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Managing deposits proactively

Deposit behavior—how long funds stay, how sensitive they are to pricing, and where they ultimately flow—can signal risks and opportunities. Understanding and acting on those signals can help financial institutions strengthen margins, liquidity, and long-term performance. 

two men and woman around a desk

Rethinking balance sheet risks

After an extended period of rate volatility, margin compression, and liquidity pressure, financial institutions are once again being challenged to adapt. Bank leaders are looking for ways to manage risk and drive growth. Increasingly, they are finding those strategies through a deeper understanding of deposit behavior and its impact on balance sheet performance. 

Deposits remain the cornerstone of bank strategy, according to Rob Newberry, Senior Consultant at Abrigo, even as the dynamics around them evolve. “The deposits are the foundation of bank funding,” Newberry says. “Depending on how your institution is growing, you have to have enough funding to continue to fund the loan growth that you have. Are you growing at the pace of your deposit growth, or are you outgrowing it?” 

Hear more from our experts on deposit growth.

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Why deposit behavior has become a strategic priority 

For many banks, regulatory requirements or periodic ALM reviews have historically driven the use of deposit modeling. But that approach overlooks how deposit behavior directly influences liquidity planning, loan growth capacity, pricing decisions, and ultimately profitability. 

“Accurate modeling enhances risk management and strategic planning,” Newberry says. “One of the biggest things we want to understand from an analytics perspective is how long those deposits are going to be around, because that impacts your ALM assumptions and a lot of other decisions downstream.” 

The need for accurate modeling is particularly acute for community and regional banks, where funding options may be more constrained and customer concentration risks are higher. Newberry points to demographic exposure as an often-overlooked factor that can impact smaller institutions. “A good chunk of your deposit balances may be represented by people over seventy years old,” he notes. “How much longer are those deposits going to be around, and how does that wealth transfer to the next generation?” 

Understanding decay, stability, and longevity 

At the center of modern deposit analysis is decay—the rate at which balances naturally run off over time. While the concept is familiar, Newberry emphasizes that its strategic implications are often underestimated. 

“Decay rates measure the rate at which deposit balances diminish over time,” he explains. “It’s exactly like prepayments on the loan side. Deposits decline because customers withdraw funds, move money internally to other accounts, or shift balances to different investment types.” 

By pairing decay rates with weighted average life and effective duration, banks gain a clearer picture of how reliable their funding really is under changing market conditions. This distinction becomes especially important when separating core balances from surge balances, which are the funds that are more likely to leave when rates or conditions change. 

“Surge balances are an inflow of deposits triggered by an event, and they’re likely to flow back out relatively quickly,” Newberry says. “These balances are usually rate sensitive and can move at any time.” 

Failing to identify surge behavior can leave institutions exposed, particularly if temporary liquidity is mistakenly treated as long-term funding. 

Pricing strategy, cannibalization, and margin risk 

Deposit pricing remains one of the most visible tools banks use to compete for funding, but it is also one of the most dangerous if used without insight. Newberry cautions that raising rates to attract new money often triggers internal movement rather than true growth. 

“When you raise rates on a new account, you have to understand how much ‘old’ money is moving into that account,” he explains. “That internal transfer increases your interest expense, and sometimes you’re paying a lot more than you realize for the next ten million dollars.” 

This concept of marginal cost is critical in an environment where margins are already under pressure. “Sometimes paying up for deposits might actually destroy your margin instead of strengthening your balance sheet,” Newberry says. “It becomes a balancing act between growth and profitability.” 

Aligning deposit pricing behavior with loan repricing by using beta and lag thoughtfully can help institutions protect net interest margin while remaining competitive. 

Who’s in charge of deposits? 

Ultimately, the value of deposit analytics lies in how effectively insights are translated into action. That requires clear ownership and consistent focus. 

“One of the first questions we ask when we work with banks is: who is actually in charge of your deposits?” Newberry says. “You might have multiple people in charge of loans, but on the deposit side, it’s often fragmented. Someone really must be focused on deposits every day if you want to be successful.” 

By integrating deposit behavior, pricing dynamics, and demographic trends into ALM and forecasting processes, banks can plan ahead. In an uncertain environment, proactive institutions are better positioned to compete against a growing list of competitors while strengthening their long-term resilience. For more insights on deposit strategy, register for the ABA’s March webinar, From Rates to Results: Turning Economic Shifts into Strategy, designed for senior financial leaders seeking to move beyond reactive management and toward a more data-driven approach. 

This blog was written with the assistance of ChatGPT, an AI large language model, and was reviewed and revised by the subject-matter expert.

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A 'gray rhino' for financial institution lenders?  

The changing nature of insurance companies' investment portfolios poses emerging credit risk that financial institution lenders should understand and monitor.

This article covers these key topics: 

Insurance: Managing and posing credit risk

For lenders, insurance is one of those necessities we secure upfront and rarely think about—until a crisis hits. Most seasoned bankers have experienced the sinking feeling of seeing a collateral property on the news engulfed in flames or destroyed in a natural disaster, followed by a too-quick drive to the office to confirm that the insurance policy is active and lists us as loss payee.

The fear of loss that’s behind that scramble is one reason why insurance has always mattered in credit. But there’s a quieter, potentially more dangerous insurance-related risk emerging, and it may catch the banking industry unprepared.

Read about best practices for identifying and managing key vulnerabilities in the portfolio.

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Insurers’ investments: An emerging risk to credit

At its core, insurance is a simple business: collect premiums, invest the funds, and pay claims. Three key risk points in this business model are well known to financial institutions:

  1. Affordability: Rising premiums strain cash flow for small businesses or tenants that have borrowed from a financial institution. The strain can force these borrowers to choose between paying bills or maintaining insurance coverage on the collateral securing a loan.
  2. Coverage gaps: Higher deductibles or new exclusions can make it difficult for insureds to return property to operational status after a loss, leaving repayment at risk.
  3. Dropped policies: Some insureds or insurers may cancel coverage entirely, the latter even across entire states or regions, posing risk to lenders with insured collateral.

Growing private market investments among insurers

A fourth credit risk related to insurance, however, is a “gray rhino,” the kind of problem that’s right in front of you, but you don’t see it). It’s the changing nature of insurance companies’ investment portfolios.

Like financial institutions, insurers must manage liquidity to meet claims. Unlike banks and credit unions, insurance companies have far more latitude in their investment choices. Increasingly, they’re reaching for yield through private credit and private equity, either directly or via funds.

Private credit investments account for more than 35% of total U.S. insurers’ investments, according to a Nov. 14, 2025, Financial Times article. In addition, private equity investors own 139 insurers as of mid-2025, according to the National Association of Insurance Commissioners (NAIC) Capital Markets Bureau. These investments account for 7.8% of insurers’ total assets in the U.S. While still small, the number is growing.

Riskier, illiquid positions

The contrast with the investment approach of traditional financial institutions is stark. Banks and credit unions have a fiduciary duty to depositors, prioritizing liquidity and stability. Private equity and credit funds, by contrast, prioritize yield, accepting illiquidity and higher risk of investing in nontraditional or alternative assets to achieve investment returns. As these investment strategies permeate insurers’ portfolios, they import vulnerabilities foreign to the conservative world of regulated finance.

The problem intensifies during economic downturns, when illiquid positions become even harder to unwind.

In addition, the recent bankruptcies of Tricolor and First Brands highlight the consequences—potential fraud aside—of weak oversight. Unlike banks and credit unions, private investors often lack the robust monitoring systems designed to prevent such failures.

In short:

  1. Private credit and private equity are risky investments.
  2. They now represent a significant portion of insurers’ portfolios.
  3. Private equity ownership of insurers is rising and could reshape both operations and risk management.

This evolving insurance landscape demands attention from credit risk professionals.

Insurance risk-concentration management planning

As with any concentration in your portfolio, financial institutions need a plan to deal with insurers and related risks to credit. Such a plan could include the following elements:

1. Assess exposure to insurers

Start by understanding your aggregate exposure to various insurers. The data exists; it’s just not always tracked. Begin with your largest relationships and work down the portfolio. Over time, aim to capture exposure data through normal credit events (renewals, new loans, reviews). You can’t control which insurers your clients use, but you can measure concentrations and prepare mitigation strategies.

2. Perform credit analysis as if you were underwriting insurers

Next, conduct financial and ownership reviews of your top insurance counterparties. Retrieve financials via company websites or the SEC’s EDGAR database. Examine 13F-HR filings for insights into investment holdings. Your loan review team—or your best credit analyst—should lead this effort to ensure objectivity and rigor. Monitor insurers on an ongoing basis

Check each insurer’s state-level activity through insurance commission websites and monitor the news for post-event changes in pricing or coverage. Track ownership changes closely—these often precede shifts in risk appetite or investment behavior.

Leverage your front-line intelligence: conversations with customers and insurance agents can surface early warning signs. Insurance may not be the most exciting topic, but it’s becoming one of the more critical.

3. Monitor insurers on an ongoing basis

Check each insurer’s state-level activity through insurance commission websites and monitor the news for post-event changes in pricing or coverage. Track ownership changes closely—these often precede shifts in risk appetite or investment behavior.

Leverage your front-line intelligence conversations with customers and insurance agents can surface early warning signs. Insurance may not be the most exciting topic, but it’s becoming one of the more critical.

4. Understand risks in “non-traditional” insurance

Don’t overlook specialized insurance such as crop coverage, where multi-year events (like droughts) can depress future claims due to declining average yields. Build those scenarios into your stress testing.

5. Have a plan of action

If a major insurer in your concentration pool changes terms, withdraws coverage or exhibits adverse changes in financial position, use your data to act proactively. Reach out to affected customers with potential alternatives rather than waiting for a crisis. Doing so builds trust—and resilience.

Insurance: No “get it and forget it” checkbox for lenders

Insurance cannot be a “get it and forget it” checkbox. It’s an integral component of credit risk management. Understanding your exposure—both macro and micro—can make the difference between a contained issue and a systemic problem.

Now’s the time to start asking the uncomfortable questions before the gray rhino charges.

 

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What is the OFAC 50% rule?  

OFAC’s sanctions guidance on entity ownership

OFAC’s 50 percent rule helps financial institutions and others understand when to block transactions involving entities or organizations. Compliance with the rule is as substantial as ever.

The OFAC 50% rule: What it is

The OFAC 50% rule is guidance from the U.S. Department of the Treasury’s Office of Foreign Assets Control (OFAC) that clarifies which entities and organizations must be blocked from transactions under U.S. sanctions programs. The rule plays a critical role in ensuring that sanctioned individuals cannot bypass restrictions by using corporate structures to hide ownership.  

Specifically, OFAC’s 50% rule is the requirement to consider as a blocked party any entity that is owned 50 percent or more, directly or indirectly, by one or more blocked individuals or parties, even if the entity is not explicitly named on the Specially Designated Nationals (SDN) list.  

This means U.S. financial institutions must treat these entities as though they were sanctioned, and engaging in transactions with them is prohibited unless authorized by OFAC.

Why is the OFAC 50% rule important right now?

OFAC administers and enforces U.S. economic and trade sanctions against foreign governments, regimes, terrorists, international drug traffickers, and transnational criminal groups. And while sanctions compliance has always been a backbone of Bank Secrecy Act (BSA) compliance, the global political and economic environment in recent years has meant increased sanctions and intense regulatory scrutiny to prevent transactions to and from sanctioned countries, individuals, and entities.

For compliance professionals, what used to be a simple “are they on the list?” check has grown more complex as OFAC has issued new guidance in recent years. However, violating sanctions can lead to severe civil penalties and reputational damage for financial institutions, underscoring the importance of understanding the 50% rule and ownership-related sanctions risk.

A series of enforcement actions makes it clear that OFAC is actively monitoring indirect ownership and control risks. Institutions that fail to identify entities subject to the OFAC 50% rule may face civil penalties, even when the blocked party is not directly named.

With sanctions programs evolving rapidly in response to geopolitical conflict, financial institutions are expected to ensure their screening and due diligence programs are up to date and capable of identifying entity ownership risk.

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Recent enforcement highlights the broad interpretation of the 50% rule.

In a recent enforcement action, OFAC issued a civil money penalty against Chicago-based private equity firm IPI Partners, LLC, for violations of U.S. sanctions on Russia. The violations stemmed from indirect dealings with sanctioned oligarch Suleiman Kerimov, who was added to the OFAC SDN List on April 6, 2018. Under OFAC rules, that designation required the blocking of all related property and interests in property.

What makes this case significant is that Kerimov did not directly own 50% or more of the transacting entity but was determined to be indirectly involved in the dealings. The enforcement highlights OFAC’s broad interpretation of ownership and control under the 50% rule, reinforcing that it looks beyond legal formalities to identify real-world influence and economic benefit.

How do financial institutions apply the OFAC 50% rule?

Unlike the SDN list, OFAC does not publish a formal 50% list of blocked entities. Instead, institutions must understand ownership aggregation and are expected to gather beneficial ownership information on legal entities, cross-reference owners with the SDN list, and aggregate ownership percentages across multiple blocked persons to determine if they meet the 50 percent threshold.

If an entity is determined to be 50 percent or more owned, directly or indirectly, by blocked individuals or entities, it is considered blocked, regardless of whether it appears on any OFAC list. Institutions that rely solely on list-based screening without ownership analysis risk missing sanctioned entities.

What should financial institutions do to stay compliant?

  1. Strengthen due diligence and CDD practices
    A robust customer due diligence (CDD) program is the first line of defense. Institutions should collect beneficial ownership information at onboarding and update it regularly. Institutions need to check both direct and indirect ownership before doing business. Pay special attention to complex corporate structures or clients operating in high-risk jurisdictions.
  2. Train staff on sanctions compliance expectations
    Staff responsible for compliance, onboarding, and investigations must understand how the OFAC 50% rule works and how to spot red flags. They should also consider the risk when ownership or control by sanctioned individuals or entities is significant—even if below 50%. Sanctions compliance requires human oversight and critical thinking.
  3. Document entity ownership reviews and decision-making
    OFAC expects institutions to make reasonable efforts to identify blocked entities based on ownership. That means keeping clear records of ownership reviews, decision rationales, and escalation procedures.
  4. Review your program considering recent enforcement actions
    Many institutions have not reassessed their sanctions compliance programs since the last major OFAC update. This is a good time to revisit policies and procedures to ensure they reflect current expectations, including application of the OFAC 50% rule.

What does this mean for community banks and credit unions?

Smaller institutions may assume that the OFAC 50% rule is primarily relevant to international or large-scale banking relationships. However, enforcement actions like the one involving IPI Partners prove that any U.S. person, including domestic financial institutions, must comply. That is why institutions of all sizes must build ownership analysis into onboarding, transaction reviews, and customer risk ratings.

 

Sanctions compliance still requires people

Sanctions compliance cannot be left solely to software. Institutions must ensure they have adequate staffing and escalation procedures to evaluate potential ownership risks flagged during onboarding or monitoring. As OFAC’s guidance indicates, even formalistic ownership structures can mask absolute control or influence.

Trained AML staff must have the time and authority to dig deeper and escalate when necessary. Institutions facing turnover, resource gaps, or outdated processes should strongly consider an AML staffing assessment to ensure their programs can meet these evolving expectations.

How does the OFAC 50% rule relate to the OCC’s MLR pullback?

While the Office of the Comptroller of the Currency (OCC) recently discontinued the Money Laundering Risk (MLR) report, this should not be seen as a reduction in regulatory expectations. Instead, it signals a shift from prescribed formats to outcomes-based compliance.

The OFAC 50% rule is a prime example. Just as the OCC expects institutions to self-manage money laundering risk without relying on the MLR, OFAC expects institutions to apply ownership and control guidance proactively, rather than just screening against static lists. The regulatory burden lies with institutions to demonstrate adequate controls and thoughtful risk assessments, not just adherence to forms.

Compliance is evolving, so should your program

The OFAC 50% rule remains a fundamental requirement of sanctions compliance. Regulators are paying close attention to beneficial ownership and control structures, even when they are not obvious.

Financial institutions must ensure that technology, staffing, and training keep pace with regulatory expectations. Staying compliant means going beyond the checklist and being prepared to explain and defend every decision. As sanctions programs evolve, it’s not enough to rely on past processes. Institutions must equip teams to manage today’s ownership risks and prepare for tomorrow’s enforcement realities.

 

 

Get a free AI readiness checklist and other resources on Abrigo's AI Hub.

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What are Chinese money laundering networks? 

Executive Summary:

Chinese money laundering networks (CMLNs) pose a high and evolving risk to U.S. financial institutions due to their role as professional money laundering service providers for transnational criminal organizations, including major drug cartels. These networks exploit international currency controls by matching cartel-generated U.S. cash with Chinese nationals seeking to bypass capital outflow restrictions, using mirror transactions, intermediaries (e.g., students and money mules), shell companies, real estate, healthcare-related fraud, and trade-based money laundering to integrate illicit proceeds into the financial system. 

  • Risk Rating: High— driven by the scale of illicit funds, use of legitimate businesses and accounts, and increasing regulatory focus. 
  • Control Impact: Elevated— Reinforce enhanced customer due diligence, risk-based transaction monitoring, targeted typology training, and ongoing alignment with FinCEN advisories regarding Chinese money laundering networks.

The growth of Chinese money laundering networks

Chinese money laundering networks (CMLNs) are emerging as one of the most significant threats to the U.S. financial system through illicit finance. These networks are linked to the movement of billions of dollars in drug trafficking proceeds and other criminal gains. Institutions across the U.S. are increasingly exposed to risk, often unknowingly, as these networks exploit the banking system to launder illicit funds.

A recent advisory from the Financial Crimes Enforcement Network (FinCEN) highlights how Chinese money laundering networks are facilitating drug trade proceeds for powerful organizations like the Sinaloa Cartel, Gulf Cartel, and Cartel de Jalisco Nueva Generacion (CJNG). But the risks go beyond narcotics. These networks are also laundering profits from human trafficking, healthcare fraud, illicit gambling, and even illegal marijuana grow operations across several U.S. states.

As anti-money laundering/countering the financing of terrorism (AML/CFT) professionals evaluate their institution's risk, understanding what Chinese money laundering networks are and how they operate is critical to protecting customers and maintaining compliance.

Understanding Chinese money laundering networks

Chinese money laundering networks are organized groups, often composed of Chinese nationals or former foreign citizens, that act as professional money launderers. They specialize in converting illicit U.S. currency into usable funds through various underground banking methods. These networks capitalize on capital flow restrictions in both Mexico and the People’s Republic of China (PRC):

  • Mexico restricts how much U.S. currency can be deposited in its financial system, which creates a challenge for cartels looking to repatriate profits.
  • China limits how much money citizens can move abroad, making it difficult for individuals to invest in foreign assets legally.

CMLNs offer a mutually beneficial solution: cartels require a means to launder large amounts of U.S. dollars, while wealthy Chinese nationals seek to access those funds to circumvent China’s currency controls.

 

How do Chinese money laundering networks operate?

Although the operations can be complex, a simplified overview reveals a three-step process:

  1. Mirror transactions – U.S. dollars are collected from the cartels. A CMLN associate in Mexico quickly transfers an equivalent amount in pesos to a cartel account, creating the illusion of a legitimate exchange.
  2. Use of intermediaries – Students on visas, money mules, and brokers, many unaware of their involvement in illegal activity, facilitate the movement of funds. Chinese students in the U.S. are often targeted due to employment restrictions and financial need.
  3. U.S. cash to China – CMLNs sell the dollars to Chinese nationals via social platforms. Buyers transfer renminbi to Chinese-based operators, paying a premium. The U.S.-based network then delivers the cash to the buyer locally.

Throughout this process, the networks exploit shell companies, straw buyers, real estate, luxury goods, and in some cases, trade-based money laundering (TBML). In New York, adult day care centers have been connected to healthcare fraud and CMLN activity, while grow house operations tied to CMLNs have been discovered in states from California to Maine.

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FinCEN Financial Trend Analysis

In August 2025, FinCEN published a Financial Trend Analysis (FTA) assessing SAR filings related to suspected CMLN activity between 2020 and 2024. The majority of the filings were submitted by financial institutions, with others filed by Money Service Businesses (MSBs), casinos, security firms, insurance companies, and other entities, totaling approximately $312 billion in suspicious activity. The analysis identified or confirmed the following activity:

  • CMLNs use U.S.-based Chinese nationals to perform cash deposits, often with an unknown source of funds. The funds are generally debited through same-day transfers to internal or external accounts.
  • CMLNs use TBML to facilitate funds movement. Funds are deposited from various entities using different methods (e.g., cash, wire transfers, P2P), and they are used to purchase high-end luxury goods or to pay down large credit card balances.
  • CMLNs recruit Daigou Buyers. Daigou means “buying on behalf of” and refers to an arrangement in which buyers use messaging platforms to connect Chinese consumers with products. The products are then sold for a profit to replenish accounts.
  • Human Trafficking and Human Smuggling activity was linked to CMLN networks. The activity involved funds movement to businesses typically associated with labor or sex trafficking, such as massage parlors, spas, escort services, and restaurants and bars.
  • CMLNs possibly use adult daycare centers and may also be associated with healthcare fraud, elder abuse, and illicit gaming activity. These filings identified activity involving senior facilities in New York that allegedly defrauded Medicaid, Medicare, and private insurance companies. In addition, the filings noted excessive or unnecessary movements unrelated to typical operational activity.
  • CMLNs facilitate real estate transactions using illicit proceeds. The purchases are often intended to benefit individuals in the PRC who wish to move wealth to the U.S.
  • CMLNs use Chinese students to facilitate financial activities.

 

Key red flags for financial institutions

No single red flag confirms illicit activity, but multiple risk indicators, when combined, should prompt enhanced due diligence. Institutions asking what Chinese money laundering networks are and how to detect them should consider the following red flags:

  • Inconsistent wealth: Chinese nationals depositing large amounts of cash without employment history that supports the volume.
  • Unexplained transfers: Incoming international wires from like-named accounts, inconsistent with the customer’s profile.
  • Unusual real estate purchases: High-value purchases with unclear or unverifiable sources of funds.
  • Suspicious business activity: Business accounts operated by Chinese nationals with little to no expected activity (e.g., no inventory purchases).
  • Geographic mismatches: Rental income or business transactions originating from locations inconsistent with the customer’s operations.
  • Healthcare business risks: Adult day care and home healthcare providers receiving significant Medicare/Medicaid reimbursements and quickly withdrawing funds or transferring them to personal accounts.

AML/CFT programs should also track businesses in the electronics, telecommunications, or luxury goods industries, as these sectors are known to be exploited by CMLNs.

How financial institutions can respond

To reduce exposure to CMLNs, financial institutions must ensure their AML programs are comprehensive, data-driven, and tailored to evolving risks. Institutions should:

  • Implement ongoing transaction monitoring with thresholds appropriate for geographic and business risk.
  • Conduct robust customer due diligence (CDD), especially for international students, cash-intensive businesses, and real estate clients.
  • Train staff to recognize complex money laundering methods, including TBML and underground banking systems.
  • Stay informed of typologies outlined in regulatory alerts, including those from FinCEN and interagency task forces.

Understanding what Chinese money laundering networks are also requires awareness of how legal businesses can be manipulated. Legitimate enterprises can be used as fronts, making it vital for compliance teams to investigate both customer behavior and broader transactional patterns.

Get a free AI readiness checklist and other resources on Abrigo's AI Hub.

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Final thoughts

Financial institutions play a critical role in safeguarding U.S. financial system from illicit activity. As cartels and transnational actors increasingly rely on CMLNs to launder funds, financial institutions must remain vigilant to evolving typologies and ensure their staff are equipped to detect suspicious behavior.

By asking what Chinese money laundering networks are and understanding their operations, institutions can enhance their AML/CFT frameworks, minimize regulatory risk, and help stop the flow of funds that support drug trafficking, human exploitation, and organized crime.

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The basics of CUSO partnerships for credit unions

Here’s how forward-thinking credit unions can expand their member business lending with CUSOs by aligning strategy, structure, and compliance with long-term goals.

How CUSOs can improve processes and help grow member business lending

Each year, credit unions deliver significant savings to members through lower interest rates on loans. Member business lending (MBL), however, brings a distinct set of challenges. Whether your credit union is seeking to scale its technology, diversify income streams, or expand product offerings, one increasingly viable and sustainable path forward is to partner with credit union service organizations (CUSOs).

CUSOs provide credit unions with a cost-effective, and innovation-friendly model for growing the MBL portfolio. They allow institutions to preserve their member-first identity while remaining agile in a competitive market.

You might also like this webinar, Mitigating Top MBL Risks.

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The case for CUSO collaboration

CUSOs are uniquely structured entities that are owned by credit unions and exist to provide services that might otherwise be too expensive or complex to develop in-house. Under NCUA regulations, federal credit unions can invest in or loan to CUSOs that primarily serve credit unions and are limited to approved activities such as loan origination, technology services, and financial counseling.

By engaging in collaborative ventures like CUSOs, credit unions can reduce duplication of services and achieve operational efficiencies that directly benefit members.

Credit unions are leveraging CUSOs for a variety of strategic purposes. Some partner with lending-focused CUSOs to expand into new verticals like commercial or indirect lending. Others outsource technology, compliance, or data analytics functions to CUSOs, reducing operational overhead while maintaining control over the member experience. Many CUSOs also offer consultative training to help internal staff become more comfortable with business lending practices.

CUSOs are particularly useful for smaller institutions that might struggle to afford or implement advanced solutions independently. Rather than build a loan origination platform or fraud detection system in-house, for example, a credit union can invest in a CUSO that offers the service and immediately bring the benefits to their members.

 

Aligning CUSO strategy with your credit union’s goals

A successful CUSO strategy starts with clarity. Before making any investment or partnership decisions, credit unions should define their objectives. The end goal might be to offer a smoother member business lending experience, enhance noninterest income, improve digital capabilities, or deliver new products like insurance or wealth management.

Credit unions that partner with CUSOs often begin by identifying gaps in their current service delivery or areas where member demand exceeds institutional capacity. The next step is selecting or forming a CUSO that complements those needs. Next, determine if the scope of the relationship will be ownership, partnership, or full acquisition.

Legal structure, compliance implications, and governance responsibilities should all be considered. According to the NCUA, CUSOs must maintain independent financial records and provide annual reports to both the NCUA and state supervisory authorities if they are federally insured. Ensuring your institution’s internal oversight keeps pace with the partnership is essential for long-term success.

 

Funding and risk oversight

Investment in a CUSO requires thorough due diligence and financial modeling. Institutions looking to grow with CUSOs should develop clear financial projections, understand expected return timelines, and evaluate the impact on balance sheet strength.

Ongoing risk oversight is also key. The NCUA emphasizes that credit unions must monitor CUSO activities to ensure safety and soundness are not compromised. Even minority ownership stakes can pose reputational or regulatory risk if a CUSO fails to meet compliance expectations. To mitigate this, credit unions should implement periodic reviews, audit procedures, and performance benchmarks for any CUSO relationship.

 

Grow with CUSOs: A scalable model for the future

By choosing to grow with CUSOs, credit unions gain access to industry expertise, advanced technology, and scalable service models that align with both growth and member impact. And because CUSOs are built on collaboration and shared success, they represent the kind of values-driven innovation the credit union movement was founded on.

Whether you’re seeking to expand your loan portfolio, enhance digital experiences, or boost operational efficiency, now is the time to explore how your institution can grow with CUSOs.

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This article covers these key topics: 

AI adoption challenges tied to technology and data

Many financial institutions face AI adoption hurdles because of their legacy core systems, manual workflows, and fragmented data. The right technology partner can help put banks and credit unions on the path to speed and precision.

Systemwide challenges to adopting AI

For some financial institutions, the promises of artificial intelligence (AI) seem unattainable due to practical challenges. Technology and data considerations, such as legacy core systems, manual workflows, and fragmented data environments, often stand in the way.  

How can banks and credit unions overcome tech hurdles to modernize operations and tap the potential of AI to keep pace with customer expectations, increasing fraud risk, and regulatory complexity? Implementing AI isn’t simple, but the right technology partner can help make the path clear and practical. 

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AI solutions

Legacy core systems can challenge AI implementation

Even though most believe AI will have a large impact on banking, banks and credit unions identify a number of barriers to adopting AI, according to a recent Abrigo survey of nearly 300 bankers. While concerns range from compliance to budget to return on investment, nearly a third of bankers identified data quality or data accessibility as adoption obstacles.  

Technology and related issues around data are an understandable challenge for many financial institutions looking to tap AI’s benefits. Many institutions still rely on decades-old core systems. Often such systems weren’t designed to support the data volume or flexibility that modern AI requires. In general, these aging infrastructures often lead to siloed data, limited integration options, and rigid architectures that slow innovation. 

How financial institutions can ease the path to AI: 

  • Look for cloud-based solutions that can integrate with legacy core systems, allowing institutions to modernize incrementally without undergoing a full core replacement. 
  • Seek out platforms that centralize data across departments to improve visibility, reduce duplication, and enable faster, more strategic decisions. Platforms that can share data across lending, credit risk management, balance-sheet management, and compliance simplify the complexity of managing multiple data stacks.  
  • Choose partners with a proven track record of helping community financial institutions navigate modernization in a regulated environment. For example, with more than 2,400 financial institution customers, Abrigo understands the operational and regulatory realities institutions face and helps them modernize without disruption. “Our AI-powered suite is designed to be modular, so banks and credit unions can adopt AI at their own pace, starting where it will have the most impact and scaling over time,” said Ravi Nemalikanti, Abrigo’s Chief Product & Technology Officer. 

Reliance on manual processes hinders AI adoption 

Manual processes are another challenge facing some banks and credit unions looking to benefit from AI technology. Manual workflows limit scalability and delay getting the kinds of strategic insights that AI could generate in real time. The impacts include missed opportunities, increased regulatory risk, and staff tied up with redundant data entry, disjointed compliance tasks, and repetitive reviews instead of strategic thinking or innovation.   

How to clear the roadblock to AI: 

  • Look for automation capabilities in high-impact areas like lending, credit risk review, and fraud detection to streamline operations and reduce the risk of human error. “Lending and financial crime are the areas where banks feel the most friction, and they’re also the best starting points for AI to make a meaningful impact,” Nemalikanti said. 
  • Choose lending solutions that automate data entry, credit analysis, and compliance tracking to improve consistency and save time. 
  • Work with partners that offer expert guidance or advisory support to help assess existing workflows and identify automation opportunities that improve efficiency without adding headcount. Optimizing an existing process can be a good first step toward layering in AI. 

Data quality and accessibility can block AI efforts   

AI models are only as strong as the data behind them. For many financial institutions, years of collecting data in spreadsheets, core extracts, and siloed systems have resulted in fragmented datasets. Those are not only difficult to reconcile on a regular basis but are also nearly impossible to analyze effectively and provide data-driven strategies.  

However, building a data warehouse internally can quickly turn into a complex, expensive endeavor that requires technical expertise many community institutions don’t have. “It takes effort to get data warehousing 100% right,” said Nathan Myers, Vice President of Integration and Client Care at Abrigo. “And unfortunately, in some cases, data that is not 100% right is 0% useful.” 

How a technology partner can help: 

  • Some data platforms eliminate the need for expensive in-house data warehousing and reduce the burden of reconciling inconsistent data across systems. 
  • Solutions like those on the Abrigo platform can naturally improve data accuracy as users engage with them daily. “The benefit of a strong data platform is that it pulls data from a suite of analytical and operational software that actually uses the data every day,” Myers said. “Since users actively and consistently use these tools, the underlying data will naturally be more reliable and accurate without any additional effort required for financial institutions.” 
  • Tools on a unified platform simplify integration and data cleansing, and those that provide user-level access controls and AI-driven reporting make it easier to surface insights and visualize data for measuring performance and risk.  
  • Some technology partners can provide strategic guidance on how to build a clean, actionable data foundation. Abrigo, for example, has decades of experience helping banks and credit unions with changes that require data integrity such as: 
  1. Adopting the current expected credit loss (CECL) accounting changes. 
  2. Automating transaction monitoring for anti-money laundering efforts. 
  3. Implementing small business lending data collection requirements under the CFPB’s 1071 rule). 

Building a technology roadmap to AI readiness 

Even with the right tools, many institutions still ask: Where do we begin? “Financial institutions need AI that’s transparent, explainable, and compliant,” Nemalikanti said. “At the same time, leaders worry about disrupting day-to-day workflows or overextending resources with large-scale transformations.” 

How to move from frozen to AI-forward: 

  • Start with a partner that offers readiness assessments to identify gaps in your institution’s infrastructure, processes, and data maturity. Download this AI readiness checklist to prepare for responsible, successful AI implementation.  
  • Look for modular, assistive AI capabilities from a single provider that can deliver early wins—such as AI-generated CECL narratives, fraud case summaries, or SAR narrative suggestions. These solutions align with a phased AI strategy, allowing your institution to test, learn, and scale adoption over time. 
  • Seek partners who can help you prepare for the next wave of innovation. Abrigo, for example, has helped financial institutions for more than 20 years as they adapt to changing needs such as adopting the current expected credit loss model (CECL), offering Paycheck Protection Program (PPP) loans efficiently, and adopting small business lending data collection requirements under the CFPB’s 1071 rule.  

As Nemalikanti explained, the real value of a technology partner like Abrigo comes “from our deep understanding of where our customers spend the most time and what tasks consume them day to day. With that insight, we can embed AI into the repetitive and deterministic areas, freeing our customers to focus their energy on the work that truly drives impact.” 

Address tech complexity and build AI for scale 

With increasing regulatory scrutiny, evolving customer demands, and competitive pressure from all sides, financial institutions can’t afford to wait on adopting AI. But they also can’t afford missteps. 

By addressing legacy technology, simplifying manual processes, and improving data readiness, institutions can set the stage for meaningful innovation. And banks and credit unions don’t have to navigate AI on their own. The right technology partner will help institutions prepare, pilot, and progress in their AI implementation. 

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5 key trends that are shaping the current state of equipment leasing

Economic conditions, regulatory expectations, and borrower behaviors are reshaping how equipment leasing lenders operate in 2026. Read on to learn how rapid technology shifts and persistent cost pressures are requiring institutions to reevaluate risk strategies, digitize delivery models, and formalize governance frameworks.

 

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The rising importance of credit quality discipline

With elevated interest rates and sector-specific slowdowns, equipment leasing lenders are focusing more on consistency and transparency in decision-making rather than faster credit approvals. Delinquencies have risen in transportation and small-ticket segments, triggering more intensive monitoring and risk-based segmentation. The Equipment Leasing & Finance Foundation (ELFF) Confidence Index has hovered below the 50-point threshold throughout early 2026, with participants citing concerns about credit quality and borrower demand.

Speed to decision and improved workflows are still important, but lenders are investing in data accuracy, consistency, and visibility to mitigate risk. Institutions that can track portfolio health in real time—by segment, collateral type, and geography—are better equipped to adjust pricing and exposure levels when warning signs emerge.

Embedded finance becomes an operational requirement

Dealer and vendor expectations have shifted. Embedded finance—once viewed as a differentiator—is now expected. Businesses want financing options built directly into the buying process, with minimal disruption or delay.

According to McKinsey & Company, embedded finance enables institutions to offer real-time approvals, increase conversion rates, and strengthen partner relationships. For equipment leasing lenders, this means rethinking legacy processes and adopting flexible digital tools that support automated quoting, instant approvals, and API-based integrations with dealer platforms. Those who maintain manual, disconnected workflows may struggle to remain competitive.

New technologies reshape asset valuation and risk

Electrification, automation, and AI are rapidly changing how equipment is designed, used, and valued. These technologies enhance productivity, but they also introduce uncertainty in terms of collateral value, depreciation, and residual forecasting.

Manufacturers like Caterpillar are advancing intelligent, connected machinery that operates on shorter innovation cycles. This dynamic makes it more difficult to apply traditional residual models, especially for high-tech assets where software updates, battery lifespan, and AI capabilities can significantly affect long-term value.

In response, equipment leasing lenders are refining their asset management strategies. This includes adjusting recovery assumptions, enhancing market data inputs, and offering more flexible lease terms based on usage or performance metrics.

Replacement demand overtakes expansion

Businesses remain cautious about large-scale capital investment, but aging fleets and rising maintenance costs are driving continued demand for equipment replacement. According to the Equipment Leasing & Finance Foundation’s U.S. Economic Outlook, replacement demand is expected to be the primary driver of equipment investment in 2026, while expansion-related investment remains constrained due to high interest rates and economic uncertainty.

The Foundation’s report emphasizes that while total equipment and software investment is expected to grow modestly, most activity will focus on upgrading or maintaining essential equipment, particularly in transportation and construction sectors where productivity and compliance pressures are high.

For equipment leasing lenders, supporting replacement activity means offering lease structures that prioritize flexibility, reliability, and cash flow predictability over long-term growth financing.

Governance and compliance shift from reactive to strategic

The growing use of automated decisioning tools and AI-driven processes has increased regulatory scrutiny. Financial institutions are now expected to demonstrate control over their models, data inputs, and decision outcomes—especially in credit underwriting.

The Office of the Comptroller of the Currency (OCC) outlines expectations for model risk management, while the FDIC emphasizes the reputational and operational risks of weak governance. The NIST AI Risk Management Framework also provides structure for implementing responsible AI systems, including transparency and bias mitigation. Equipment leasing lenders are formalizing governance frameworks to meet these expectations. This includes documented model validation procedures, regular audits of automated workflows, and controls that ensure fairness in credit decisioning.

Moving forward with purpose

In 2026, equipment leasing lenders are expected to deliver speed and automation without compromising risk management, data quality, or regulatory alignment. The current environment demands clear operational priorities: digital integration, credit discipline, and defensible governance.

Institutions that execute well on these fronts will be positioned to serve their borrowers more effectively while maintaining institutional resilience.

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A panel of experts from top regulatory supervisory agencies compiled 10 AML hot topics to look out for in 2022

AML and cybersecurity in 2026

Criminals are exploiting gaps between cybersecurity defenses and anti-money laundering (AML) controls, making it critical for financial institutions to build stronger connections between these risk areas. As fraud schemes become more data-driven and cyber-enabled, the convergence of AML and cybersecurity programs is no longer optional; it is essential.

Cybercriminals are increasingly leveraging online platforms, real-time payments, and emerging technologies to move illicit funds more quickly and covertly. In 2026 and beyond, financial institutions that adopt integrated strategies and apply data-driven AI tools across cyber and AML functions will be better equipped to detect threats early, meet regulatory expectations, and maintain customer trust.

Siloed functions increase exposure

At many community financial institutions, AML and cybersecurity responsibilities have traditionally been handled in separate departments. AML and fraud teams monitor transactional activity and customer behavior, while cybersecurity teams focus on external threats, such as phishing, malware, and system vulnerabilities. This separation made sense when risks were more compartmentalized.

Today’s financial crimes are increasingly complex, often beginning with a cyber event and ending with a financial transaction. Without collaboration across teams, institutions risk missing early warning signs or failing to connect related pieces of information. In some cases, this has led to delayed investigations or missed opportunities to prevent losses.

These blind spots can have serious consequences, including regulatory scrutiny, financial impact, and reputational harm. Building stronger connections between AML, fraud, and cybersecurity teams enables institutions to develop a more comprehensive picture of risk and respond more effectively.

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Integration for better risk management

The rise in business email compromise, ransomware, cryptocurrency laundering, and data breaches underscores the need to unify AML and cybersecurity efforts. When AML and cybersecurity teams collaborate, they can correlate cyber indicators with financial activity. This strengthens detection and enhances the quality of cases filed with law enforcement or regulators.

The FBI’s Internet Crime Complaint Center (IC3) reported that U.S. institutions lost over $16 billion in fraud in 2024. These losses have persisted into 2025 with no signs of slowing. Institutions that treat these events as separate issues will fall behind. Funds obtained through cybercrime must still be laundered, underscoring the importance of connecting AML and cyber programs to manage risk effectively.

The following scenario illustrates the difference a combined program can make when it comes to investigating suspicious activity:

A financial institution may notice a surge in business email compromise attempts, including phishing emails targeting finance staff. Their cybersecurity team flags suspicious login activity tied to foreign IP addresses and unauthorized attempts to access business accounts. At the same time, AML staff may observe a pattern of new accounts conducting high-velocity transactions shortly after initial funding.

If the institution had integrated its AML and cybersecurity tools, investigators would be able to use “accept without post” functionality to delay outgoing payments and investigate further. Behavioral analytics can detect mule activity, allowing the case team to quickly file a Suspicious Activity Report (SAR) that includes critical cyber indicators, such as IP addresses and virtual wallet information. Law enforcement can then use this information to connect related cases and trace the flow of illicit funds.

Support for integrating AML and cybersecurity tools

FinCEN’s advisory on cyber-enabled crime encourages institutions to incorporate cyber elements such as IP addresses and virtual wallet IDs into suspicious activity reports. These details help law enforcement connect financial and cyber evidence, improving investigations and outcomes. Although this guidance is not new, it reflects the growing expectations of regulators. Including data-driven AI insights from threat feeds and forensic tools enhances both detection and reporting.

As institutions plan for 2026 risk management, staffing evaluations will play a critical role. Effective convergence of AML and cybersecurity requires specialized knowledge in both disciplines, especially as artificial intelligence and machine learning become increasingly common in surveillance tools.

AML staffing assessments can help institutions:

  • Identify gaps in skill sets or coverage areas
  • Allocate resources strategically across overlapping functions
  • Prepare for increased fraud activity tied to digital channels and emerging threats
  • Support continuity planning for key roles, such as the AML officer or fraud investigator

Staffing assessments also demonstrate regulatory readiness and help ensure that compliance functions remain effective, even in the face of turnover or increased workload.

The role of predictive analytics and AI in financial crime detection

As the financial crime landscape evolves, so must your institution’s approach to detection and reporting. Data-driven AI tools help institutions identify anomalies and emerging trends more quickly, but their effectiveness depends on continuous validation and refinement.

Incorporating model governance practices is now an expectation. Financial institutions should document how input variables are selected, justify threshold settings, and perform routine validations to ensure AI model outputs remain reliable. These practices not only enhance accuracy but also enable institutions to meet regulatory expectations for explainability in AI models and informed risk-based decision-making.

By applying above-the-line and below-the-line testing techniques, institutions can improve the effectiveness of their AML and fraud detection systems. These approaches allow teams to identify which alerts were missed (below the line) and which alerts were triggered but ultimately deemed irrelevant (above the line). Incorporating this type of backtesting helps fine-tune thresholds, reduce false positives, and ensure that high-risk activity is not overlooked. This ongoing validation process demonstrates a risk-based approach to monitoring that regulators increasingly expect. Predictive intelligence is a forward-looking capability that gives institutions a proactive edge in identifying and responding to new threats.

2026 readiness checklist for AML and cybersecurity

The following are key actions your institution can take now to bridge security gaps:

  • Conduct a joint staffing assessment across AML and cybersecurity teams
  • Integrate cyber threat intelligence into AML monitoring systems
  • Perform above-the-line and below-the-line testing
  • Enhance SAR narratives with cyber-related data fields
  • Invest in data-driven AI tools and backtesting capabilities to strengthen detection

The bottom line

AML and cybersecurity functions are converging out of necessity. Institutions that take steps now to integrate data, systems, and teams will be better equipped to address the risks ahead. Whether it is preventing instant payment fraud, aligning with FinCEN guidance, or navigating new regulatory scrutiny, your institution’s readiness will depend on people, processes, and technology working in harmony. With the correct data and the right tools, financial institutions will not only respond to threats but also anticipate and mitigate them.

 

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Lending strategy for credit unions 

Member business lending is growing again at credit unions, driven by improved liquidity and renewed demand from small businesses. But as portfolios expand and average loan sizes increase, rising delinquencies signal that risk management must keep pace with origination. In 2026, successful member business lending will depend on disciplined portfolio oversight, strategic partnerships, and a long-term view of member needs.

This article covers these key topics: 

The state of credit union business lending

Member business lending has long played a critical role in how credit unions support small businesses and local communities. However, credit union member business lending has historically been constrained by regulation, most notably the lending caps established under the 1998 Credit Union Membership Access Act and related NCUA rules. These limits have shaped the scale, structure, and growth strategies of member business lending programs for decades.

Despite these constraints, demand for member business lending has remained consistent. According to the Federal Reserve’s Small Business Credit Survey, approximately 7% of small business credit applicants have sought loans, lines of credit, or cash advances from credit unions each year since 2019, demonstrating steady interest in credit union–based member business lending options.

More importantly, credit unions are competitive when they participate in member business lending. SBCS data shows that in 2023, credit union approval rates for business loans, lines of credit, and cash advances were comparable to small banks and traditional nonbank lenders, with 51% of applicants fully approved and 24% partially approved. The success factor lies in how member business lending programs are structured, staffed, and managed over time.

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Speed and risk management are pain points to successful SMB loans

The MBL cap limits the amount of business loans a credit union can make, but for some credit unions, the restriction has also become a barrier to entry. Due to this cap, some credit unions are hesitant to invest time and resources in establishing small business loan programs.

To be successful in business lending, it’s essential for credit unions to focus on areas where they have control: processes. Digitizing and automating the business lending process allows for credit unions to drastically improve time- and cost-savings. From online loan applications to automated loan decisioning, today’s technology enables credit unions to make lending decisions quickly and support greater loan volumes.

If all loans require the same amount of time – regardless of size – your credit union has little incentive to make small-business loans. For some credit unions, a $20,000 loan and a $2,000,000 loan may go through largely the same origination process, resulting in the cost to originate the loan outweighing the benefit. Technology enables credit unions to streamline their lending process by electronically processing tax returns, reducing and eliminating manual data entry, and automatically scoring and decisioning loans, among other benefits. Business loans can be some of the most paperwork-intensive loans offered, and these technologies enable credit unions to scale business loans, making them profitable investments for their members. 

Risk management's role

Smooth origination is only one part of successful member business lending. Managing a member business lending portfolio through economic cycles, interest rate changes, and borrower stress is significantly more complex.

During the late 2010s and early 2020s, many credit unions benefited from historically low interest rates and exceptionally low delinquencies across their member business lending portfolios. According to the NCUA, delinquency rates at federally insured credit unions reached multi-decade lows during this period.

That environment has shifted. In 2025, member business lending activity rebounded, but early signs of credit stress began to emerge. NCUA quarterly data show that while loan balances increased year over year, delinquency rates also rose, indicating a more normalized credit cycle. For credit unions, this means member business lending success now depends as much on monitoring, analytics, and new tools for proactive risk management as it does on origination volume.

Volumes are back

After a challenging period marked by liquidity pressure and muted demand, member business lending volumes increased in 2025. NCUA data shows that total loans outstanding at federally insured credit unions grew year over year in both the first and second quarters of 2025, reflecting a broad rebound in lending activity, including member business loans.

However, growth within member business lending has been uneven. Industry data suggests that loan dollar volume has grown faster than loan counts, indicating a shift toward larger average member business loan sizes—often tied to commercial real estate. This trend increases concentration risk within member business lending portfolios and reinforces the need for disciplined oversight.

SBA loans as a growth track

Credit unions that want to expand their business lending opportunities and support local businesses and entrepreneurs may consider participating in the Small Business Administration (SBA) loan program.

Loans guaranteed by the U.S. Small Business Administration provide incentives for institutions to lend money to businesses that might not otherwise qualify for term loans. These loans help to bolster local economies by providing capital to small businesses and entrepreneurs. But SBA loans aren’t a magic bullet for business lending. Many financial institutions shy away from SBA loans, due to their reputation of being onerous, complex, and expensive.

To mitigate some of the complexities involved with SBA lending, credit unions can leverage SBA lending technology to help customize and streamline the underwriting and decisioning process for SBA loan application, as well as integrate FRANdata technology, which transfers all franchisor data and eliminates hours of research into franchisees or gambling on the performance of the franchise.

Participations are up, but so are credit quality pressures

Loan participations have re-emerged as a strategic lever within member business lending. After slowing during the liquidity crunch of 2022–2023, participation activity increased alongside improved balance-sheet conditions.

NCUA call report data shows that loan participation balances rose in 2024 and continued to increase in 2025, signaling renewed cooperation among credit unions engaged in member business lending. Institutions without the staffing or infrastructure to originate member business loans at scale are increasingly using participations to meet portfolio goals while managing concentration and regulatory limits.

When used strategically, loan participations can help credit unions expand member business lending capacity, diversify risk, and maintain consistent production without overextending internal teams.

Credit quality trends also deserve close attention. NCUA data shows that the delinquency rate for federally insured credit unions increased year over year in 2025, reaching 0.91% in the second quarter. While still manageable, rising delinquency levels signal increasing stress within loan portfolios—including member business lending portfolios.

Effective member business lending management requires early detection and intervention. Monitoring borrower behavior, property tax performance, and collateral conditions—essentials of effective risk grading—remains essential. In some cases, managing stressed member business loans may require outside expertise, as workouts and collections demand a different skill set than origination.

The future of member business lending

Member business lending has consistently been one of the most impactful ways credit unions serve their communities. As portfolios grow larger and more complex, credit unions must invest in member business lending infrastructure with the same rigor applied to origination growth.

This includes staffing, technology, analytics, and partnerships that support long-term portfolio health. Demand is also evolving. Many businesses formed during the pandemic years are now maturing and seeking more sophisticated financial services—ranging from SBA loans to working capital lines of credit and treasury management.

The current environment offers credit unions a timely opportunity to reset their member business lending programs for sustainable success

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AI, fraud detection, and other community financial institution priorities for 2026

As 2026 begins, community financial institution leaders are balancing innovation with persistent market pressures. Insights from Abrigo’s annual customer webinar and survey reveal five key areas that are shaping community financial institution priorities in 2026: AI adoption, fraud mitigation, deposit strategies, data utilization, and operational efficiency.

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AI adoption is accelerating, but not without barriers

The pace of AI implementation continues to pick up, with more than 75% of surveyed institutions reporting they are adopting or planning to adopt AI tools in 2026—a threefold increase from the previous year. Popular use cases include loan decisioning, fraud monitoring, allowance narratives, and onboarding efficiencies. However, barriers remain. Top concerns include data quality, limited internal expertise, and regulatory uncertainty. Community financial institution priorities in 2026 must include upskilling teams and implementing AI in controlled, explainable ways to meet operational goals and regulator expectations.

Deposit competition remains intense

As market competition and rate pressure persist, deposit strategy has emerged as a core concern. Institutions are turning to data analytics to refine their pricing strategies, manage liquidity risk, and better understand customer behaviors. The ability to make data-driven decisions quickly is becoming a differentiator. 

Despite growing access to dashboards and reporting tools, only 26% of surveyed institutions consider themselves “very effective” at using data for decision-making. Community financial institution priorities in 2026 must address this gap. Investing in platforms that centralize data and deliver curated insights can help leaders move from reactive to strategic. Better data usage supports more informed loan decisions, more effective risk management, and a stronger customer experience.

Fraud is evolving—and financial institutions are responding

Fraud remains a top risk, with check and wire fraud being the primary concerns. The coming year brings increased focus on ACH and FedNow fraud as these payment rails become more widely adopted. Community financial institution priorities in 2026 include investing in tools that provide real-time visibility and leveraging platforms that reduce both fraud losses and staff burden. One institution reported intercepting a $190,000 counterfeit check with the help of Abrigo Fraud Detection, underscoring the tangible value of a proactive approach.

Artificial intelligence has quickly become both a red flag and a green light for consumers. According to Abrigo Fraud Survey data,  while concern about AI is rising, so is trust in how it can be used to prevent fraud. In 2025, 44% of consumers and an impressive 69% of small business owners stated that they would feel safer if their institution used AI-powered fraud detection. People are beginning to accept that fraudsters are using advanced tools, and they want their banks and credit unions to fight back with equally sophisticated defenses.

Doing more with less

Community financial institutions continue to face headwinds around staffing and resource limitations. Many are leaning into technology partnerships that allow them to automate workflows and redirect staff to higher-value tasks. Whether it’s modernizing the loan origination process or improving fraud detection, automation is not about replacement—it’s about enabling institutions to work smarter, not harder.

As the industry moves forward, community financial institution priorities in 2026 are clear: reduce risk, increase efficiency, and stay ahead of customer and regulatory expectations. With the right tools and partners, institutions can turn today’s challenges into tomorrow’s opportunities.

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