Digital Banking: Being Best in Class and Driving Profit

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Forward-thinking financial institutions have been focused on digital transformation to compete with megabanks and fintechs. They’re funding development to actively shaping user expectations for what a digital banking experience can offer. By 2028, the global digital banking market size is estimated to surpass $10.3 trillion.

Yet, many banks without deep pockets or partners and limited technology resources are relying on their core technology provider for a turnkey platform — a “bank-in-a-box” that includes bundled services like payments, loan origination and digital banking. The biggest threat remains for those institutions that decide to maintain the status quo with a less-than-impressive digital banking platform or ineffective home-brewed solution.

Consumers expect a seamless digital experience to help them manage their finances and achieve their financial goals. A recent study found that consumers’ trust in digital banking is shifting away from their preferred financial institution. If account holders aren’t convinced that their preferred bank provides the best digital security and privacy, reliability, feature breadth, and ease of use, they’re willing to leave. It’s clear that digital banking can make or break a bank’s future.

What is the ideal digital banking experience that account holders want? Banks should keep these best-in-class components in mind as they search for the right partners and technology for their digital banking transformation.

  1. Data-driven insights. Bank executives must find ways to execute on internal transaction data to deepen user relationships and build profitability and institutional loyalty.
  2. Seamless user experience. Now more than ever, it’s important that banks understand what attractive features will improve digital banking experiences for their users.
  3. Continuous software delivery. Best practices for continuous software delivery is to find a partner offering a single code source, rather than multiple.
  4. Investments in API and SDKs. Vendors that can seamlessly integrate application programming interfaces, or APIs, into digital banking help banks leverage the latest industry leading technology and maintain a competitive advantage.
  5. Cloud-forward thinking. Banks can leverage the cloud to enhance features, security and user experiences while improving uptime, performance and quality.
  6. Modern security strategies. When financial institutions and digital banking providers band together and treat cybersecurity as a shared responsibility, security issues can pose less of a threat.

Financial institutions may need to consider replacing legacy technologies and embracing artificial intelligence tools. This means taking advantage of transaction data flowing through the core to uncover important insights about account holders’ needs based on their behaviors and spending patterns, and using it to optimize the digital experience. This kind of thinking results in transforming digital banking — moving from a cost center into a revenue center, all rooted in data.

In the past, marketing campaigns focused on products that just needed to be sold. They were delivered from the top down, funneling to all users regardless of their personal needs. That strategy changed when big data, artificial intelligence and machine learning gave marketers the ability to target tailored messages to the ideal recipient. Aligning data insights and marketing automation means banks can deliver experiences that are compelling, timely and relevant to account holders.

Pairing insights and marketing automation with a digital banking platform allows banks to target their account holders with personalized engagements and cross-sell marketing offers that appear within the banking platform and other digital channels. Banks can generate a 70% return on initiatives targeting existing customers, versus 10% when targeting new customers, according to PwC. “In a time where every bank is focused on revenue growth in a constrained and competitive environment, making smart choices with limited resources can provide a fast track to higher-margin growth,” PwC states.

Banks can use data to drive revenue through the digital banking channel through a number of real-world, practical applications, including:

  • Onboarding programs.
  • Self-service account opening.
  • Product cross-sell and upsell.
  • Competitive takeaway.
  • Communications and servicing opportunities.
  • Product utilization.
  • Transitioning retail accounts into business accounts.

Digital banking is mission critical to banks. Catalyzing this platform with data insights and marketing automation creates an engaging channel for deeper customer relations, ultimately transforming the digital banking investment into a profit center.

Steps for Managing and Leveraging Data

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Does your institution rely on manual processes to handle data?

Institutions today generate vast amounts of data that come in different forms: transactional data such as deposit activity or loan disbursements, and non-transactional data such as web activity or file maintenance logs. When employees handle data manually, through mouse and keyboard, it puts your institution at risk for inefficient reporting, security threats and, perhaps most importantly, becoming obsolete to your customers.

Take a look at how data is moved through your organization. Exploring targeted improvements can result in actionable, timely insights and enhanced strategic decision-making.

First, focus on areas that may have the biggest impact, such as a process that consumes outsized amounts of time, staff and other resources.

What manual processes exist in your institution’s day-to-day business operations? Can board reporting be streamlined? Do directors and executives have access to meaningful, current data? Or should the institution explore a process that makes new opportunities possible, like improving data analytics to learn more about customer engagement?

Build Your Data Strategy
Crawl — The first step toward effectively managing data is to take stock of what your bank currently has. Most institutions depend on their core and ancillary systems to handle the same information. Various inputs go into moving identical data, like customer or payment information, from one system to another — a process that often involves spreadsheets. The issue of siloed information grows more prominent as institutions expand their footprint or product offering and adopt new software applications.

It’s helpful for directors and executives to ask themselves the following questions to take stock:

  • What is our current data strategy?
  • Does our data strategy align with our broader institution strategy?
  • Have we identified pain points or areas of opportunity for automation?
  • Where does our data reside?
  • What is missing?
  • In a perfect world, what systems and processes would we have?

Depending on complexity, it is likely a portion of the bank’s strategy will look at how to integrate disparate systems. While integration is an excellent start, it is only a means to an end in executing your bank’s broader digital strategy.

Prioritize ROI Efforts and Execute
Walk — Now that the bank has developed a plan to increase its return on investment, it is time to execute. What does that look like? Executives should think through things like:

  • If I could improve only one aspect of my data, what would that be?
  • What technical skills are my team lacking to execute the strategy?
  • Where should I start: build in-house or work with a third party?
  • Are there specific dashboards or reports that would be transformational for day-to-day business operations and strategic planning?
  • What digital solutions do our customers want and need?

Enable Self-Service Reporting
Run — The end goal of any bank’s data strategy is to help decision-makers make informed choices backed by evidence and objectivity, rather than guesswork and bias.

Innovative institutions have tools that make reporting accessible to all decision makers. In addition to being able to interact with data from multiple systems, those tools provide employees with dashboards that highlight key metrics and update in real time, generating the pulse of organizational performance.

With the combination of self-service reporting and data-driven dashboards, leaders have the means to answer tough questions, solve intractable challenges and understand their institution in new ways. It’s a transformative capability — and the end goal of any effort to better manage data.

The information contained herein is general in nature and is not intended, and should not be construed, as legal, accounting, investment, or tax advice or opinion provided by CliftonLarsonAllen LLP (CliftonLarsonAllen) to the reader.

Redefining Primary Relationships

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Ask 100 bankers to define what it means to be the primary financial institution for a consumer, and you’ll likely get 100 different answers. Ask 100 consultants to bankers what being the primary FI entails, and you’ll probably get 100 more answers.

Ask 100 consumers how they define which FI is their primary one, and you’re apt to get just a few answers. The most frequent answers will be: where my paycheck is deposited, or what I use to pay my bills.

At StrategyCorps, we talk to a lot of bankers about being the primary FI for a customer or member. We call this primacy. We talk about what they’re doing to lockdown primary relationships to keep from losing them, and what’s being done with non-primary customers to win them over and make them financially productive.

With few exceptions, most community and regional banks do not have a quantitative measurement or definition of primacy. It’s still very much rooted in a banker’s intuition or past experience, rather than a data-driven approach to determine precisely which customers are primary and which aren’t.

The Math
In our 20-plus years studying and analyzing retail checking relationships, products and pricing strategies, we have developed a database of well over 1 billion data performance points from hundreds of financial institutions.

We have found through this analytical approach a metric that holds true with nearly every FI we analyze, regardless of size or operating area location. Here it is: If the banking activity of a customer on a householded basis isn’t generating annually at least $350 in revenue, that household doesn’t consider your organization their primary FI.

Like clockwork, we find that when household revenue is less than $350, the banking relationship effectively nosedives. This typically is the case for 35% of all consumer checking accounts.

More specifically, we find this 35% of total checking account relationships represent slightly less than 2.1% of total relationship dollars and generate only 3.7% of revenue.

Address the Gap
Those customers are not engaged in a mutually beneficial relationship with their FI. They aren’t doing enough banking activities to generate enough revenue to cover the cost to manage and maintain their relationship. Many of those customers are primarily engaged at another FI and need a more compelling reason to bank with your FI than is currently being provided.

A major advantage of knowing specifically who does not consider your bank a primary FI is that you can develop product, pricing, communication and business development campaigns to move them closer to generating at least $350 in revenue. If you don’t, those 35% of relationships will continue to drag down financial performance. And this financial drag can be sizeable — conservatively speaking about $204 a year per relationship.

Do the math: If you have 20,000 checking relationships, 7,000 will be non-primary with a deficit of $204 per relationship. This equates to an annual loss of $1.43 million.

Build Profitability
Another major advantage of knowing precisely the amount of primary relationships at your institution is that knowledge provides great insight for a game plan to lock the relationship down even further with enhanced product offers, preferred pricing, elevated levels of customer service or, in some cases, a thank you. Doing one or more of those things diminishes the chances they’ll consider an offer from a competitor.

In today’s ultra-competitive marketplace, smart bankers realize a data-based definition of primacy in their retail checking base is necessary to make timely decisions. Banks that do so can better protect and grow primary relationships, and fix and grow the non-primary ones. By doing both, they optimize the performance and growth of their retail checking base and don’t leave the financial performance of their checking accounts to guesswork.

Winning Customer Loyalty During Trying Economic Times

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Bank leaders are preparing for an economic downshift; if done well, this can be a time to support customers’ financial health and improve long-term relationships. Proactive counsel, guidance and timely services can turn economic hardships into stronger financial foundations that benefit a bank’s bottom line.

That’s because consumers are facing the perfect storm of cash flow difficulty: Covid-related interventions have petered out, only to be replaced by a rise in the costs of goods, fuel and interest rates. Consumers cannot keep up with the pace of inflation; as of September 2022, 63% of Americans reported living paycheck to paycheck in order to make ends meet, and 43% expected to add to their debt in the next six months.

Economic hard times can give bank customers a sense of shame, discouragement and alienation. They may choose to ignore their financial troubles and debt and disengage with their financial institutions. Bankers can interrupt this pattern with more transparent and proactive best practices. They can provide support and education, in real time, that consumers need to be financially healthy.

Upwards of 80% of consumers prefer to receive money-related insights from more traditional sources such as banks, but only 14% believe their financial institution delivers such guidance. This needs to change. Banks have the unique advantage of owning the data and relationships necessary to proactively develop deep and meaningful experiences that support customers in hard times. They can use this data to maintain and protect customer relationships, rather than risk losing them to a competitor or fintech.

The first step for banks is to focus on customers’ needs, then educate them on helpful tools, best practices and how they can avoid missteps, such as products with predatory interest rates. While banks can’t control inflation, they can be a valuable partner for their customers.

Customers feel at ease when the guesswork is taken out of banking. Bankers need to eliminate the black box of uncertainty. For instance, a bank can analyze internal and external data streams, such as customer information from their loan database and the credit bureaus, to generate personalized pre-approved offers unique to its specific risk tolerance and portfolio. Such offers can include everything from home equity to auto loans, turning lending on its head from an application to a shopping cart scenario.

Banks should also consider out-of-the-box financial services and alternative offerings that can meet the evolving needs consumers face in 2023. For instance, if a consumer has a home equity surplus, the bank could suggest that they access this untapped equity in their homes for any pressing needs. The bank may offer to help a consumer with loan consolidation, or a better interest rate based on an improved credit score. Offering specific, personalized rates and services takes the mystery and chance of failure out of financial services. Banks can empower borrowers with knowledge of their unique opportunities — helping them make smart financial decisions while increasing their wallet share and gaining trust that lasts for a lifetime.

More than three in four Americans feel anxious about their financial situation. Banks must take this time to rethink the value they provide to customers. Those that prioritize personal, healthy financial guidance in 2023 will become trusted advisors and solidify relationships that last. 

Proactively Managing Credit Reporting Data

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The mandate that credit furnishers, like banks, provide accurate account data to credit reporting agencies can be overwhelming.

This information is disclosed in files that follow the standard electronic data reporting format called Metro 2®. To manage this tremendous task, banks should proactively focus on maintaining accurate Metro 2® records, which should mitigate any potential harm to consumers.

In addition to protecting consumers, accurate furnishing helps banks avoid unwanted regulatory scrutiny from increased consumer complaints and credit reporting disputes. Regulation V requires that furnishers establish and implement reasonable written documentation regarding the accuracy and integrity of consumer information furnished to consumer reporting companies (CRCs). In fact, the CFPB’s Supervisory Highlights in Spring 2022 cites this violation: “In reviews of credit card furnishers, examiners found furnishers’ policies and procedures had failed to specify how particular data fields, such as the date of first delinquency, should be populated when furnishing information about credit card accounts.”

It’s the responsibility of credit data furnishers to ensure accurate furnishing to CRCs, including that which is generated by third-party processors. Banks need a clear understanding of how well their systems of record map to their Metro 2® files and the ability to generate the right documentation to back them up.

As a senior executive in consumer reporting operations, I have my clients focus on three foundational data furnishing accuracy and control activities. First, we conduct a deep review of the Metro 2® furnishing file that is submitted to CRCs. Then we develop a detailed data mapping and conversion document to examine the system of record code that produces the file. Finally, we examine the organization’s upstream operational processes to identify trigger events and data that affect that file.

Four Areas to Examine Metro 2® Files for Accuracy
Banks should proactively focus on improving furnishing accuracy in four areas: the system of record’s limitations for compliant reporting, the internal logic in the system of record that inadvertently causes inaccuracies, inconsistencies among correlated fields and missing or inaccurate values in the fields. To avoid inaccuracies and potential regulatory red flags, review the activities below. Remember that these also apply to data generated by your third-party processors.

1. Examine your system for limitations that may hinder data compliance, including:

    • Inability to generate certain Metro 2® file segments.
    • Limited capture / storage of information (for example, 6 months versus 7 years).
    • Reporting of delinquent accounts greater than 7 years beyond the date of first delinquency.
    • Consolidation of data elements into one field requiring manual parsing (surname, first name, middle name)
    • Missing logic required to report Metro 2® fields (such as reporting spaces instead of the appropriate generation Code)
    • Not flagging required Metro 2® fields as mandatory (like a Social Security number).

2. Review logic that could result in inaccurate reporting, including:

    • Inaccurately counting days past due for account status assignment.
    • Lacking logic to report “last good payment” date after a payment reversal due to non-sufficient funds.
    • Mass overwriting of dates (such as date of account information).
    • Missing best practice controls (like if account is current and in bankruptcy, the date of first delinquency should not be blank).
    • Reporting the most recent actual payment amount value, rather than totaling all payments receiving during the reporting period.

3. Address inconsistencies among correlated fields, including:

  • Failure to update all relevant downstream data elements when manually overriding Metro 2® fields (such as account status).
  • Inaccurate or incomplete reporting when an account is closed (like date closed is not populated, current balance is greater than $0).
  • Inconsistent date progression (like if the date of account information is a date later than the timestamp of the file).
  • Inappropriate representation of Metro 2® fields related to account status (such as payment rating is not populated when required or payment history profile does not reflect the prior month’s account status).

4. Resolve missing and inaccurate field values, including:

  • Invalid assignment of portfolio type and/or account type values
  • Inaccurate values furnished for special comment code, ECOA, consumer information indicator and compliance condition code fields.
  • Ensure data accuracy now and for the future.

Now that you understand how to avoid the issues that can harm your consumers, drive credit disputes and draw regulatory scrutiny, take immediate steps to understand exactly how your data is mapping to Metro 2®. If your bank is struggling with capacity or expertise or is new to credit data furnishing, find a trusted expert to help implement both a proven technology data mapping solution as well as the knowledgeable operational support needed to execute it.

How Banks Can Create Financially Savvy Communities

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Money is a complicated subject for many Americans, and financial literacy is often a challenge.

Financial wellness is often a personal journey that lasts a lifetime — and is a place where banks and technology can really improve people’s lives. Everyone benefits when bank customers enjoy financial wellness. People in good financial health tend to enjoy better physical and mental health, contribute more to society and pay more in taxes. But from a bank perspective, financial wellness is both a challenge to be met and an opportunity to be seized. Now is the time for institutions to pick up the pace.

Although financial wellness can be hard to define, only 22% of respondents in a recent TIAA survey described their finances as “healthy.” This is a concern because of the negative compounding effects over the long term mean that multiple generations may struggle to get on top of their finances. How can the banking industry address this potential widening gap between the rich and poor?

Financial literacy is one starting point, but only 21 states require students complete a personal finance course to graduate from high school. This is a major shortcoming – personal finance is an essential life skill. There’s no substitute for starting early.

The Money Smart financial education program from the Federal Deposit Insurance Corp. helps people of all ages enhance their financial skills and create positive banking relationships. FIS actively supports this and is helping to move this program online and embed financial education within financial products and services. But there is more work to do.

Just like physical well-being, everyone has unique goals and measures of success of financial wellness. Banks that appropriately assist customers on their financial journeys can create deep loyalty and great customer satisfaction. Personalized tools are essential to help individuals align finances with life goals, such as going to college, getting married or having a family. But ultimately, financial wellness is about making small, everyday choices about budgeting, expenses and using credit wisely. While this is never easy, technology can help.

Put Data and Technology to Work
For many people, facing up to their financial position is daunting. Financial jargon can be confusing, and the majority of individuals cannot afford a financial adviser to help navigate the complexity of securities, mutual funds, 401(k)s and the like. But, with the right digital tools and banking support, most don’t need one.

Digital technology empowers people to better understand their financial transactions by harnessing the power of data. The right analysis makes it easy to determine patterns, whether decisions are wise and if they are aligned with savings and retirement goals. Sophisticated data tools can provide insights to financial wellness and take much of the hard work out of the analysis of where customers spend money, and where there are opportunities to save. Over time, people form new financial habits that encourage easier budgeting and regular saving.

The opportunity is there for banks to become proactive and help customers make better financial decisions. With a wealth of customer financial data, banks are uniquely positioned to offer customers a guided journey to good financial health; those that do will be rewarded with loyal customers.

Financial wellness is an opportunity for every bank. It requires bankers to think creatively and collaborate, likely working with fintechs and suppliers to offer financial management services that empower customers to better manage their money. Open banking makes this easier and more affordable, and the time is right to accelerate progress.

Financial wellness and financial inclusion go hand in hand. Financial wellness tools can educate and encourage unbanked and underbanked individuals to participate in the regulated bank space. But it takes perseverance and commitment from banks to progress and earn the trust of those unfamiliar with traditional banking. Banks committed to financial wellness and inclusion must think big and start small. But the crucial thing is to start.

Digitizing Documentation: The Missed Opportunity in Banking

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To keep up in an increasingly competitive world, banks have embraced the need for digital transformation, upgrading their technology stacks to automate processes and harness data to help them grow and find operational efficiencies.

However, while today’s community and regional banks are increasingly making the move to digital, their documentation and contracting are still often overlooked in this transformation – and left behind. This “forgotten transformation” means their documentation remains analog, which means their processes also remain analog, increasing costs, time, data errors and risk.

What’s more, documentation is the key that drives the back-office operations for all banks. Everything from relationship management to maintenance updates and new business proposals rely on documents. This is especially true for onboarding new clients.

The Challenges of Onboarding
Onboarding has been a major focus of digital transformation efforts for many banks. While account opening has become more accessible, it also arguably requires more customer effort than ever. These pain points are often tied back to documentation: requesting multiple forms of ID or the plethora of financial details needed for background verification and compliance. This creates friction at the first, and most important, interaction with a new customer.

While evolving regulatory concerns in areas such as Know-Your-Customer rules as well as Bank Secrecy Act and anti-money laundering compliance have helped lower banks’ risks, it often comes at the expense of the customer experience. Slow and burdensome processes can frustrate customers who are accustomed to smoother experiences in other aspects of their digital lives.

The truth is that a customer’s perception of the effort required to work with a bank is a big predictor of loyalty. Ensuring customers have a quick, seamless onboarding experience is critical to building a strong relationship from the start, and better documentation plays a key role in better onboarding.

An additional challenge for many banks is that employees see onboarding and its associated documentation as a time consuming and complicated process from an operations perspective. It can take days or even weeks to onboard a new retail customer and for business accounts it can be much worse; a Deloitte report suggests it can take some banks up to 16 weeks to onboard a new commercial customer. Most often, the main problems in onboarding stem from backend processes that are manual when it comes to documentation, still being largely comprised of emails, word documents and repositories that sit in unrelated silos across an organization, collecting numerous, often redundant, pieces of data.

While all data can be important, better onboarding requires more collaboration and transparency between banks and their customers. This means banks should be more thoughtful in their approach to onboarding, ensuring they are using data from their core to the fullest to reduce redundant and manual processes and to make the overall process more streamlined. The goal is to maximize the speed for the customer while minimizing the risk for the bank.

Better Banking Through Better Documentation
Many banks do not see documentation as a data issue. However, by taking a data-driven approach, one that uses data from the core and feed backs into it, banks transform documents into data and, in turn, into an opportunity. Onboarding documents become a key component of the bank’s overall, end-to-end digital chain. This can have major impacts for banks’ operational efficiencies as well as bottom lines. In addition to faster onboarding to help build stronger customer relationships, a better documentation process means better structured data, which can offer significant competitive advantages in a crowded market.

When it comes to documentation capabilities, flexibility is key. This can be especially true for commercial customers. An adaptable solution can feel less “off the shelf” and provide the flexibility to meet individual client needs, while giving a great customer experience and maintaining regulatory guidelines. This can also provide community bankers with the ability to focus on what they do best, building relationships and providing value to their customers, rather than manually gathering and building documents.

While digitizing the documents is critical, it is in many ways the first step to a better overall process. Banks must also be able to effectively leverage this digitized data, getting it to the core, and having it work with other data sources.

Digital transformation has become an imperative for most community banks, but documentation continues to be overlooked entirely in these projects. Even discounting the operational impacts, documents ultimately represent the two most important “Rs” for banks – relationships and revenue, which are inextricably tied. By changing how they approach and treat client documentation, banks can be much more effective in not only the customer onboarding process, but also in responding to those customer needs moving forward, strengthening those relationships and driving revenue now and in the 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.

Taking Model Risk Management to the Next Level

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

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

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

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

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

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

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