Three Reasons to Prioritize Digital Customer Service

Consumers and businesses are increasingly choosing to complete financial tasks in digital channels, but banks have largely failed to evolve their customer service and support strategies.

Traditional phone service models that banks have relied on for decades are notoriously frustrating and inefficient not only for the consumer, but for the agent as well. Forcing customers to leave the digital channel to connect with a service agent via a time-consuming phone experience is detrimental to customer satisfaction and loyalty. Not to mention, this channel hop leads to higher costs and inefficiencies for the bank. It’s time for banks to take a digital-first approach to customer service.

Digital customer service has experienced significant acceleration in recent months. Banks that modernize their customer service strategies with digital-first communication and collaboration capabilities will be able to enhance the customers’ and employees’ experiences. There are three top reasons banks should adopt digital customer service: modernize communications, boost operational efficiencies and increase customer engagement.

Modernize Communications
The coronavirus pandemic has amplified the use of digital this year, more than anyone could have predicted. With fewer customers visiting branches, digital banking usage has skyrocketed. While this shift made banks realize that the digital experience should be their top priority, many are neglecting the glue that makes digital transformation work: digital customer service.

For many consumers, this is the first time they’re relying on digital for more-complex tasks like opening accounts and applying for loans. Customers must have the ability to be met with full support and guidance within digital channels by bankers that can see their issue in real time and help them find a resolution.

Boost Operational Efficiencies
Contact centers have traditionally fielded simple requests, such as determining account balances and transferring money between accounts, but now self-service and automation allows most customers to handle these more straightforward tasks themselves. As a result, bank agents are typically met with more complex requests and inquiries. This has created a need for contact centers to become more sophisticated, with more highly-trained and specialized employees.

Savvy banks are recruiting AI to help with this transition — not just for customer-facing inquiries but agent training as well. Bots can speed up customer service by surfacing relevant information during interactions, alleviating agents from manually retrieving data from back-end systems. They can also recommend the best next action and pre-approved verbiage for customer responses, reducing time and effort for agents and increasing compliance with bank policies. As agents accept or decline the suggestions, the bank’s system can capture more data to optimize and improve bot recommendations for more accurate, targeted assistance in the future.

Digitizing customer service and enlisting bots to assist agents gives banks a way to save time, increase operational efficiencies and boost staff morale and satisfaction. This is especially important now, as they navigate thin margins and the pressure to do more with less.

Increase Customer Engagement
Today’s phone-centric customer service models typically include long wait times and disjointed experiences. Once customers connect with an agent, they have to spend time reauthenticating and providing context around the issue at hand. Meeting customers where they are in the digital channel instead — whether that’s through chat, video or voice — ensures that the agent can see the issue in real time, eliminating any guesswork. Agents should never have to ask ‘How can I help you?’ again. This more-seamless option leads to a better customer experience and increased engagement and loyalty.

Customers expect their financial services providers to know and understand them, just as big tech companies and major retailers like Amazon.com and Netflix do. Through digital customer service, banks can better, more quickly access relevant customer information necessary to tailor responses and interactions, ultimately boosting customer loyalty. In fact, it’s common for banks that leverage digital customer service to experience 20% improvements in customer satisfaction, reflected in net promoter and customer satisfaction scores.

Banks are increasingly realize that a phone-first approach to customer service will no longer cut it, especially in the increasingly digital world.  In fact, the most-advanced institutions are removing phone numbers from their websites entirely, replacing them with flexible, digital-first communication options. Those that embrace digital customer service will be well positioned to keep and grow customer relationships, increase profit margins and secure a strong competitive position.

The Promise, and Peril, of Risk Technology

The pandemic has underlined how essential risk technology is for proactive and responsive financial institutions.

Prior to the coronavirus outbreak, bank risk managers were already incorporating such technology to manage, sift and monitor various inputs and information. The pandemic has complicated those efforts to get a handle on emerging and persistent risks — even as it becomes increasingly critical to incorporate into day-to-day decision-making.

Data, and getting insights from it, has always been central to how risk managers have worked. That hasn’t changed,” says Sandeep Mangaraj, an industry executive at Microsoft who focuses on digital banking transformations.

Prior to the pandemic, concerns about operational risk had increased “somewhat” or “significantly” among 51% of CEOs, chief risk officers and directors responding to Bank Director’s 2020 Risk Survey, which was completed just before the pandemic. More than half also revealed heightened concerns around cybersecurity, credit and interest rate risk, and strategic risk.

That survey also found respondents indicating there was room for technology to improve their compliance with Bank Secrecy Act and anti-money laundering rules (76%), know your customer (50%) requirements, and vendor management requirements.

One way executives and risk managers can keep up is by incorporating risk technology to help sift through reams of data to derive actionable insights. These technologies can create a unified view of risk across exposure types and aggregation levels — product, business line, region — so executives can see how risk manifests within the bank. Some of these solutions can also capture and provide real-time information, supplementing slower traditional sources or replacing end-of-day reports.

But the pandemic led more than half of respondents to Bank Director’s 2020 Technology Survey to alter or adjust their technology roadmaps — including 82% of respondents at institutions with more than $10 billion in assets. Two-thirds said they would upgrade existing technology; just 16% planned to add technology to improve regulatory compliance.

Artificial intelligence holds a lot of promise in helping banks more efficiently and effectively comply with regulations and manage risk. Many banks are still early in their risk technology journeys, and are working to identify areas or situations that can be serviced or assisted by risk technologies. Forty-six percent of respondents to Bank Director’s Technology Survey say they are not utilizing AI yet.

Those that have are applying it to situations like fraud monitoring, which generates large amounts of data that the bank can correlate and act on, Mangaraj says. Others have applied it to process intelligence and process improvement, or used it to enhance the control environment. Key to the success of any AI or risk-technology endeavor is finding the right, measurable application where a bank can capture value for heightened risk or capabilities.

“We have a client who uses AI to monitor trader conversations that can proactively flag any compliance issues that may be coming up,” he says. “There are lots and lots of ways in which you can start using it. Key is identify cases, make sure you have clear measurement of value, monitor it and celebrate it. Success breeds success.”

The addition and incorporation of innovative risk technologies coincides with many banks’ digital transformations. While these changes can often complement each other, they can also make it difficult for a bank to manage and measure its risk, or could even introduce risk.

A strong management team, effective controls and active monitoring of the results are essential keys to a bank’s success with these technology endeavors, says James Watkins, senior managing director at the Isaac-Milstein Group. Watkins served at the FDIC for nearly 40 years as the senior deputy director of supervisory examinations, overseeing the agency’s risk management examination program.

“It’s time for a fresh look of the safeguards and controls that banks have in place — the internal controls and the reliability of the bank system’s and monitoring apparatuses. All of those are extremely important,” he says.

Bank executives and boards of directors must have the processes and procedures in place to ensure they’re using this technology and contextualizing its outcomes in a prudent manner.

“I think the importance of general contingency planning, crisis management strategies, thinking strategically — these are all areas that boards of directors and senior management really need to be attuned to and be prepared for,” Watkins says.

Enhancing Risk & Compliance

Financial institutions increasingly seek to use technology to efficiently and effectively mitigate risk and comply with regulations. Bank leaders will need the right solutions to meet these objectives, given the amount of data to make sense of as organizations include risk as part of their decision-making process. Microsoft’s Sandeep Mangaraj explains how banks should explore these issues with Emily McCormick, Bank Director’s vice president of research. They discuss:
  • How Risk Management is Evolving
  • Adopting AI Solutions
  • Planning for the Future

Four Digital Lessons from the Pandemic

2020, so far, is the year of digital interactions.

Without the ability to interact in the physical world, digital channels became the focal point of contact for everyone. Industries like retail and restaurants experienced a surge in the use of digital services like Instacart, DoorDash and others.

This trend is the same for banks and their customers. In a survey conducted by Aite Group, 63% of U.S. consumers log into financial accounts on a desktop or laptop computer to check accounts at least once a week, while 61% use a smartphone.

The coronavirus pandemic has certainly accelerated the move to the digital channel, as well. In a Fidelity National Information Services (FIS) survey, 45% of respondents report changing the way they interacted with their financial institution because of the pandemic. The increased adoption of the digital channel is here to stay: 30% of respondents from the same survey noting they plan to continue using online and mobile banking channels moving forward.

The same is true for payments. FIS finds that consumers are flocking to mobile wallets and contactless payment to minimize virus risks, with 45% reporting using a mobile wallet and 31% planning to continue using the payment method post-pandemic.

This pandemic-induced shift in consumer preferences provides a few important lessons:

1. Experience Matters
Customers’ experiences in other industries will inform what they come to expect from their bank. Marketing guru Warren Tomlin once said, “a person’s last experience is their new expectation.” No matter where it came from, a great digital experience sets the standard for all others.

Banks should look to other industries to see what solutions can offer a great customer experience in your online and mobile banking channels. Customers’ service experiences with companies like Amazon.com’s set the bar for how they expect to interact with you. Their experience making payments with tools from PayPal Holdings, like Venmo, may inform their impression of how to make payments through the bank.

2. Personalization is Key
Providing a personalized experience for customers is key to the success of your bank, both now and in the future. Your bank’s online and mobile tools must generate a personalized experience for each customer. This makes them feel valued and well served — regardless of whether they are inside a branch or transacting through a mobile app.

Technologies like artificial intelligence can learn each customer’s unique habits and anticipate specific needs they might have. In payments, this might look like learning bill pay habits and helping customers manage those funds wisely. AI can even make recommendations on how users can ensure they have enough funds to cover the month’s bills or save anything they have left over.

AI is also able to look at customer data and anticipate any services they might need next, like mortgages, car loans or saving accounts. It brings the personal banker experience to customers in the digital world.

3. Weave the Branch Into the Digital
The ability to interweave the personalized, in-branch experience into the digital world is crucial. There are positives and negatives in both the branch and digital channels. The challenge for banks is to take the best of both worlds and provide customers with an experience that shines.

Customers want to know that someone is looking out for them, whether they can see that person or not. A digital assistant keeps customers engaged with the bank and provides the peace of mind that, whether they are in the branch or 100 miles away, there is always someone looking out for their financial well-being.

4. Embrace the “Now” Normal
To state that the Covid-19 pandemic changed the world would be a big understatement. It has disrupted what we thought was “business as usual,” and irrevocably changed the future.

The “new normal” changes day by day, so much that we choose to more accurately refer to it as the “now normal.” The increased dependency on digital has made it critical to have the right infrastructure in place . You truly never know what is coming down the line.

Customers enjoy the ease of digital and, more than likely, will not go “back to normal” when it comes to banking and payments. Now, more than ever, is the time to examine the digital experiences that your bank offers to further ensure its prepared for this endless paradigm shift that is the “now normal.”

Reducing Contact Center Hold Times to Improve Service

The continuing coronavirus pandemic is pushing banks to think even more productively about how they can help their customers.

American workers are increasingly concerned about their ability to stay current on credit card and mortgage payments as workplaces continue to close and more jobs are lost amid Covid-19 uncertainty. What products and services can banks offer customers to offset their financial burden and address or alleviate their worries? Plainly, there’s never been a better opportunity for banks to focus on deepening their relationship with the customer.

Today’s bank looks a bit different than the bank of six months ago. Six months ago, customers willingly moved in and out of bank branches, offering many touch points with which the bank could engage with them and vice versa. Now, branch foot traffic is declining significantly, and the contact center has become the dominant human touchpoint.

The shift in demand means that some banks are struggling to efficiently answer basic customer service queries, let alone deal with unique and complex scenarios. Many institutions are offering the most basic customer experience at best. At worst, they are offering a terrible experience, with customers complaining of hold times lasting hours during Covid-19’s onset.

This is a problem for banks for many reasons. Customers don’t want to sit on hold for an extended period (if at all) for nearly anything, especially to get an answer to a simple question. And most of the questions are in fact simple. Our call driver data shows that approximately 70% of customer service queries are basic or transactional: routine requests for information and actions on an existing customer account. Not surprisingly, the most common requests are account access issues — typically a password reset or login confusion.

The next largest group, making up 25% of all requests, are complex. These are customer specific problems or special cases that require detailed attention and assistance to resolve. In these circumstances, the customer often has already attempted other digital methods of finding the answer before reaching for live help. These situations offer the opportunity to provide personal service with a warm human touch, cementing customer loyalty to the institution. This is where customer experience reputations are made and where customer service agents can really shine.

But customers with routine requests are forced to sit on hold when they don’t want to, and those with complex requests who need to speak with an agent can’t do so efficiently because agents are stuck servicing routine requests, according to our recent data report. Banks can solve this problem in two ways: they could hire more customer service agents to reduce wait times or they can automate certain functions using AI.

Handling transactional queries with a conversational chatbot offers the highest value to the customer and to the bank. Instead of hiring more agents, banks can free up the time of existing agents by offloading routine tasks. Contact center agents can focus on more complex or high-value problems, supporting more consumers with the same resources. A large bank reported that their AI chatbot halves the average handling time for customer inquiries, saving customers an average of 12 minutes per chat when handled by the bot.

To get started, banks shouldn’t look at conversational banking as a niche channel but as an important part of their overall customer experience strategy. Consumers no longer decide where to bank based on whether there’s a branch nearby. Banks need to look deeper, creating meaningful engagement with their customers. Excellent customer service is the baseline.

How One Bank Flattened Fraud

Argo.pngProtecting the bank and its customers — through cybersecurity measures, identity verification, fraud detection and the like — is vital in ensuring a financial institution’s safety and soundness, as well as its reputation in the marketplace. These investments typically represent significant cost centers, but fraud prevention tools can be an exception to the rule if they’re able to pay for themselves by preventing losses.

The idea is, when you put in a fraud system — and this is where some folks lose it — you want to make sure to catch more fraud than the system costs,” says Ronald Zimmerman, vice president in the operations department at $32.2 billion IBERIABANK Corp., based in Lafayette, Louisiana. “You always have to make sure that the cost doesn’t supersede your savings.”

Zimmerman implemented ARGO OASIS about a year ago. OASIS, which stands for Optimized Assessment of Suspicious Items, uses neural networks and image analytics to detect and prevent fraud. Modeled after the human brain, neural networks are a form of artificial intelligence designed to recognize patterns, making it well suited to identify check alterations, forgeries and other forms of transaction fraud. The solution then provides bank employees with detailed information to enable them to further investigate the activity.

Bank Director’s 2020 Risk Survey found that just 8% of executives and directors report that their bank uses AI technology to improve compliance. One-third are exploring these types of solutions.

IBERIA brought in OASIS to identify fraud in its “two-signature accounts” — customer accounts that require two signatures on a high-dollar check. “We have a queue set up in OASIS to monitor these checks as they come in through clearing. If a signature is missing or is in question, OASIS flags it for review,” Zimmerman says.

One thing about the technology that sets it apart is its check stock validation tool. “You have an overlay button where you can place a questioned check on top of a good check, and you have a little slide bar [so you] can see the small differences,” he says.

That tool alone has helped the bank stop roughly $300,000 in check fraud over the first eight months of use — meaning ARGO has already paid for itself. “We’ve caught a ton of fraud through this product,” says Zimmerman.

And $300,000 is a conservative estimate of the bank’s savings, Zimmerman says, because fraudsters have learned not to target his bank. “Check fraud flattened out, because the fraudsters have probably moved on, knowing that we’ve covered up a hole that was there before.”

ARGO OASIS was recognized as the Best Solution for Protecting the Bank at the 2020 Best of FinXTech Awards in May. ALTR, a blockchain-based security solution, and IDology, which uses big data for identity verification and fraud detection, were also finalists in the category.

Importantly, ARGO helps IBERIA stop fraud efficiently. A task that used to occupy three full-time employees’ time now takes two employees just a couple of hours.

IBERIA will soon merge with Memphis, Tennessee-based First Horizon National Corp. to form a $75 billion company. The deal was driven in part by the pursuit of scale.

Generating efficiencies is essential to better compete with big banks, said First Horizon CEO Bryan Jordan in a 2017 presentation. “We’ve got to be invested in technologies in such a way that we’re at or above table stakes,” he said. “The trick for us will be to … create efficiency in other parts of the business to create money that we can invest in leading-edge technologies and processes that really allow us to be competitive.”

Leveraging AI to reduce compliance busywork is a great place to start.

A Small Bank’s Big Bet on AI

Brex.pngBuilding a board with an appetite for innovation can be difficult, but the small group that oversees C3bank is decidedly different.

The institution was originally founded as a quiet community bank serving the Inland Empire region of southern California in 1981.

That same year, Evert “Chooch” Alsenz and Paul Becker, now board members at C3bank, formed an engineering partnership that would go on to fund the development of the world’s first quartz-based solid-state gyroscope, a patented technology used in brake systems for millions of automobiles. Subsequent ventures from the duo produced military communications antennas, lightning diversion strips and surge protection equipment for aircrafts.

Alsenz and Becker are no strangers to invention, a background they brought with them when they joined commercial real estate expert Michael Persall to buy C3bank in a deal that closed in 2014.

Alsenz and Becker’s shared history helps one understand how a four-branch, $356 million institution has been able to remake itself as a tech-savvy commercial bank. From the moment they acquired it, Persall, Alsenz and Becker, who also serve as principals for investment company ABP Capital, worked to transform the bank into an entrepreneurial shop with a specialty in commercial real estate lending. In 2019, the group moved the bank’s headquarters to Encinitas, California, where ABP is based, and changed its name to C3bank.

Understanding the entrepreneurial owners at C3bank also helps explain how the group was able to ink a new partnership to develop an artificial intelligence-based commercial lending tool just a few years after the change in ownership.

To strengthen the bank’s CRE lending program, bank chairman Persall approached technologist Shayne Skaff to develop a custom platform for assessing and monitoring CRE loans. Initially, Skaff wasn’t sold on the idea. When he dug deeper, though, he discovered that commercial lending technology was years behind the solutions for residential loans. That lag presented an opportunity, so he started working with the teams at ABP Capital and C3bank in June 2018 to build a solution that would eventually become known as Blooma.

Skaff brought developers into the institutions to learn about their respective underwriting processes. The goal for the project was to streamline the commercial underwriting process in a way that made it more dependent on science, than on art. Science, the parties believed — in this case, AI —  would lead to thorough, well-researched deals.

Our board and ownership group continues to think AI can have a big impact on banking,” says A.J. Moyer, the CEO of C3bank. “[They] push that thought process and believe a lot of underwriting can be supplemented.”

Traditionally, lenders spend a lot of time manually gathering the data that factors into a potential deal. Blooma allows banks to outsource that process to its AI engines. It taps into third party databases to extract information about local real estate markets and scours the web for other relevant information, such as neighborhood crime statistics and negative news.

Blooma then scores CRE deals on a 100-point scale that measures the probability that it will fit within the bank’s risk profile and portfolio needs. Users can drill down into the score to see exactly what factors influenced the score. As more deals pass through the system, Blooma’s AI gradually learns from the bank’s process to prioritize new opportunities.

The result? The process of onboarding and assessing a potential deal can shrink from weeks to minutes.

“[Q]uick yet accurate decision-making can be a strategic advantage for your institution,” says Moyer. “If I have a toolset that, when a potential deal comes my way, I can quickly confirm what that asset’s worth, [then] I can sign that deal faster than anyone else.”

In addition to the underwriting assist, Blooma provides a digital hub for managing deal documents and workflows. “We’ve gotten out of a spreadsheet environment,” says Moyer. “The world we’re in is more dynamic. Everyone can go [to Blooma] to see what deals we’re working on and what’s mission critical.”

Blooma was a finalist in the Best Business Solution category of this year’s Best of FinXTech Awards. Shield Compliance, a Seattle-based fintech helping institutions bank cannabis-related businesses, was also a finalist. The winner in this category was Brex, which partnered with Bank of the West to launch a small business-focused credit card that’s grown the bank’s revenue by more than 50% from clients using the co-branded card. You can learn more about that partnership here: How Innovative Banks Cards to Grow Revenue, Earn Loyalty.

Practical AI Considerations for Community Banks

A common misconception among many community bankers is that it isn’t necessary to evaluate (or re-evaluate for some) their use of artificial intelligence – especially in the current market climate.

In reality, these technologies absolutely need a closer look. While the Covid-19 crisis and Paycheck Protection Program difficulties put a recent spotlight on outdated financial technology, slow technology adoption is a long-standing issue that is exacerbating many concerning industry trends.

Over the last decade, community banks have faced massive disruption and consolidation — a progression that is likely to continue. It’s imperative that bank executives take a clear-eyed look at how advanced technologies such as AI can support their business objectives and make them more competitive, while gaining a better understanding of the requirements and risks at play.

Incorporating AI to Elevate Existing Business Processes
This may seem like a contrarian view, but banks do not need a specific, stand-alone AI strategy. The value of AI is its ability to improve upon existing structures and processes. Leadership teams need to be involved in the development process to identify opportunities where AI can tangibly drive business objectives, and manage expectations around the resources necessary to get the project up and running.

For example, community banks should review how AI can automate efficiencies into their existing compliance processes — particularly in the areas of anti-money laundering and Bank Secrecy Act compliance. This application of AI can free up manpower, reduces error rates and help banks make informed decisions while better serving their customers.

It’s necessary to have a strong link between a bank’s digital transformation program and AI program. When properly incorporated, AI helps community financial institutions better meet rising customer expectations and close the gap with large financial institutions that have heavily invested in their digital experiences.

Practical Steps for Incorporating AI
Once a bank decides the best path forward for implementing AI, there are a few technical and organizational steps to keep in mind:

Minimizing Technical Debt and “Dirty Data”: AI requires vast amounts of data to function. “Dirty data,” or information containing errors, is a real possibility. Additionally, developers regularly make trade-offs between speed and quality to keep projects moving, which can result in greater vulnerability to crashes. Managing these deficiencies, “or technical debt,” is crucial to the success of any AI solution. One way to minimize technical debt is to ensure that both the quantity and quality of data taken in by an AI system are carefully monitored. Organizations should also be highly intentional about the data they collect.More isn’t always better.

Minimizing technical debt and dirty data is also key to a smooth digital transformation process. Engineers can add value through new and competitive features rather than spending time and energy addressing errors — or worse, scrapping the existing infrastructure altogether.

Security & Risk Management: Security and risk management needs to be top-of-mind for community bankers any time they are looking to deploy new technologies, including leveraging AI. Most AI technologies are built by third-party vendors rather than in-house. Integrations can and likely will create vulnerabilities. To ensure security and risk management are built into your bank’s operating processes and remain of the highest priority, chief security officers should report directly to the CEO.

Managing risks that arise within AI systems is also crucial to avoid any interruptions. Effective risk management ties back to knowing exactly how and why changes affect the bank’s system. One common challenge is the accidental misuse of sensitive data or data being mistakenly revealed. Access to data should be tightly controlled by your organization.

Ongoing communication with employees is important since they are the front line when it comes to spotting potential issues. The root cause of any errors detected should be clearly tracked and understood so banks can make adjustments to the model and retrain the team as needed.

Resource Management: An O’Reilly Media survey from 2018 found that company culture was the leading impediment to AI adoption in the financial services sector. To address this, leaders should listen to and educate employees within each department as the company explores new applications. Having a robust change management program — not just for AI but for any digital transformation journey — is absolutely critical to success. Ongoing education around AI efforts will help garner support for future initiatives and empower employees to take a proactive role in the success of current projects.

At a glance, implementing AI technologies may seem daunting, but adopting a wait-and-see approach could prove detrimental — particularly for community banks. Smaller banks need to use every tool in their toolkit to survive in a consolidating market. AI poses a huge opportunity for community banks to become more innovative, competitive and prosperous.

AI: The Slingshot for Small Banks

Regional and community banks are struggling with growth and profitability in the face of competitive pressure from large national banks and fintech startups. Executives at these institutions are instructed to invest in technology, and to leverage data and artificial intelligence to compete more effectively.

While that sounds good, smaller banks are often constrained by a dependence on legacy core vendors that limits their IT potential, encounter difficulties in accessing their own data, lack skilled data scientists, and have no clear vision on where to start.

This conundrum came up during Bank Director’s 2020 Acquire or Be Acquired conference in Phoenix. I rubbed shoulders with fellow conference attendees over the course of three days, sharing ideas about the state of the banking sector and how community banks could leverage data and AI to drive business results. The talent gap was a frequent topic. Perhaps unsurprisingly, only a miniscule number of community banks have hired data scientists. The majority of banks have not prioritized data science capabilities; the few who are actively recruiting data scientists are struggling to attract the right talent.

But even if community banks could arm up with data scientists, what volume of data will they be working on to derive insights to fuel their business strategy? A $1 billion asset bank may have 50,000 to 75,000 customers — not a lot of data to start with. Furthermore, a number of bankers point to the difficulties they encounter in accessing their data in their legacy core systems.

As we were having these discussions, conversations were raging about the need for smaller banks to prepare for an existential threat. At the World Economic Forum in Davos, attendees were assessing comments from Bank of America Corp. Chairman and CEO Brian Moynihan that the bank could double its U.S. consumer market share. Back-of-envelope calculations indicate that if Bank of America manages to accomplish that growth, more than 1,000 community banks could be out of business. Can technology enable these banks to retain their core customer base, grow and avoid this fate? I think so.

One promising area of AI application for community banks is loan and deposit pricing. Community banks have little or no analytic tools beyond competitive rate surveys; most rely on anecdotal feedback from customers and front-line bankers. But price setting and execution on both assets and liabilities is one of the most important levers a bank can use to drive both growth and improve its net interest margin. Community banks should take advantage of new tools and data to level the playing field with the big banks, which are already well ahead of them in adopting price optimization technology.   

Small banks can gain the upper hand in this “David versus Goliath” scenario because accessible cloud-based technology works in their favor. True, big banks have worked with price optimization technology and leveraged large amounts of customer behavioral data for years. But community banks tend to have stronger customer relationships and often better pricing power than their larger competitors. Now is the time for community banks to take control of their destiny by adopting new technology and tools so they can better compete on price.

There are three reasons why cloud computing and the power of AI will be the slingshot of these ‘David’ banks:

  1. Scalable computing power, instantly on tap. Cloud-based computing and pre-configured pricing solutions are affordable and can be implemented in days, not months.
  2. Big data — as a service. Community banks can quickly leverage AI-based pricing models that have been trained on hundreds of millions of transactions. There is no need to build their own analytic models from a small customer footprint.
  3. Plug-and-play IT. It’s much easier today to integrate cloud-based platforms with a bank’s core system providers, which makes accessing their own data and implementing smarter pricing feasible.

Five years ago, it would have seemed crazy to think that in 2020, community banks would be applying AI to compete against the nation’s top banks. But the first wave of early adopters are already deploying AI for pricing. I predict we’ll see more institutions embracing AI and machine learning to improve their NIM and increase growth over the coming years.

Artificial Intelligence: Exploring What’s Possible

Banks are exploring artificial intelligence to bolster regulatory compliance processes and better understand customers. This technology promises to expand over the next several years, says Sultan Meghji, CEO of Neocova. As AI emerges, it’s vital that bank leaders explore its possibilities. He shares how banks should consider and move forward with these solutions. 

  • Common Uses of AI Today
  • Near-Term Perspective
  • Evaluating & Implementing Solutions