio—$65,000 of $1 million, for example—produces an arbitrary number. To truly understand the potential risk of human data entry error, one must be able to estimate the true cost of each error. Solely quantifying data entry error rates is meaningless without assigning a value to each error.

The 1-10-100 Rule is one way to determine the true value of these errors.

The rule is outlined in the book “Making Quality Work: A Leadership Guide for the Results-Driven Manager,” by George Labovitz, Y.S. Chang and Victor Rosansky. They posit that the cost of every single data entry error increases exponentially at subsequent stages of a business’s process.

For example, if a worker at a communications company incorrectly enters a potential customer’s address, the initial error might cost only one dollar in postage for a wrongly-addressed mailer. If that error is not corrected at the next stage—when the customer signs up for services—the 1-10-100 Rule would predict a loss of $10. If the address remains uncorrected in the third step—the first billing cycle, perhaps—the 1-10-100 Rule would predict a loss of $100. After the next step in this progression, the company would lose another $1,000 due to the initial data entry error.

This example considers only one error in data entry, not the multitude that doubtlessly occur each day in companies that rely heavily on humans to enter data into systems.

In lending, data entry goes far beyond typos in customers’ contact information and can include potentially serious mistakes in vital customer profile information. Data points such as social security numbers and dates of birth are necessary to document identity verification to comply with the Bank Secrecy Act. Data entry errors also lead to mistakes in loan amounts. A $10,000 loan, for example, has different implications with respect to compliance reporting, documentation, and pricing than a $100,000 loan. Even if the loan is funded correctly, a single zero incorrectly entered in a bank’s loan management system can lead to costly oversights.

Four Ways Data Entry Errors Hurt the Bottom Line
Data entry errors can be especially troublesome and costly in industries in which businesses rely heavily on data for daily operations, strategic planning, risk mitigation and decision making. In finance, determining the safety and soundness of an institution, its ability to achieve regulatory compliance, and its budget planning depend on the accuracy of data entry in its loan portfolios, account documentation, and customer information profiles. Data entry errors can harm a financial institution in several ways.

  1. Time Management. When legacy systems cannot integrate, data ends up housed in different silos, which require duplicative data entry. Siloed systems and layers of manual processes expose an institution to various opportunities for human error. The true cost of these errors on an employee’s time—in terms of wages, benefits, training, etc.—add up, making multiple data entry a hefty and unnecessary expense.
  2. Uncertain Risk Management. No matter how many stress tests you perform, it is impossible to manage the risk of a loan portfolio comprised of inaccurate data. In addition, entry errors can lead to incorrectly filed security instruments, leaving a portfolio exposed to the risk of insufficient collateral.
  3. Inaccurate Reporting. Data entry errors create unreliable loan reports, leading to missed maturities, overlooked stale-dates, canceled insurance and other potentially costly oversights.
  4. Mismanaged Compliance. Data entry errors are a major compliance risk. Whether due to inaccurately entered loan amounts, file exceptions, insurance lapses or inaccurate reporting, the penalties can be extremely costly—not only in terms of dollars but also with respect to an institution’s reputation.

Reduce Opportunities for Human Error
An institution’s risk management plan should include steps intended to mitigate the inevitable occurrence of human error. In addition to establishing systems of dual control and checks and balances, you should also implement modern technologies, tools, and procedures that eliminate redundancies within data entry processes. By doing so, you will be able to prevent mistakes from happening, rather than relying solely on a system of double-checking.

Managing Cost, Efficiency & Control in the Loan Portfolio

What sets today’s lending environment apart is the potential for banks to collaborate with technology platforms to manage their risk more effectively and efficiently, explains Garrett Smith, the CEO of Community Capital Technology. In this video, he outlines how banks of varying sizes are diversifying their loan portfolios, and he shares his advice for banks seeking to buy or sell loans on the secondary market.

  • Using Technology to Manage the Loan Portfolio
  • Purchasing Loans on a Marketplace Platform
  • What to Know About Selling Loans