Giving Customers Choice, Access With Investments

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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.

Rise of the Quantum Machines

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A new technological revolution on the horizon is poised to disrupt the financial services industry: Quantum Computing.

While broad commercial applications of quantum technologies are likely several years away, experts predict that practical applications of quantum computing in the banking industry may only be three to five years away. Various industry leaders at Goldman Sachs Group and JPMorgan Chase & Co. have already begun experimenting with quantum computing and are preparing for the inevitable “quantum supremacy.”

What is Quantum Computing?
IBM defines quantum computing as a “rapidly emerging technology that harnesses the laws of quantum mechanics to solve problems too complex for classical computers.” Classical computers operate on a binary system, processing “bits” of information as either zeros or ones. In contrast, quantum systems process quantum bits or “qubits” of information as either zeros, ones, a combination of zeros and ones, or any value in between. As a result, the processing power of quantum systems will be well beyond what a binary system could ever process.

However, because quantum computing relies on the laws of quantum mechanics, the answers produced by quantum calculations will be probabilistic instead of determinative. Binary systems operate by processing a limited data set via specific processing instructions to deliver a singular answer. In contrast, quantum systems operate by processing multiple units of data, resulting in a narrowed range of possible answers instead of a singular answer. Practically speaking, this means that teams must run calculations through quantum systems multiple times to narrow the universe of possible answer to a functional range.

While results from quantum systems may sound less reliable, it ultimately depends on their use. In many cases, binary systems will be better and never need to be replaced by quantum systems. However, quantum computing will be revolutionary when it comes to eliminating certain possibility ranges associated with incredibly complex problems.

What is Quantum Supremacy?
“Quantum supremacy” sounds ominous, but it simply refers to the point in time where quantum systems can perform calculations beyond the scope of classical computers in a reasonable amount of time. Although developments in quantum computing are promising, quantum supremacy is not likely to occur until the end of this decade. One of the challenges is assembling a single quantum system with the requisite qubits that outperforms a classical, binary computer. Some companies have almost achieved this, but developers have yet to develop a reasonably sized quantum system for commercial applications. So while quantum supremacy is currently only theoretical, it is not so far off in the future.

Benefits and Risks of Quantum Computing
Quantum computing gives early adopters a competitive advantage. Insights gleaned from quantum computing can help banks make better decisions, reduce risk, increase profits and provide better customer service. An IBM report identified a few use cases that are likely to improve financial services:

  • Targeting and Prediction: According to an IBM report, 25% of small to medium sized banks lose customers because their offerings don’t target the right customer. Quantum computing can help financial institutions break down their complex data structures to develop better predictive models that offer products and tailored services more effectively to customers.
  • Trading Optimization: Equity, derivative, and foreign exchange markets are complex environments, and trading activities are growing exponentially. The complex and fast-paced nature of these markets require exceptionally fast models to help investment managers optimize customer portfolios. Quantum computing can help give investment managers the tools necessary to deliver better services to customers, such as improving portfolio diversification or rebalancing portfolio investments to meet a customer’s investment goals.

Although the benefits of quantum computing are numerous, they do not come without risks. In particular, quantum computing poses a serious threat to cybersecurity controls. Encryption techniques used to secure accounts and networks are immediately at risk upon quantum supremacy. Currently, banks use complex encryption algorithms to secure user accounts, transactions and communications. Breaking through current encryption algorithms is virtually impossible and highly impractical. However, threat actors leveraging quantum technologies have the potential power to break through these classical encryption methods. Although this threat is currently only theoretical, leaders in quantum computing are already working on quantum cryptography to get ahead of this potential cybersecurity threat.

How to Prepare for Quantum Supremacy?
While broad adoption of quantum systems and products is unlikely until later this decade, banks can anticipate quantum products and solutions emerging in the next few years. In anticipation of this quantum revolution, financial institutions should:

  • Start Talking About Quantum Computing: Financial institutions should begin preparing to implement and leverage these technologies immediately given that product breakthroughs are likely within the next five years. Financial institutions should also consider potential partnerships with leaders in quantum computing such as IBM, Microsoft, and others. The sooner financial institution boards and executives can put a quantum strategy in place, the better.
  • Start Talking About Quantum Encryption: Financial institutions with significant data repositories should begin thinking about the cybersecurity risks associated with quantum computing. Chief information security officers should begin thinking about how their institution will safely transition their data repositories from classical encryption to quantum encryption in the near future.

Does Your Bank Struggle With Analysis Paralysis?

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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

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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.

AI: The Slingshot for Small Banks

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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.

Sizing Up Amazon Web Services

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cloud-4-17-18.pngFintech is prominent in today’s business lexicon, having migrated from the back office to a prominent position in both consumer and commercial finance. Its core functionality on mobile devices and wide application in artificial intelligence (AI) spans blockchain, smart contracts, banking, insurance, regulation and cybersecurity. And Amazon Web Services (AWS), a major cloud player, is the go-to provider for small and mid-sized businesses.

AWS delivers internet-based, on-demand computing, servers, storage, remote computing, mobile development and security, and a host of other information technology (IT) resources, all on a pay-as-you-go basis. Companies can gain unfettered, rapid access to low-cost, flexible services, with no up-front investment in hardware, software consulting and design, or expensive-to-maintain data centers. Companies can operate faster, more securely and less expensively, preserving their most valuable resources: time and money. And it is user-friendly—the AWS Management Console is simple, intuitive and accessible on the web or through the AWS Console mobile app. Wide adoption means lower costs from economies of scale.

AWS has mushroomed since its introduction a decade ago—posting $5.1 billion in revenue for fourth quarter 2017 and a 44.6 percent increase in year-over-year sales. AWS’ business model enables financial services firms and banks to scale up and down with increasing speed and agility. They can target new market segments, such as millennials—the fastest-growing consumer base—instantly, and easily offer an uncomplicated, compelling and accessible banking experience, appealing to a broad range of customers anywhere in the world.

Users’ traditional security concerns are assuaged with the AWS infrastructure, which aligns with best security practices, including SOC 1 and SOC 2 assurances. Third-party attestations and helpful white papers are available at its AWS Security Center at aws.amazon.com. AWS’ reliable development environment supports establishing a firewall via separate accounts for development and production. Thus, companies can try new features, conduct product experiments and perform user acceptance testing (UAT) without compromising the integrity of existing applications or disrupting active operations.

Although AWS offers quick, easy and simple solutions, users need assurance of adequate controls to protect the underlying database. Company decision makers must clarify who controls the data and how security is managed before migrating their data. Minimum precautionary measures include encrypting data, limiting the amount of data stored and insisting on multifactor authentication. Data ownership is a murky issue with AWS, and companies’ data could be mined to gain a competitive advantage.

AWS fintech customers should understand that segregation of duties is paramount. Oftentimes, small organizations have a chief technology officer who is also responsible for development, design and support. These multiple duties can create a control issue. Additionally, fintech companies may not have clearly defined production schedules, so they often make changes during the day. Segregating the production from the development environment mitigates the risk of unauthorized changes.

The overarching issue of regulation is major. The Financial Stability Board, an international body that monitors the global financial system, highlights 10 issues that supervisors and regulators must heed, and three have top priority. First is an oversight structure to govern third-party service providers, including cloud computing and data services. Second is mitigating cyber risks by maintaining contingency plans for cyberattacks and focusing on cybersecurity when designing IT systems. Third is monitoring macro financial risks against undue concentration and large and unstable funding flows.

These top issues have particular application to fintech, where traditional risk management functions may not suffice. Blockchain and robotics technologies demand a risk management framework that examines underlying assumptions, revises risk tolerance levels and acceptable risks, and increases stress testing and simulations.

AWS has earned a solid reputation in the marketplace—it is more than 10 times the size of its nearest competitor—and its prominence will increase. Small and medium-sized businesses have championed its ease of use, cost savings and scalability. However, they must protect data and avert potential operational risk.

Six Best Practices to Help Customers Achieve True Data Privacy

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data-7-24-17.pngWith today’s constant news stream of ransomware threats, denial of service attacks and data breaches, data privacy is more of a concern than ever. But, what exactly do we mean by data privacy, and how can we convey its importance to customers?

At its root, data privacy is the concept of implementing appropriate controls related to the sensitivity of data. There are two key components of data privacy: data classification and data protection.

Data classification simply means understanding the sensitivity level of data. There are three main categories: public, sensitive and confidential. Any data, even that which is publically available, can be collected and used by a criminal to profile their prey. The numbers tell the story: Through July 6, 2017, according to the nonprofit Identify Theft Resource Center, we’ve seen a total of 791 breaches and 12.39 million compromised records across all major industries.

Data classification helps determine the level of protection warranted, with confidential data justifying the most:

  • Confidential data, such as social security numbers, bank details, or other personally identifiable information—whether in transmission or storage—should be encrypted, and devices used to store and transmit it should be secured as well. When disposing of this data, whether electronically or in a tangible format, the data records should be fully destroyed through shredding (electronic or physically). In some cases, entire storage devices should be destroyed.
  • Sensitive data, such as religious or relationship information, or private business plans, is similar to confidential data in that the owner does not wish to share it with others. As such, sensitive data often is protected similarly to confidential data. The only differentiator is the amount spent to protect it.
  • Public data is that which is publically available, like where a person attended high school.

With greater access to information, coupled with the increased rate and publicity of compromise, many consumers are numb to the severity of a data breach, even though strengthening the environments in which they store or transmit data should be top of mind.

Below are six best practices you can convey to your customers to help them achieve real data privacy:

  • Employ data encryption for both storage and transmission. One advantage of encrypting all data is that a decision doesn’t have to be made regarding classification when it comes to encryption. A second benefit is that a criminal doesn’t know what to target when all data is encrypted.
  • Avoid accessing data such as emails, cloud storage, and the like on a public computer or network, which are easily compromised. If a public network must be used, virtual private network (VPN) encryption is necessary when sensitive or confidential data is being accessed. Keep in mind, passwords aren’t always transmitted in an encrypted format, so a criminal could intercept the password. Public computers should be used only as a last resort, and never to access confidential or sensitive data.
  • Ensure your computer is patched and protected with a firewall and up-to-date anti-malware solution. Further, even careful users should periodically have their machine inspected for malware and cleaned by a trusted technician; with the sophistication of malware today, even the most cautious and educated can still end up compromised.
  • When possible, implement multi-factor authentication, which entails using more than one means of authentication, such as passwords and authentication codes. This is one of the most promising ways to ensure data and accounts remain secure, yet even these systems aren’t foolproof. Avoid receiving texts of access codes when possible, as this is a weaker form of multi-factor authentication. Use authentication applications, phone calls or a secure email account instead, and remember that codes sent to a device are only as secure as the device itself.
  • Use strong passwords that are changed at least every 90 days. Passwords should, when allowed, be at least 15 characters in length and complex in nature, including letters, numbers and symbols. Also, password safes like KeyPass are useful for storing them. And remember, treat your password like your toothbrush: never share it and change it often.
  • Consider the sensitivity of the data you store in the cloud. Utilizing a cloud service means entrusting a company to protect your data, so ensure the provider is equipped to protect the data to the same degree that you would. Another alternative is encrypting the data with your own encryption key before storing it in the cloud, which helps mitigate risk.

While one of banks’ most important tasks is protecting customer data, educating customers to respond in kind goes a long way toward a common goal.

Banking on the Cloud: Why Banks Should Embrace Cloud Technology

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Cloud adoption has reached critical mass, with roughly 90 percent of businesses employing its technology in some facet of their organization. The cloud presents opportunities for enhanced efficiencies and flexibility—without any security trade-offs—so it’s no surprise that we’re seeing more organizations shift to the software as a service (SaaS) model. But while we’ve seen the healthcare, legal and insurance industries evolve, banks have been more reluctant to adopt new technologies built outside of their own walls.

Why Banks Lag at Cloud Adoption
The banking industry is not known for being nimble. As one of the oldest, largest and most vital industries in the U.S. economy, banking has, in some ways, fallen victim to inertia—relying on traditional technologies and internal networks to disseminate its services. This is in large part due to the widely-held belief that on-premise solutions are inherently more secure than the cloud because data lives in proprietary servers and systems, rather than a service provider’s environment. However, research shows that cyber attacks affect both environments, with on-premise users experiencing over twice as many web application attacks as service provider customers, on average.

Still, for many banks, the perceived risks of the cloud outweigh its forecasted benefits. In fact, 73 percent identified security concerns as the main reason for avoiding it, while 63 percent listed privacy issues as their top worry. That perception is beginning to change, as the cloud’s business advantages have become too significant to ignore. A recent study found big banks are expected to grow from as little as zero percent public cloud adoption to 30 percent by 2019—a dizzying adoption rate for an industry that still relies on legacy systems from the 1960s.

For those still wary of making the switch, here are three of the biggest benefits of moving to the cloud:

Security
Cloud technologies boost your security in ways that on-premise systems are unable to. Traditionally, to use a new offering, you install an on-premise server in your datacenter. Then you must configure network, firewall and secure access to the server. This stretches resources by increasing training requirements, which ultimately detracts from the goal of the offering. Due to economies of scale, cloud companies can own the server, the networks and the processes making the entire offering more complete and secure.

With strict protocols and security certifications like SOC2 and ISO27001 built into many services, banks can ensure that the cloud is accessed and enabled securely for any solution provider they work with.

Understanding the value of security and the benefits that cloud technology brings to banks, a handful of institutions are leading the shift and others are expected to follow. Capital One Financial Corp., an early adopter of Amazon Web Services (AWS), has steadily built its infrastructure in the cloud over the past two years. The company continues to work closely with AWS on specific security and data protocols, allowing the company to operate more securely in the public cloud than it could have in its own data centers, according to Capital One CIO Rob Alexander.

Efficiency and Scalability
The cloud enables teams to be more agile than ever. The SaaS model gives teams the ability to be flexible and enable new interations on-demand. This access to real-time commentary empowers teams to ship updates more quickly and frequently and to push the envelope so they’re constantly improving products to align with what customers are looking for.

By leveraging the cloud to store complex data, organizations can meet ever-evolving regulatory compliance and governance rules mandating data protection. A recent example would be financial institutions working to comply with the EU’s General Data Protection Regulation. The ability to meet regulations can be sped up by a number of the cloud’s features, including built-in auditability for more clarity around your compliance status, and virtual infrastructure that reduces room for error.

On top of addressing infrastructure models, the cloud allows businesses to be elastic. For instance, being able to address the mass amount of credit card purchases on Cyber Monday and expand for that specific demand, rather than having to buy new servers to address the one day-per-year demand.

Overhead Cost Savings
Switching from on-premise to cloud can mean significant savings on overhead costs.

When you work with a SaaS provider, you no longer need to invest in proprietary infrastructure. Instead, you’re able to access and maintain your data through your partner’s established environment. This cuts down on both the up-front capital costs associated with hardware and the continuous costs that eat up budget to keep hardware and software optimized and refreshed.

Rather than pay a flat fee to keep systems up and running, cloud providers offer a variety of metered, pay-per-use options. These include Salesforce and Microsoft Office 365’s pay-per-seat, AWS’ infrastructure as a service (IAAS) pay-per-hour model, and Oracle’s high integration fees.

By outsourcing services to the data center, you can also realize savings on staffing. On-premise technologies can require a team varying in size from one to dozens, depending on the bank’s size. Because your cloud provider takes on the computing, your internal team no longer has to worry about hardware refreshes or server and software updates, freeing up their time to focus on what matters most: your business. Cost savings can also be reinvested into the business to increase headcount, boost wages and drive product innovation.

Cloud technology has already been embraced by businesses in numerous industries, but banks have been slower to acknowledge its benefits. Now, as cloud’s positive impact on security, efficiency and cost come to the forefront, it’s becoming harder for banks to ignore the advantages. Already, we’re seeing early adopters reap the benefits, from a financial standpoint and innovation perspective, and in the coming years, we can expect to see banking in the cloud transition from a “nice-to-have” to a business-critical approach to moving up in the market.

How to Pick the Right Digital Small Business Lending Tool: Top 10 Must Have Characteristics

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lending-4-24-17.pngHaving access to online lending applications has quickly transitioned from a customer convenience to a customer expectation. It’s only a matter of time before all institutions will be providing digital access to small business lending. That much is certain. What isn’t certain is how to find the right fintech partner. Your partner should understand your institution’s lending processes and digital strategy in that space, and provide you with a solution that meets your unique objectives.

Here are the top 10 characteristics you should demand from any digital business lending partner.

1. Friend Not a Foe Business Model
It’s obvious, I know, but find a partner who is not a competitor of yours. There are business lending fintech companies that once had designs on putting banks and credit union lending departments out of business. If the businesses you serve can also go to your partner’s website and apply directly with them for a loan, they’re not a partner. They are a competitor.

2. Timely End-to-End Functionality
Current business lending processes are onerous for both the client and the bank. Applications are submitted incompletely 60 percent of the time, and data is bounced from one party to another and back again. Technology does an amazing job of doing things right the first time every time. The value in your business lending tool resides in its ability to help facilitate everything from the application to closing the loan.

3. Endorsed by a Trusted Source
Most of the financial services industry’s trusted resources and trade associations provide their members with a list of solutions for which they have completed comprehensive due diligence and identified as an endorsed solution. Entities, like the American Bankers Association, Consumer Bankers Association and others, have the resources to conduct due diligence on the companies they recommend. Leverage their expertise.

4. Control…Control…Control
The institution must be able to retain control over every aspect of the process. Your clients should never even know the tech partner exists. The brand, the credit policy, pricing, scoring, decisions, and all aspects of the customer relationship must be fully owned and controlled by the institution.

5. Customer Experience
Find a tech partner that shares your philosophy of putting the borrower at the center of the process. Look for a tool that creates an engaging, simple, and even fun environment for the application portion of the process, and results in a speedier, more efficient and convenient end-to-end process.

6. Enhances Productivity
Find tech that frees up your sales staff to sell, and allows your back office to spend minutes—not hours—making a decision on a business loan. Sales teams should spend their time growing relationships and sourcing new deals as opposed to shepherding deals through the process or chasing documentation. With the right tool, back office can analyze deals quickly and spend more time on second look processes or inspecting larger deals.

7. Builds the Loan Portfolio
Find a tech solution so good that it will draw new opportunities into your shop—even those folks who would never think about walking into a branch. And make sure the application process can accommodate both the borrower who is online and independent, as well as the borrower who wants to sit next to a banker and complete the application together.

8. The Human Touch
The most important relationship is the one between banker and customer. Don’t lose the personal touch by using technology that cuts out the value the banker brings to the relationship. Instead, find a tool that engages the relationship managers and facilitates their trusted advisor status.

9. Positive Impact on Profitability
By finding a tool that enhances productivity across the board, you should be able to reduce cost-per-loan booked by as much as two-thirds. That means even the smallest business loans should be processed profitably.

10. Cloud-Based Model
The best way to keep pace with innovation in a cost-effective manner is to find a partner that uses the latest technology, development processes and a cloud-based model, which enhances storage capabilities. Your partner should update and enhance often, and not nickel and dime you for every enhancement or upgrade.

Stick to these guidelines and you’ll be sure to find the right tool for your unique institution.

Community Banks to Fintech: We Need You

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fintech-2-1-17.pngWhen Terry Earley, the chief financial officer of Yadkin Bank, a $7.5 billion asset bank in Raleigh, North Carolina, gets to work each morning, he sees an online dashboard showing him all the details of the loans in his bank’s pipeline, what is closing and when, and more. “If you don’t know the information, you can’t manage your company,’’ he says.

Upgrading from cumbersome Excel spreadsheets, he can easily see which lenders are pricing loans lower than others, and quickly react in terms of lender training and managing the bank’s loan portfolio. “A lot of times we try to manage [by] anecdote,’’ he says. “But what does the data tell you? The information is key.”

Like a lot of other community banks, Yadkin is increasingly using partnerships with technology companies to improve its operations and better meet customer needs. At Bank Director’s Acquire or Be Acquired Conference in Phoenix, Arizona, which wrapped up yesterday, Earley and other bankers talked about M&A and growth strategies, as well as how they were using technology to improve profitability and efficiency. In Yadkin’s case, the bank signed up with PrecisionLender, a pricing and profitability management platform, when it became a $1 billion bank several years ago. Then, it partnered with technology company nCino, which operates a secure cloud-based operating system, when it became a $4.5 billion bank, to get access to a quicker commercial lending origination platform. [For more on how banks are using the cloud, see Bank Director digital magazine’s Tech Issue story, “Banks Sail Straight Into the Cloud.”]

Even investors are getting excited about the plethora of off-the-shelf software available to help smaller banks become more competitive with larger institutions. Joshua Siegel, CEO of asset manager StoneCastle Partners, said he thinks banks have a lot of room to improve efficiencies with technology and take out back office costs, as well as offer better customer service. The software to do this is becoming increasingly available and affordable to do so. Siegel was happy to see banks as small as $150 million in assets offering online personal financial management tools superior to what regional banks are offering, because the regional banks are sometimes held up trying to develop their own software in-house.

While some financial technology companies are directly competing with banks for small business loans or payments, such as payments provider PayPal or online lender Kabbage, other financial technology companies want to sell their technology to banks.

Instead of only seeing the potential threats, there are reasons for the industry to see financial technology as a tool that can help them compete with bigger banks, which control most of the nation’s deposits. Small banks can use software to speed up their lending operations and the time it takes to open an account, and make the entire experience of doing business with a bank easier and simpler.

Somerset Trust Co. in Somerset, Pennsylvania, is using a fintech company called Bolts Technologies to quickly validate identities and open accounts for new customers. Radius Bank, a $1 billion asset bank in Boston, Massachusetts, is using a variety of partnerships with fintech companies to support its branchless bank, including a robo-advisor software company called Aspiration.

“From a cultural perspective, we look at whether they share our values,’’ said Radius Bank CEO Mike Butler. “It needs to be true partnership. If we’re just in it to try to make money off each other, then it’s not worth it. But if there is a benefit in terms of both of us wanting to create a better customer experience, then you have a great partnership.”