4 Keys Banks Need to Unlock Value From Artificial Intelligence

Banks of all sizes are tuning up their technology to better compete for customer loyalty by focusing on areas involving consumer interactions. But bank leaders need to understand that artificial intelligence, or AI, alone can’t revolutionize the customer experience.

In order for AI investments to elicit instant, human-like understanding and communication, banks must combine AI technology with:

  • Access to quality data.
  • Customer experience solutions that support responsiveness, natural interaction and context retention.
  • Security for enrollment, authentication and fraud detection — indispensable in the context of retail banking.

Data
Quality and Access
Data is the fuel driving AI-based experiences. That means the quality of the available data about the user for a specific use case and the ability to access this data in a real-time, secure fashion are mission-critical aspects of an AI investment.

Unsurprisingly, increasing the quality of data and providing seamless, secure access to this data has been a challenge that banks have grappled with for years.

But institutions must overcome these data utilization hurdles in order to offer an AI-based experience that is better than mediocre. The best outcome? Users will no longer suffer through disjointed experiences or delayed satisfaction caused by siloed data, multiple data connection hops and antiquated back ends that haven’t been modernized to today’s standard.

Collection and Understanding
Big data — the collection of very large data sets that can be analyzed computationally to reveal patterns, trends and associations — goes hand-in-hand with AI. When it comes to consumer banking, an AI solution for banks should store all customer interaction information, from words used to communicate with the bot to actions taken by the user, so it can be analyzed and applied in future interactions. To do this, banks need to adopt AI technology that integrates a learning loop that’s always running in the background.

As data accumulates, AI-powered bots should get smarter over time. Behavioral, transaction and preference information enables banks to create personalized experiences that elevates customer experience to the next level. J.D. Power’s 2022 U.S. Retail Banking Satisfaction Study found that 78% of respondents would continue using their bank if they received personalized support, but just 44% of banks are actually delivering it.

Without the right data, there’s no intelligence to inform interactions.

Customer Experience
If someone asked, “What’s your name?” and it took you 8 seconds to respond, the conversation would seem unnatural and disjointed. Similarly, AI technology requires real-time responsiveness to live up to its human-like image. Additionally, bank customers expect to be able to seamlessly transition between interaction channels without having to rehash their issue each time they get transferred, change interaction channels or follow up. Banks can only achieve this omnichannel customer experience that incorporates customer interaction information across channels with customer experience technology that integrates AI.

Consumers now rank omnichannel consistency as the most important dimension of customer experience, according to a 2021 Harris poll, up from No. 2 in 2019. In a Redpoint Global research study, 88% of respondents said that a bank should have seamless, relevant and timely communications across all channels; less than half (45%) reported that their bank effectively achieved this objective. An omnichannel customer experience is foundational for AI.

Security
As powerful as artificial intelligence can be as a competitive advantage in banking, lack of strong security measures is a nonstarter. In the latest The Economist Intelligence Unit Survey, bankers identified privacy and security concerns as the most prominent barrier to adopting and incorporating AI technologies in their organization. Thankfully, ironclad AI is within reach.

While AI capability is great, its usability is limited if its security is not up to par. An AI bot can go far beyond answering your customers’ basic questions if bank transactions are authenticated and secure; it can perform tasks such as retrieving account balances, listing and searching transactions, making payments, transferring funds and more. Imagine the impact that a friendly and reliable virtual teller, available 24/7, could have on your institution.

Four in five senior banking executives agree that unlocking value from artificial intelligence will distinguish outperformers from underperformers. To access its value, a bank’s customer-facing system must be supported by four pillars: AI understanding, quality data, omnichannel customer experience technology and security.

When technology budgets are tight, bank leaders must invest wisely; not all AI solutions are created equal. Chasing the new shiny thing can waste dollars if bank decision makers don’t have a handle on the scope of what their institution needs. Knowing which pieces of the puzzle will complete the picture is a competitive differentiator. Now, your bank can unlock the value of AI and win.

Giving Customers Choice, Access With Investments

It’s time for community financial institutions to significantly upgrade their investment resources to service their clients. Retail investors want to be more educated about investing opportunities and have greater access to investment tools; in response, investment-as-a-service companies are building platforms so banks can give their clients more of what they want.

One problem with financial and investment innovation today is that there is either too much focus on gimmicks or not enough focus on innovation. Crypto-only investment companies indiscriminately pitch every token as the latest and greatest get-rich-quick scheme. Gamified investment apps promote risky options trades to retail investors, turning investing into a lottery or casino and distracting users from what investing should be: a powerful tool to maintain, protect and build wealth. Further, legacy investment institutions often make the bulk of their revenue from customers who are already wealthy via older products, with little incentive to experiment with creative new offerings.

In this unhappy mix, it is investors with the most to gain from a long-term investing strategy — younger less affluent or not yet rich investors — who lose the most. Unable to access wealth management and investing services from their trusted financial institution, they seek out third-party investment apps that don’t prioritize their long-term success and happy retirement. For community financial institutions, this interrupts the chain of familial wealth transfer and risks their next generation of customers.

Investors desire a unified platform that offers access to a growing list of investments, ranging from physical metals to AI-driven investment models to crypto-assets to collectibles. A self-directed platform is key: Investors should be given a choice to pursue the investment strategy they feel fits best for their unique investment interests and risk profile. The platform should include all the tools they need to effortlessly pursue the “Get rich slowly” strategy: passive investing and dollar-cost averaging into a low-cost, highly diversified portfolio.

Cloud computing innovations and numerous rounds of fintech venture capital have made it possible for companies to build curated investment platforms that traditional banks can easily add and implement. Investment tools driven by application program interfaces, or APIs, allow financial services to embrace change in collaborative ways that don’t conflict with existing business, yet still appeal to the ever-changing preferences of investors.

Investing is not one-size-fits-all. Wine fans may want to invest in a portfolio of wine assets to hold or eventually redeem. Investors who collected baseball cards as a kid may now have the capital to buy collectibles with significance to them as culturally relevant assets. Individuals also may want to invest in thematic categories, like semiconductors — the foundation for all computing, from electric vehicles to computers to smartphones. These investments are not optimal for everyone, but they don’t have to be for everyone. What matters most is access.

Too many banking platforms do not take full advantage of the full range of investment tools available in the marketplace, even though their clients are looking for these. Lack of access leads to painful experiences for the average investor who wants to be both intelligent with their money and allowed to experiment and explore the ever-changing world of digitally available investment categories. Give customers a choice to pursue wealth-building strategies based on their unique insights and instincts, and made available through their existing bank.

Unlocking Banking as a Service for Business Customers

Banking as a service, or BaaS, has become one of the most important strategic imperatives for chief executives across all industries, including banking, technology, manufacturing and retail.

Retail and business customers want integrated experiences in their daily lives, including seamlessly embedded financial experiences into everyday experiences. Paying for a rideshare from an app, financing home improvements when accepting a contractor quote, funding supplier invoices via an accounting package and offering cash management services to fintechs — these are just some examples of how BaaS enables any business to develop new and exciting propositions to customers, with the relevant financial services embedded into the process. The market for embedded finance is expected to reach $7 trillion by 2030, according to the Next-Gen Commercial Banking Tracker, a PYMNTS and FISPAN collaboration. Banks that act fast and secure priority customer context will experience the greatest upside.

Both banks and potential BaaS distributors, such as technology companies, should be looking for ways to capitalize on BaaS opportunities for small and medium-sized enterprises and businesses (SMEs). According to research from Accenture, 25% of all SME banking revenue is projected to shift to embedded channels by 2025. SME customers are looking for integrated financial experiences within relevant points of context.

SMEs need a more convenient, transparent method to apply for a loan, given that business owners are often discouraged from exploring financing opportunities. In 2021, 35% of SMEs in the United States needed financing but did not apply for a loan according to the 2022 Report on Employer Firms Based on the Small Business Credit Survey. According to the Fed, SMEs shied away from traditional lending due to the difficult application process, long waits for credit decisions, high interest rates and unfavorable repayment terms, and instead used personal funds, cut staff, reduced hours, and downsized operations.

And while there is unmet demand from SMEs, there is also excess supply. Over the last few years, the loan-to-deposit ratio at U.S. banks fell from 80% to 63%, the Federal Reserve wrote in August 2021. Banks need loan growth to drive profits. Embedding financial services for SME lending is not only important for retaining and growing customer relationships, but also critical to growing and diversifying loan portfolios. The time for banks to act is now, given the current inflection point: BaaS for SMEs is projected to see four-times growth compared to retail and corporate BaaS, according to Finastra’s Banking as a Service: Global Outlook 2022 report.

How to Succeed in Banking as a Service for SMEs
There are three key steps that any institution must take to succeed in BaaS: Understand what use cases will deliver the most value to their customers, select monetization models that deliver capabilities and enable profits and be clear on what is required to take a BaaS solution to market, including partnerships that accelerate delivery.

BaaS providers and distributors should focus on the right use case in their market. Banks and technology companies can drive customer value by embedding loan and credit offers on business management platforms. Customers will benefit from the increased convenience, better terms and shorter application times because the digitized process automates data entry. Banks can acquire customers outside their traditional footprint and reduce both operational costs and risks by accessing financial data. And technology companies can gain a competitive advantage by adding new features valued by their customers.

To enable the right use case, both distributors and providers must also select the right partners — those with the best capabilities that drive value to their customers. For example, a recent collaboration between Finastra and Microsoft allows businesses that use Microsoft Dynamics to access financing offers on the platform.

Banks will also want to focus on white labeling front‑to-back customer journeys and securing access to a marketplace. In BaaS, a marketplace model increases competition and benefits for all providers. Providers should focus on sector‑specific products and services, enhancing data and analytics to enable better risk decisions and specialized digital solutions.

But one thing is clear: Going forward, embedded finance will be a significant opportunity for banks that embrace it.

Does Your Bank Struggle With Analysis Paralysis?

The challenge facing most community financial institutions is not a lack of data.

Institutions send millions of data points through extensive networks and applications to process, transmit and maintain daily operations. But simply having an abundance of data available does not automatically correlate actionable, valuable insights. Often, this inundation of data is the first obstacle that hinders — rather than helps — bankers make smarter decisions and more optimal choices, leading to analysis paralysis.

What is analysis paralysis? Analysis paralysis is the inability of a firm to effectively monetize data or information in a meaningful way that results in action.

The true value is not in having an abundance of data, but the ability to easily turn this cache into actionable insights that drive an institution’s ability to serve its community, streamline operations and ultimately compete with larger institutions and non-bank competitors.

The first step in combatting analysis paralysis is maintaining a single source of truth under a centralized data strategy. Far too often, different departments within the same bank produce conflicting reports with conflicting results — despite relying on the “same” input and data sources. This is a problem for several reasons; most significantly, it limits a banker’s ability to make critical decisions. Establishing a common data repository and defining the data structure and flow with an agreed-upon lexicon is critical to positioning the bank for future success.

The second step is to increase the trust, reliability, and availability of your data. We are all familiar with the saying “Garbage in, garbage out.” This applies to data. Data that is not normalized and is not agreed-upon from an organizational perspective will create issues. If your institution is not scrubbing collected data to make sure it is complete, accurate and, most importantly, useful, it is wasting valuable company resources.

Generally, bad data is considered data that is inaccurate, incomplete, non-conforming, duplicative or the result of poor data input. But this isn’t the complete picture. For example, data that is aggregated or siloed in a way that makes it inaccessible or unusable is also bad data. Likewise, data that fails to garner any meaning or insight into business practices, or is not available in a timely manner, is bad data.

Increasing the access to and availability of data will help banks unlock its benefits. Hidden data is the same as having no data at all.

The last step is to align the bank’s data strategy with its business strategy. Data strategy corresponds with how bank executives will measure and monitor the success of the institution. Good data strategy, paired with business strategy, translates into strong decision-making. Executives that understand the right data to collect, and anticipate future expectations to access and aggregate data in a meaningful way is paramount to achieving enduring success in this “big data” era. For example, the success of an initiative that takes advantage of artificial intelligence (AI) and predictive capabilities is contingent upon aligning a bank’s data strategy with its business strategy.

When an organization has access to critical consumer information or insights into market tendencies, it is equipped to make decisions that increase revenue, market share and operational efficiencies. Meaningful data that is presented in a timely and easy-to-digest manner and aligns with the company’s strategy and measurables allows executives to react quickly to changes affecting the organization — rather than waiting until the end of the quarter or the next strategic planning meeting before taking action.

At the end of the day, every institution’s data can tell a very unique story. Do you know what story your data tells about the bank? What does the data say about the future? Banks that are paralyzed by data lose the ability to guide their story, becoming much more reactive than proactive. Ultimately, they may miss out on opportunities that propel the bank forward and position it for future success. Eliminating the paralysis from the analysis ensures data is driving the strategy, and enables banks to guide their story in positive direction.

Recapturing the Data That Creates Valuable Customer Interactions

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

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

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

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

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

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

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

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

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

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

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

The Future of Banks: Platforms or Pipes?


future-banking-11-9-16.pngMuch has been written about the future of banking. In the end, it all seems to come down to one question: Will banks become platforms or pipes?

In reality, there’s no question at all. Platforms are the winning business model of the 21st century and the banking industry is well aware. In fact, banks have been platforms for decades—fintech companies are merely creating the latest set of bank platform extensions. Earlier incarnations include ATMs and online bill pay for consumers.

That said, what’s happening today is forcing banks to rethink how fast they extend their platform to avoid becoming just the pipes. The advent of the cloud and the software revolution in fintech with billions of capital being invested every quarter has brought more innovation to banking in the past two years than it has seen in the past 20. Still, the current David taking down Goliath narrative surrounding the future of banking and finance ultimately fails to account for the reality of the situation.

While it often goes unnoticed, a great many fintech startups today rely heavily on banks to enable their innovative services. The success of financial innovations like Apple Pay for instance is happening with a great deal of participation and cooperation between technology companies and financial institutions.

This relationship between banks and fintech underscores the reality of the financial services industry’s future. Yes, finance is evolving alongside the accelerating curve of technology, and yes, fintech is driving much of this change, but banks are—and will remain—squarely at the center of the financial universe for quite some time to come.

Why is this? For one, banks have been the backbone of the modern economy since its inception. They are far too ingrained in the financial system to be removed within any foreseeable time frame. Banks also have deep pockets, infrastructure and experience. Large market caps and long track records are clear signals to customers that banks can weather the inevitable downturn. Startups, on the other hand, are more susceptible to turbulence and market volatility—things banking customers, especially business customers, would rather avoid.

Big data is yet another boon to banks’ staying power. Banks have been collecting data on customer transactions and behavior for decades. This creates major advantages for banks. When used in the right way, this data can be leveraged to do things like identify customers that are ripe for new payment services or to mitigate and underwrite risk in innovative ways.

But despite all this, there is one hazard currently menacing banks: disintermediation. Starting with the ATM, technology has been distancing consumers from banks for quite some time. Today, their relationship with the consumer is slimmer than ever.

Meanwhile, fintech is picking up the slack. While traditional banking experiences can feel clunky, fintech products and services are designed to work with people’s lives and deliver value in new and unexpected ways. These upstarts pride themselves on delivering superior customer experiences—banking that is intuitive, mobile, cloud-based, responsive, available 24/7, you name it.

Fintech companies are also agile and built for rapid iteration—skill sets banks don’t yet have internally. This allows fintech companies to focus heavily on usability and keeping their user interfaces modern. At Bill.com, for instance, we upgrade our onboarding experience every two weeks. By comparison, most banks have outsourced many key functions to third-party service providers like Fiserv and Jack Henry, severely limiting their ability to make product changes outside of rigid, long-term release cycles.

The comparative lack of innovation by banks is no surprise. For decades, banks have spent most of their resources driving to meet quarterly earnings targets, delivering consistent results and ensuring compliance—the key objectives most highly-regulated, publicly-traded financial institutions must focus on to meet obligations to shareholders. That leaves fewer resources and funds for experimentation, learning and new product development. This makes it difficult for banks to keep up with shifts in customer preferences and behavior the way that fintech can. Banks know this and it is exactly why they are starting to shift their strategies to reflect being a platform and not just the pipes.

When banks become platforms for their customers and fintech partners, they increase the value of what they have built over the past several decades and disintermediation on the consumer front becomes irrelevant. Instead, as banks fuse their platforms with fintech, innovation will accelerate, creating tremendous value for everyone in the food chain.