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A rundown of the latest hot topics surfaced by nearly 1,000 bankers and industry experts.

From uncertainty over tariffs and regulations and the impact on small businesses to fraud threats and AI opportunities, here's what attendees at Abrigo's ThinkBIG 2025 were talking about.

Key topics covered in this post:

The fog of tariffs and economic uncertainty
How to handle regulatory rollbacks
Fraud threats topping concerns
AI isn't coming-it's here
Prepare the balance sheet for change

Issues and common themes bankers should be ready to tackle

Nearly 1,000 people — including bankers representing 365 financial institutions — gathered at Abrigo’s ThinkBIG 2025 conference this week in Orlando, Florida, for three intense days of hallway huddles, hands-on labs, and the kind of candid peer conversations you can’t stream later.

A few consistent takeaways surfaced as lenders, credit leaders, risk managers, BSA Officers, and fraud fighters hustled from break-time networking to sessions led by more than 80 industry experts.

Financial institutions have plenty of opportunities and risks ahead in 2025 and beyond, but below are some of the common themes and imperatives that speakers and attendees said are shaping the next 6-12 months.

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1. Keep small businesses resilient amid economic uncertainty

Banks and credit unions understand the role small businesses play in their communities. But with the economic outlook murky and business demographics shifting, speakers at ThinkBIG 2025 challenged institutions to reassess the opportunity and how they’re supporting this segment—and to sharpen the tools, products, and services they use to do it efficiently.

Ginger Siegel, North America Small Business Lead at Mastercard, noted that some six million new small businesses launched in 2024 alone, a dramatic increase from fewer than 900,000 in 2018. But inflation, labor shortages, and tariffs are leading many to put off investments and capital requests, several speakers said.

Without the cash provided during COVID, the uncertainty is tough for small businesses, and it’s tough for lenders trying to make credit decisions. One commercial banker described how a meeting with a “perfect” borrower to “check boxes” related to tariff risk described how 70% of its suppliers were in China, and it wasn’t sure how it will adjust.

To help businesses stay resilient, speakers encouraged banks to connect frequently with small businesses and pair relationship banking with modern data and technology. That includes alternative data for underwriting, such as real-time receipts, as well as automation with small business lending software to compete with fintechs’ faster decision times. It may also mean offering different products or services beyond checking, savings, and loans.

“Small businesses don’t want to be sold to, they want to be spoken to,” Siegel said. They often need help with cybersecurity, succession planning, and managing cash flow, which is why Mastercard recently built an expense management solution for small businesses.

Several institutions described bundling treasury management and fraud-protection services to boost efficiency and deepen relationships. These value-added services not only strengthen margins, they also make it harder for small businesses to leave when rates shift.

2. Stay disciplined—even if some rules ease

As regulatory priorities shift in Washington, some bankers may be tempted to relax. But speakers at ThinkBIG 2025 urged caution: Even if the tone softens temporarily, examiners haven’t let up—and the next administration could bring a sharp pivot.

“Don’t take your eye off the ball,” advised Laurel Sykes, EVP and Chief Risk Officer at American Riviera Bank. “This is a four-year administration, and deregulation is definitely necessary and helpful. But executive orders are merely shifting priorities. They don’t do anything about the existing regulations we still have to comply with.”

In addition, Sykes reminded attendees that bankers have seen multiple cycles of regulatory whiplash. “I remember days when we had to do look-backs of loan decisions for three, four years because a new administration came in and all of a sudden fair lending was the big thing again.”

Sticking with practices that are good for customers and the institution regardless of the regulatory environment also applies to anti-money laundering and fraud efforts, speakers said. Abrigo Director of Client Engagement Terri Luttrell said risk assessments remain foundational to the pillars of BSA, even as certain rulemakings stall. Keeping the risk assessment current helps institutions stay focused on their highest-risk areas, regardless of regulatory noise.

Auditors, too, illustrate the need to continue “doing the right thing.” CECL-related scrutiny continues, especially around qualitative factors, governance practices and documentation.

“You need a management team that is actively reevaluating what’s going into your model,” said Mark Scriven, principal, Elliott Davis. “It’s not a set-it-and-forget-it process.”

Abrigo advisors also emphasized that stress testing, backtesting CECL models, and sensitivity analysis are increasingly expected as part of sound model governance.

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3. Stay ahead of fraud and financial-crime evolution

Fraud continues to evolve, and financial institutions are seeing firsthand that it’s not just a consumer issue. It’s a business risk and a reputational threat. In fact, over 57% of small business owners said they have experienced fraud, and only 16% feel extremely prepared against fraud, according to a recent Abrigo survey of more than 1,000 respondents.

Several ThinkBIG 2025 sessions underscored how fraudsters are moving faster, targeting small businesses and older adults with increasingly sophisticated schemes. From persistent check fraud to pig-butchering to cryptocurrency schemes, teams must be aware of the latest fraud trends to have proactive conversations with customers, and they must use fraud detection tools sufficient for their institution’s risk profile.

Fraud may be unavoidable—but with the right strategy, it doesn’t have to be unmanageable.

Another common fraud risk is that small business owners often underestimate their risk, despite the fact that 50% of all cyberattacks hit small businesses. Yet most financial institutions don’t ask about cyber protection in the underwriting process. “You can underwrite a business that has a beautiful balance sheet and one cyberattack can wipe them out,” Siegel of Mastercard said.

4. Use AI where it already works—then scale deliberately

AI was a major focus at ThinkBIG 2025, and not just in the sessions. It showed up in hallway conversations, live demos, and candid comments from attendees who’ve seen firsthand how the technology can save time and reduce risk. Abrigo AI-driven tools that draft loan memos, answer policy questions, or streamline loan review are no longer theoretical—they’re in production and delivering value.

Beta solution AskAbrigo, for example, lets staff search internal policy documents in plain language, returning clean answers with citations. Other tools, like Abrigo's Loan Review Assistant and Narrative Generation, also in beta, help speed up credit analysis while flagging missing data for human review.

“In five years, every banker will have an AI co-pilot—not replacing people, empowering them,” predicted Ravi Nemalikanti, Abrigo’s Chief Product and Technology Officer. “It's going to be similar to how we use Microsoft Office today. Can anybody imagine a life without Excel?”

Adoption has accelerated. More than three-quarters of respondents in a recent Abrigo survey said they are adopting or planning their approach to AI. That's nearly triple the share responding the same way a year earlier.

But many attendees expressed frustration: They understand the business case for AI but feel that their institutions are moving too slowly. In conversations throughout the conference, bankers said they’re eager to experiment. However, meaningful adoption is difficult without executive-level support to develop clear guardrails and approval processes. Many expressed the need for educational AI resources for bankers.

Several panelists already using Microsoft’s Copilot suggested financial institutions start small so they can prove value as they build policies and plans. Starting with clean, reliable data and documenting prompt inputs and assumptions are key to scaling safely.

David Christiansen, Chief Credit Officer from First County Bank in Stamford, Connecticut, and others urged their peers to walk before trying to run. “You don’t have to take the whole bottle of aspirin; you can take a couple at a time.”

AI doesn’t replace bankers—it frees them up to do more of what they do best. The real question isn’t whether it works. It’s whether your institution is ready to use and compete with it.

Abrigo has developed an AI readiness checklist to help financial institutions navigate their way to implementing AI tools needed to remain competitive.

5. Plan for liquidity risks and rate changes

If the last two years taught anything, it’s that liquidity risks can move faster than institutions are ready for. At ThinkBIG 2025, bankers revisited past lessons and got advice for ensuring models, policies, and assumptions are ready for whatever is ahead.

Speakers encouraged institutions to revisit their stress-testing and funding frameworks now—not when rates or deposits move. The more tightly connected your data and decision-making processes are, the faster your institution can adapt to what’s next, said Dave Koch, Managing Director of Abrigo Advisory Services.

Treasury specialists from Bloomberg emphasized that disjointed systems and manual processes remain top challenges for liquidity forecasting. But they also pointed to AI and machine learning as tools to close the gap.

6. Technology and human connections: The formula for remaining relevant

At ThinkBIG 2025, one idea cut across discussions of AI, risk, credit, and compliance: Connection—among bankers, between departments, and with customers—isn’t just a cultural asset. It’s a strategic one that can help financial institutions compete with a growing list of competitors in an uncertain environment.

Panelists and attendees shared how they’re pairing technology, including AI, not to replace staff but to free them up so bankers can focus on judgment calls, personal interactions, and local market nuance.

“We want to help you be more efficient, stay compliant, manage risk, and surface the insights buried in your data so you can make better decisions,” said Abrigo CEO Jay Blandford.

Financial institutions may not be able to avoid every pothole. But they can prepare so that their bank or credit union is sturdy enough to absorb the shocks.

“We’re not just a vendor—our role is to be on board with you," he said. "With the right people, technology, and data, you can spot the rough patches early and stay focused on the destination, while others are stuck fixing flats."

Financial institutions that use technology to better meet customer and operational needs can still center their people and processes on what remains core: asking the right questions, listening carefully, and acting intentionally.

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Changes to CECL rules finalized

On April 30, the FASB met to revisit and finalize important decisions regarding its proposed changes under CECL for Purchased Financial Assets (PFAs). If you’ve been following this project, you know it’s been a journey, but the end is now in sight, and the board made some important calls that community financial institutions (CFIs) need to be aware of.

Here’s a brief recap of what happened, why it matters, and how it could affect your institution.

This article covers these key topics:

What FASB decided
Why these changes matter for community financial institutions
More CECL details and adoption dates

What was decided?

The board voted in strong favor of what they called "Alternative A1" – a narrower, more targeted approach that fine-tunes CECL rules without blowing up what institutions have already built. That’s important.

Key takeaways from Alternative A1:

All loans acquired in a business combination are automatically considered seasoned and will use the gross-up accounting approach.
For other purchased loans, like those acquired in asset sales or the secondary market, a new seasoning test will determine if the gross-up method applies.
The gross-up method continues the accounting used today for PCD assets, where expected credit losses are added to the purchase price to establish amortized cost.
Credit cards and HTM debt securities are excluded from these changes.

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Why the FASB CECL changes matter for community financial institutions

If your institution has undergone a merger, you’ve likely seen how CECL treats acquired loans differently than originated ones. The timing of expected loss recognition can distort capital, confuse investors, and create what many have called a “day-one double count.”

This update is a big deal because it starts to fix that. The FASB listened to investor and preparer concerns, especially from institutions like yours, and decided to expand the use of the gross-up model in a way that makes it more intuitive and more consistent with economic reality.

That means:

Less capital volatility after acquisitions.
More transparency for stakeholders.
Fewer one-off manual workarounds just to get the accounting to tell the right story.

Clarifying details and adoption dates

The seasoning test will be applied on a loan-by-loan basis (no portfolio-level shortcuts) to each loan acquired through asset purchases outside of business combinations.
The new approach only affects transactions going forward. It won’t require restating past activity.
The final rule is expected to take effect for fiscal years beginning after December 15, 2026.

Assuming the final ASU is issued sometime in 2025, CFIs will have two key timing options:

Early Adoption: You can adopt the new rules as early as 2025 or 2026, provided your financial statements for that year have not yet been issued. If you adopt during an interim period, you can apply the new guidance either from the beginning of that interim period or from the beginning of the full fiscal year that includes that interim period.
Mandatory Adoption: If you don’t adopt early, the new rules will be required for fiscal years beginning after December 15, 2026, which means 2027 for calendar-year CFIs.

This flexibility gives CFIs time to prepare, while also offering the opportunity to implement sooner, particularly if you have upcoming acquisitions where the gross-up model may provide clearer results.

What’s next

We’re now awaiting the release of the final ASU, which is expected sometime in 2025. Once issued, CFIs can begin preparing for implementation, whether choosing early adoption or waiting until the mandatory effective date. In the meantime, it’s a good opportunity to assess how your institution accounts for acquired loans and whether your systems are ready for this change.

We’ll continue monitoring the timeline and guidance closely and will share updates as more details become available.

Final takeaways

If you would like to dive deeper or stay up to date on how things progress, FASB has a dedicated project page with updates, documents, and meeting notes: FASB Topic 326 – Purchased Financial Assets Project.

For CFIs navigating CECL while growing through acquisitions, this is a welcomed refinement. It acknowledges the operational realities and cost pressures facing smaller institutions while still providing investors with more meaningful information.

These changes don’t overhaul CECL, but they do improve it in a targeted and thoughtful way. That’s a win for CFIs and the stakeholders who rely on their financial reporting.

Whether you’re reassessing model configuration, evaluating an upcoming acquisition, or simply trying to align accounting with operational goals, having a trusted, flexible CECL platform in place can help ease the lift. Look for CECL software and services that are designed to adapt to evolving guidance and support institutions through transitions like this one.

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Utilizing loan review worksheet for consistent analysis

Analytical inconsistency is a persistent challenge in the loan review profession, often leading to wildly different approaches across reviewers. Striking the right balance is essential—and a structured tool like the loan review worksheet can help reviewers achieve clarity, consistency, and more meaningful assessments.

Standardization matters when assessing asset quality

One of the things Abrigo Senior Consultant Kent Kirby observed over his loan review career is that analytical consistency is not a hallmark of the loan review profession.

“We’re all over the board,” he said. “On one end are maniacs like me. As my wife and daughter will readily attest, I’ll carry an analysis far beyond what’s necessary to make sure every detail is crystal clear. At the other extreme are those who provide so little analysis that readers are left guessing at even the basics: When was the company founded? What are the terms and conditions of the facility? These analysts often spend more time cutting and pasting from prior work than developing new, relevant insights.”

Neither extreme is desirable. Both drive the reviewer in charge crazy as they battle inconsistent individual approaches on their way to the true objective: assessing asset quality, administrative competency, and the future trajectory of the segment under review.

Fortunately, there’s a tool that helps eliminate these extremes and foster a consistent, thoughtful approach: the loan review worksheet.

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What is a loan review worksheet?

A worksheet is simply a series of standardized questions on a subject loan review cares about — underwriting, governance, monitoring, etc. Its purpose is to systematically collect structured, comparable, and analyzable information to support sound, data-driven conclusions.

Specifically, worksheets help to:

Assess borrower risk: Gather updated financial, operational, and compliance information to evaluate repayment ability.
Test underwriting discipline: Verify that loans were originated and monitored according to policy and sound credit principles.
Identify emerging credit issues: Surface early signs of borrower stress, collateral deterioration, or covenant breaches.
Enable portfolio monitoring: Aggregate responses to detect risk patterns across industries, geographies, or loan types.
Support documentation and defensibility: Create a clear record of what information was considered during analysis for regulators, auditors, and management.

In short, loan review worksheets turn scattered, subjective input into organized, actionable insight for targeted and effective loan reviews

Five benefits of using worksheets

Here are five key benefits of using worksheets in analytical work:

Standardization of data collection
- Ensures every analyst answers the same questions, presented in the same way.
- Improves consistency, making results easier to compare and quantify.
Efficiency and scalability
- Quickly gathers data across many credits with relatively low effort.
- Helps analysts stay focused, avoiding the extremes of over- or under-analysis.
Objectivity and reduced bias
- Minimizes bias toward particular credits or lenders.
- Captures responses openly (often on the line sheet), promoting comparability.
Quantitative and qualitative insights
- Provides numeric scoring and rankings, as well as open-ended narrative insights.
- Supports both statistical and thematic analysis.
Data archiving and reusability
- Stores responses electronically for easy retrieval, comparison, and analysis.

Worksheet examples for loan reviewers

A common question when creating loan review worksheets is: Should I build one comprehensive worksheet or several smaller ones?

Experience has shown that a series of smaller worksheets (no more than 10–15 questions each) works best.

Some worksheets should be mandatory (e.g., credit analysis).
Others can be optional depending on the nature of the review (e.g., collateral evaluation).

Here are two simple examples — not best practices, but illustrations:

Example: Credit analysis worksheet (250 words or less per response)

Briefly describe the background of the borrower(s).
Do you arrive at the same conclusion as the original approval? (Yes / Yes with qualifications / No—explain.)
Quality of primary repayment analysis: (Conservative / Reasonable / Liberal—explain.)
Quality of secondary repayment analysis: (Conservative / Reasonable / Liberal—explain.)
Quality of projections: (Acceptable / Unacceptable / N/A—explain.)
Quality of sensitivity analysis: (Acceptable / Unacceptable / N/A—explain.)
Are the guarantors a source of strength? (Yes/No—explain; if Yes, assess global cash flow.)
Do you agree with the assigned risk rating? (Explain.)
Credit strengths: (Explain.)
Credit weaknesses: (Explain. Were they identified by the line? Were mitigations put in place?)
Financial trend of the borrower: (Improving / Stable / Erratic / Declining — explain.)
Any follow-up questions for the Relationship Manager?

Example: Controls worksheet (250 words or less per response)

What exceptions were cited by the bank? (Choose from list.)
What exceptions were missed? (Choose from same list.)
Do mitigating factors justify exceptions? (Yes/No—explain.)
How do you rate ongoing borrower monitoring controls? (Adequate/Inadequate—explain.)
Are covenants effectively monitored? (Yes / No / Missing—explain.)
If substandard, should customer be moved to non-accrual/charged off? (Select option and explain.)

Each worksheet mixes quantitative (trackable/scorable) and qualitative (explanatory) responses.

By keeping each worksheet focused, analysts zero in on risks that matter — and avoid wasting time on superfluous activities. Worksheets bring structure, consistency, and objectivity to loan review. They help the reviewer in charge bridge different analytical styles and generate forward-looking, actionable insights that truly add value.

If you’re not using worksheets yet and want to start, reach out to [email protected] to set up a time to discuss how worksheets can add structure, insight, and real value to your loan review program.

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The value of loan review worksheets: Bringing structure to analysis

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The case for complex credit: A framework for simplifying challenging loans

A loan reviewer's perspective on complex credit deals

Abrigo Senior Consultant Kent Kirby says he always gravitated toward the messiest, most chaotic credits on the review list during his loan review career. They were challenging — like solving a complex puzzle — making the work more engaging. Bankers often avoid these kinds of deals because of their complexity, not because they’re inherently bad. But Kirby says that usually, that’s not prudence — it’s missed opportunity. The key is learning how to understand and manage complexity. Read his perspective below.

What makes a credit complex?

Two factors typically drive credit complexity: volatility and correlation.

Volatility is rapid and unpredictable change. We all know someone with a volatile mood — calm one moment, explosive the next. The same applies to lending. Take ag lending commodities, for example. Perhaps corn is the seventh-largest concentration in a bank’s portfolio, and 30 days later, it is the second-largest — without a single additional ear of corn in a bank’s collateral. It was all price movement.

Correlation refers to how one variable affects another. The strength of that relationship can vary widely. A loose correlation: speeding doesn’t always mean getting a ticket. A tight one: a mother telling her son, “If you do that, you will go in time out.” In credit, correlations exist everywhere — but in complex credit, they tend to be stronger and drive much of the volatility.

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Let’s look at two examples:

Discretionary income
Most people don’t have large piles of idle cash. They must prioritize essentials like food, shelter, and transportation. What's left is discretionary. People cut back during periods of high inflation — when real wages lag. That impacts industries like casual dining or movie theaters. These sectors are tightly correlated with shifts in discretionary income.
Public policy
We rarely think of public policy as a correlation factor, but it can be huge. Take tax credits for solar panels and windmills. When those incentives are removed or threatened, entire projects stall and revenues plummet. Lending on assets driven by policy incentives introduces political risk — and I generally avoid lending on anything political. Tax credits sit high on that list.

Differentiating risk in complex credits

Complex credits often come with layers of risk. A helpful way to assess them is by separating key risks from trigger risks.

Key risk is the fundamental threat that causes actual loss. You can’t avoid it, only mitigate it.
Trigger risk is a condition that could activate the key risk. It may or may not occur, and even if it does, it might not cause harm.

Take commodity lending. The key risks are price fluctuation and collateral control. Trigger risks might include weather events, geopolitical conflicts, or even market rumors—things that might influence price but don’t guarantee impact.

Misdiagnosing a trigger risk as a key risk can lead to poor decisions. For example, imagine a construction loan backed by pre-leased tenants. If a tenant like Party City goes bankrupt 18 months into a 3-year build, reacting as if the whole project is at risk could be a mistake. The developer still has time to backfill, restructure, or adjust. Recognizing the true key risk — the ability to refinance or sell upon stabilization — is critical.

Analyzing complex credits

I’ve never been a fan of the overly ritualized, checkbox-driven approach to credit analysis. It often misses the real risk. My framework — especially useful for complex credits — is straightforward:

Use of proceeds: Why do they want the money? Not “working capital” or “business purposes” — give me the real reason.
Repayment source: When and how do I get paid back? What’s the real source, and when does it kick in?
What can go wrong: What events could impair repayment?
Likelihood of failure: Sensitivity analysis should match the repayment structure — not just be done for form's sake.
What’s Plan B?
- What’s the borrower’s contingency plan?
- What’s yours?
Participation purchased (if applicable): Can the agent bank manage this credit? Should someone else take the lead?

Case study: Lending to religious organizations

Church loans are among the most complex — and consistently misstructured — credits bankers make. These aren’t real estate loans. They’re special-purpose properties with limited resale markets and PR risk galore.

Let’s break it down:

Key risk: The sustainability of contributions from major donors. Most churches don’t repay loans from operating income; they rely on capital campaigns.
Use of proceeds: Building or renovating sanctuary or “life center.”
Repayment: Two sources — capital campaign funds and asset sales (existing structures or donations in kind). Campaigns typically span 2–5 years with pledges paid over time (monthly, annually, or one-time). Asset sales often supplement repayment.

Making 20-year amortization loans secured by the church building is a common tactic. Why? That’s not the repayment source. Instead, funds should go into escrow, with structured disbursements tied to campaign receipts and pay based on a fixed schedule, with a maturity balloon after 5 years. Oversimplified? Yes — but you get the idea.

What can go wrong: The 80/20 rule applies —often, a few large donors give most of the money. If one of those donors dies, will their families continue to honor the pledge?
Borrower’s Plan B: Are they encouraging planned giving from major donors? Nonprofits do this all the time — why not churches?
Your Plan B: "Extend and pretend" isn’t a strategy. Churches aren’t traditional businesses. Many prioritize mission work over debt service. At minimum, mission spending should be capped or suspended during loan repayment. Contributions and asset sales should be escrowed, and assets should be secured as “abundance of caution” collateral to ensure payment before you release your lien. Your real reliance is on donations, not the building.

Conclusion

A banker’s job is to serve a broad community — including borrowers with complicated needs. Avoiding complexity isn’t prudence; it’s abdication. Understanding what makes a credit complex, how to structure around it, and where to focus risk analysis is what separates a good banker from a great one. It's not just about saying “yes” or “no.” It’s about saying “yes, if.”

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Graphic showing how to develop a small business lending program

A practical framework built for speed, efficiency & community impact

Supporting small businesses in your community while meeting the bank or credit union's expectations around risk and reward demands a well-structured, deliberate small business lending program. Here's how to build one.

Key topics covered in this post:

Simply offering loans to small businesses doesn't cut it.
Start with a team, a policy, and a decision model.
Leverage technology and change management.
Implement and monitor the program.

Meet community needs and risk/reward expectations

Every town has them: the bakery that sponsors the Little League team, the florist that delivers last-minute bouquets for school dances, the landscaper who hires local teens each summer. These small businesses are more than customers. They’re part of the economic and social fabric of the communities that financial institutions serve.

Supporting these essential contributors to local economies—while also meeting a financial institution’s expectations around risk and return—requires more than offering loans. It demands a deliberate, well-structured program designed to make small business lending scalable, compliant, and sustainable.

With competition from fintechs offering fast, digital-first experiences, financial institutions have an opportunity to stand out by being both efficient and relationship-driven. That starts by approaching small business lending not as a sideline activity, but as a focused capability worth building intentionally.

The six steps below outline a practical framework for building a small business lending (SBL) program designed for speed, efficiency, and community impact.

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6 Steps for creating a small business lending program

1. Build a team and policy

This is not a Nike moment where an institution can just do it. Small business lending needs to be a focus—a program. An institution must be able to say, “We are small business lenders,” not just “We do small business lending.”

The first priority is clearly defining the “who” and the “how.” Will there be dedicated production staff or underwriters? Will loan officers manage both commercial and small business portfolios? Define roles and responsibilities and identify a team to own the process from start to finish.

Next, create a small business lending policy supported by the institution’s risk appetite. This policy should live within the core credit policy and include:

How an SBL loan is defined (vs. a commercial loan)
Allowable and excluded products or industries (e.g., cannabis-related businesses)
Dollar thresholds (minimums, maximums, or total exposure limits)
Target markets
Acceptable collateral (e.g., no CRE loans)
Required documents
Credit risk attributes for decision models
Staff responsibilities

Keep it simple. Focus on reducing the burden for borrowers and staff while getting the information needed to make sound credit decisions.

2. Create decision models

Decision models allow lenders to move quickly and consistently. The goal is to eliminate unnecessary complexity so small businesses can access capital faster.

Scorecards that combine quantitative factors like debt service coverage ratios and credit scores with qualitative inputs such as management experience or industry concentration help standardize decisions across the institution. That consistency mitigates variation across lenders and underwriters, promotes compliance, and makes exceptions easier to audit and track.

Attributes can be weighted, and outcomes assigned, such as “auto-approve,” “recommend for review,” or “decline.” It’s the art and science of lending, combined.

3. Leverage technology

Technology plays an essential role in making SBL programs efficient and scalable. Borrowers expect a seamless digital experience—not just during application but throughout the life of the loan.

Prioritize small business lending technology that enables:

Online or mobile-first applications
Automated underwriting and credit decisioning
Real-time decision tracking
Prefilled, auto-generated loan documents
Core system integration for booking loans

API integrations can streamline KYC/KYB checks, pull data from credit bureaus and deposit accounts, and connect to accounting systems like QuickBooks. Reducing time spent on each deal lowers cost, improves NIM, and supports scalable growth.

4. Address the cultural shift

Often, the biggest challenge in building a small business lending program is not technology—it’s the cultural shift. Adopting faster underwriting, streamlined workflows, and different risk thresholds can feel uncomfortable in institutions used to traditional commercial lending processes.

Tone at the top is critical. Without leadership buy-in, clear communication, and staff training, change can stall. People may revert to old habits when under pressure.

Help teams understand the vision: Why is this shift happening? How will it strengthen the institution and benefit the community? The goal is for this to become the way business is done, not just a new way.

5. Implement the program

Once built, the SBL program must be rolled out thoughtfully. That means collaboration across marketing, sales, credit, risk, and compliance. Each function plays a role in ensuring success.

Marketing should create a plan to generate awareness, both internally and externally. Promote the program online, in branches, and through local business groups. Avoid a “build it and they will come” mindset. Generate momentum with consistent outreach.

Start with the bank or credit union’s existing customer or member base. Review deposit relationships to identify prospects. Connect with accountants, attorneys, and local economic development agencies to build a referral network.

Don’t stop at the loan. Offer bundled services that support small business needs—from treasury management to merchant services—and make ongoing interactions seamless, whether it’s payments, statements, or loan servicing.

6. Monitor and report

This is not a one-and-done step. Ongoing evaluation is essential to ensure the program delivers on expectations.

Establish benchmarks: What defines success? What metrics will be tracked?

Monitor the borrower experience. Are applications being abandoned? Is the approval rate where it should be? Are there too many manual reviews? These may indicate policy or model adjustments are needed.

On the portfolio side, track loan types, pricing, terms, charge-offs, and performance by decision tier. Make sure the portfolio is healthy, diversified, and aligned with strategic goals.

Decision models must evolve with experience and results. Continual monitoring and adjustment keep the program effective and responsive.

Not just any community financial institution

A well-developed small business lending program furthers the mission of community banks and credit unions. It supports the businesses that keep local economies running and strengthens the institution’s position as a trusted partner. When designed with intention and executed consistently, it helps institutions not just be a community bank or credit union—but be the community bank or credit union.

This post is based on online training offered by Abrigo in partnership with the American Bankers Association. Abrigo is a Premier Partner with the ABA.

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6 questions & answers on how generative AI is shifting the landscape

Abrigo's Director of Applied AI, Sriram Tirunellayi , shares advice and insight into AI, its role, and how it can power the future of banking.

Generative AI for safer, smarter growth

As a seasoned leader in data science and AI for financial services, Sriram Tirunellayi brings a practical perspective to the evolving role of artificial intelligence in banking. He holds multiple patents for innovative machine-learning and AI applications that address some of the industry’s most complex challenges. Today at Abrigo, he drives the strategy and roadmap for generative AI and applied AI/ML products, helping financial institutions harness emerging technologies to achieve safer, smarter growth. As Director of Applied AI, Tirunellayi is focused on bridging innovation with trust, finding new ways to power the future of banking through responsible AI.

In this Q&A, he shares how generative AI is shifting the landscape — not by replacing human expertise, but by amplifying it. He discusses where banks and credit unions can find the greatest opportunities to apply AI thoughtfully, why governance and explainability are critical, and how emerging technologies like agentic AI could reshape financial services. His insights offer a clear, balanced view for institutions looking to embrace AI as a long-term strategic capability.

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What role does generative AI play in banking today?

Generative AI is one of the most exciting innovations in recent times that has the potential to make a profound impact across every aspect of banking and lending.

There are plenty of applications in banking that use traditional machine learning, a form of AI that is very good at finding patterns in structured numerical data. However, these applications are typically focused on solving specific tasks such as assessing credit risk, detecting fraud, or optimizing marketing spend.

Generative AI is unique in the sense that it works very well on unstructured data, leveraging foundational large language models (LLMs) that have been trained on web-scale data. Today's LLMs don’t just understand language; they follow instructions and respond with the fluency of a human expert. This has opened up a whole new set of applications in banking, where generative AI can be used to address challenges that were previously out of reach, such as:

Understanding free-form customer interactions
Distilling insights from complex documents
Generating personalized communications at scale
Reimagining how bankers interact with information.

Generative AI introduces a new layer of intelligence that enables automation and amplification of human expertise. For the first time, we have not just a tool but an intelligence amplifier that processes complexity, uncovers insights, and enhances human judgment in real time. This shift from prediction to understanding and interpretation is what makes this moment exciting and different.

Abrigo serves 2,500 financial institutions. What is your advice for banks and CU looking to adopt AI effectively?

First and foremost, it’s important to recognize that at its core, AI is advanced technology powered by algorithms and data — not a superintelligent entity. This framing matters because it sets realistic expectations for what AI can and cannot do, especially in complex industries like banking and lending. Rather than thinking of AI as a replacement for human expertise, it’s more helpful to view it as a powerful tool that can amplify human judgment, streamline time-intensive processes, and unlock new opportunities where traditional methods fall short.

The pace of innovation in AI is accelerating, and for banks and credit unions, keeping up is a strategic imperative. Financial institution leaders should prioritize building internal awareness, understanding how generative AI is evolving, where it’s being applied, and what it means for the future of financial services. As with adopting any emerging technology, it is crucial to understand both its potential and its boundaries. This ensures financial institutions deploy it in ways that are secure, compliant, and aligned with long-term business and regulatory objectives.

To identify meaningful opportunities, prioritize high-value areas marked by high repetition, time-intensive processes, and complex decision-making that depend on unstructured data and expert judgment, such as credit underwriting, loan servicing, compliance monitoring, and customer communications. These are domains where generative AI can amplify expertise, streamline operations, and unlock new efficiencies.

Equally important is establishing a strong governance framework from the outset, ensuring responsible use, managing risks, and maintaining regulatory alignment. Starting with targeted pilot programs in well-scoped use cases allows institutions to learn, adapt, and scale with confidence.

Over time, the institutions that succeed will be those that treat AI not as a one-off initiative, but as a long-term capability—embedded into strategy, operations, and culture. The key is to start early, learn continuously, and scale thoughtfully.

Credit risk modeling and underwriting have traditionally relied on historical data. Compared to traditional methods, what improvements have AI-driven models made in assessing borrower risk and improving the borrower experience?

If you peek inside the underwriting box, three major steps shape a credit decision.

First is the gathering of borrower data. One of the key risks in lending stems from information asymmetry — an imbalance of information between the lender and borrower. Traditionally, lenders have relied heavily on credit bureau data, which provides useful insights but can miss important, real-time changes in a borrower’s financial situation. Expanding the scope of data to include alternative sources — such as bank transactions, real-time updates on financial statements, income, and employment status — helps reduce this gap and gives lenders a more complete and timely understanding of borrower risk.

AI plays a critical role by labeling and categorizing alternative data, such as bank transactions, to provide better visibility into cash flows and improve the accuracy of downstream ML models. Large language models (LLMs) are also being applied to read diverse formats of financial statements and automate the spreading of key financial information, significantly enriching underwriting data inputs with greater speed and precision.

Second is predicting the borrower's future payment behavior. AI models now leverage cash flow data and alternative datasets to more accurately predict credit risk, helping lenders better determine who to lend to and on what terms. By tapping into broader data sources, financial institutions are also expanding access to credit for underbanked and populations with thin credit files. Additionally, AI-powered analytics help assess the performance of automated decision models and identify potential biases, supporting the move toward fairer, more transparent lending practices.

Third is the final decisioning process. Credit analysts define the risk criteria, underwriting policies, and decision rules that govern how borrower data and risk scores are evaluated. AI assistants increasingly support this work by gathering relevant information from multiple sources and drafting the initial credit memo narrative, significantly reducing time and manual effort. AI also helps automate complex underwriting logic, define test cases, and identify potential gaps in decisioning frameworks — driving greater efficiency, consistency, and governance across credit operations.

Compliance teams often worry about AI creating rather than solving compliance challenges. What advice about compliance risk do you have for BSA Officers or risk managers evaluating AI solutions? Are there ways to balance automation and the human element?

It is important to recognize that while AI solutions can enhance compliance operations, they can also introduce new risks if governance is inadequate. My advice to BSA Officers and risk managers evaluating AI tools is to start with a comprehensive risk management framework that emphasizes the following:

model transparency
explainability
fairness testing
clear documentation of model design and validation

Institutions must ensure that human oversight remains embedded within all AI-supported compliance activities, particularly for high-risk functions such as transaction monitoring, customer due diligence, and sanctions screening. Automation can assist in prioritizing and surfacing potential issues, but final decision-making and accountability must always reside with qualified compliance professionals.

Finally, AI governance should be treated as an active, ongoing process — not a one-time certification exercise. Strong programs will rely on cross-functional teams that continuously audit, refine, and improve AI systems as regulatory expectations and risks evolve.

One of the biggest concerns for financial institutions is explainability—regulators and decision-makers need to understand AI-driven outcomes. How does your team ensure AI-powered solutions are transparent and interpretable?

Explainability is fundamental to the way we design and deploy AI in Abrigo's solutions. Our approach begins with prioritizing inherently interpretable models wherever possible, particularly in high-stakes areas such as credit decisioning. When more complex models are necessary, we implement dedicated explainability layers that clearly trace how specific inputs contribute to each outcome, ensuring transparency at every stage.

We also embed “human-in-the-loop” processes throughout the model lifecycle. Subject matter experts validate AI-generated outcomes against structured test scenarios, supported by AI evaluation tools (AI evals) that systematically measure outputs against defined benchmarks such as factual accuracy, completeness, relevance, and clarity. This combination of expert review and automated evaluation ensures a rigorous, unbiased assessment of model quality. Only models that meet or exceed our established thresholds are approved for production use.

Finally, we maintain a comprehensive governance framework that includes detailed model documentation, audit trails, independent validation, and ongoing monitoring and re-validation of AI systems. This approach ensures that our solutions consistently meet regulatory expectations, uphold ethical standards, and sustain stakeholder trust over time.

What emerging AI-driven banking applications excite you the most right now?

One area that excites me is breakthroughs in “mechanistic interpretability.” This is where researchers are beginning to map the "thought processes" of large language models. It's like building an MRI for AI: a way to look inside, map how these systems think, and understand the concepts they're using. As we learn to see more clearly into these models, we have a real opportunity to build AI that supports fairer credit decisions, smarter risk assessments, and more transparent banking experiences — not just faster ones.

I’m especially excited about the area of agentic AI. Unlike traditional generative AI applications, which rely heavily on human prompts, agentic AI applies sophisticated reasoning, planning, and self-correction to tackle complex, multi-step problems on its own. These systems are designed to work more like human teams — managing tasks independently, collaborating dynamically, reflecting on outcomes, and improving with each cycle.

A recent example of agentic AI involves Capital One’s “Chat Concierge” application. It moves beyond basic chatbot interactions by breaking down a complex task — like purchasing a car — into multiple coordinated steps handled by different AI agents. Instead of simply answering questions, the system can autonomously schedule appointments, estimate trade-in values, and manage other related tasks, working collaboratively to guide the user through a multi-step process with minimal human intervention. The goal? Make car-buying a less overwhelming and more enjoyable experience.

While agentic AI holds enormous promise, it is still early; many systems remain brittle, error-prone, and reliant on human oversight. Yet its true potential is clear: to move beyond automation and build intelligent systems — and financial services — that are not just faster and smarter but genuinely aligned with human needs.

By expanding access, promoting fairness, and rebuilding trust, agentic AI can help shape a future where technology serves people, not the other way around. That possibility is what excites me most.

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BSA/AML exam prep: From exam room to boardroom

As political shifts influence Washington’s regulatory landscape, financial institutions face new challenges and opportunities. The 2025 administration change has already paused new rulemakings and delayed the effective date of several recent regulations, including those related to anti-money laundering/countering the financing of terrorism (AML/CFT) and the Corporate Transparency Act.

While the tone may suggest regulatory relief, community financial institutions should not interpret this as a signal to ease off their compliance efforts. Instead, institutions should embrace this moment as an opportunity to modernize their approach to BSA/AML exam prep and demonstrate leadership-level commitment to a strong culture of compliance.

What does this mean for future regulatory exams?

This perceived reduction in regulatory burden may mean financial institutions will see more flexibility from regulators. Many are asking what will happen to FinCEN’s priorities, and some anticipate that there will be a greater focus on truly risk-based examinations and program effectiveness over technical compliance. But let’s be clear: BSA/AML exam prep still matters.

Changes in tone or examiner staffing do not mean regulators are abandoning core expectations. Institutions must still demonstrate strong internal controls, timely reporting, and a culture of compliance. These must be reflected not just in procedures but also in the actions of leadership and the board.

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Why preparation isn’t just a checkbox

If you’ve been through an exam recently, you know how quickly things can shift from manageable to overwhelming. The first day letter alone can feel like a firehose of documentation requests. However, those who prepare proactively by maintaining current risk assessments, conducting staffing assessments, and documenting clearly and thoroughly position themselves to not only survive an exam but also use it as a meaningful touchpoint with regulators.

Getting ready starts well before that first day letter arrives. Most exam teams give about 2–4 weeks’ notice, but institutions that treat exam prep like a continuous process are more confident when it’s go time.

Three steps to stronger BSA/AML and fraud exam readiness

Streamline your foundation by starting with the basics:

Are your AML/CFT and sanctions risk assessments up to date?
Do you have a fraud risk assessment?
Can your team demonstrate timely resolution of alerts, sanctions matches, and SAR filings?
Are your policies and procedures current, consistent, and centralized?
Do your procedures match actual day-to-day processes?

Even more importantly, do you have the documentation to show all of this? Regulators increasingly expect decisions and alert dispositions to be well-supported. Every case note should read like an examiner might see it, because they will.

Technology plays a significant role here, too. Transaction monitoring software must be optimized based on your institution's risk. Too many, or too few, alerts will draw criticism. Dashboards and automated reports can help reduce the manual scramble when exam or board reporting time hits.

Turn findings into leadership insights

One of the most significant opportunities after an exam is translating technical findings into operational value. When compliance leaders frame issues around the level of risk and impact rather than regulatory language, they engage executives and boards more effectively.

An example of achieving value from a finding may look like this:

Exam finding: Greater than 30-day backlog in alert review
Compliance insight: Insufficient staff to keep pace with alert volume
Leadership takeaway: Time to reassess staffing or enhance monitoring systems

Create a post-exam action plan that clearly defines ownership, timelines, and how progress will be tracked. Following up regularly and tying each item to business impact not only builds accountability but also shows your institution is serious about continuous improvement. Be sure to meet all deadlines in your plan to show commitment to improvements.

Communicate clearly with the board

Boards don’t want technical jargon or data dumps. What they need is a high-level understanding of how the institution is managing risk and where strategic investments may be required. A graph or chart as a one-look understanding of the data will go a long way.

A few statistics to highlight include:

Trends in SAR activity by typology, both AML and fraud
Alert resolution timelines and backlogs
Progress since the last exam, and how findings have been addressed
Risk scoring changes linked to customer behavior or product risk

Use visual dashboards or heatmaps to make key points stand out. And always connect metrics to the institution’s strategic risk appetite. That’s what turns compliance from a cost center into a strategic advantage.

Stay ahead with smarter staffing decisions.

Staffing continues to be a hot-button issue and is frequently seen in content orders. Examiners want to know: Is your program appropriately resourced? And just as importantly, can you prove it?

Red flags that may signal the need to re-evaluate staffing:

Alerts aren’t reviewed within 2-4 weeks
SARs are not filed timely and by the 30-day deadline
You’re struggling to clear sanctions hits daily
New fraud typologies or regulatory changes have increased your team’s workload

If any of those sound familiar, consider a formal staffing assessment. Tools like Abrigo’s AML staffing calculator can help you model needs based on current and projected volumes—and make the case for additional resources with leadership or the board.

Mock exams: Your secret weapon

Mock exams are one of the most effective ways to strengthen your BSA exam prep. They give you a chance to test documentation quality, evaluate policies and procedures, and simulate interactions with examiners—all before the stakes are real.

Define your scope upfront. Are you reviewing the full AML/CFT program to include sanctions? What about fraud? Will you focus on high-risk customers and enhanced due diligence reviews or look across the board?

Once the mock exam is complete, debrief with leadership. Share where things went well and where improvements are needed. Then turn those insights into clear action items, so your real exam doesn’t come with surprises.

What to do right now

Even in a potentially less intense regulatory environment, now is not the time to let your guard down. Instead, use this moment to strengthen your program fundamentals:

Align risk assessments with actual exposure, and tie those results to resources
Improve documentation practices with the assumption that every decision will be reviewed
Simplify your story for the board by focusing on trends, improvements, and what comes next

Purpose-driven BSA/AML exam prep isn’t only about satisfying regulators, it’s about building a resilient, transparent program that reflects your institution’s values and risk appetite. By investing in the right tools, aligning your team with your risk profile, and framing compliance in terms that leadership understands, you’re not just preparing for your next exam; you’re shaping a stronger AML/CFT program for your institution. None of us has a crystal ball, but whether regulation tightens or flexes, proactive preparation will always pay off.

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FinCEN GTO for the Southwest border

FinCEN implemented a new Geographic Targeting Order requiring money services businesses in 30 zip codes near the U.S. Southwest border to file Currency Transaction Reports for cash transactions between $200 and $10,000. It is designed to curb illicit cash flows linked to drug trafficking and transnational criminal activity—two of FinCEN’s national AML/CFT priorities.

Key topics covered in this post:

What this means for banks and credit unions.
Why FinCEN issued the GTO.
The strategic opportunity for financial institutions.

FinCEN GTO for Southwest border: What this means for banks and credit unions

The Southwest border between Mexico and the United States has long been a hotbed of illicit narcotic activity. In an effort to curtail this flow of dirty money coming into the U.S. banking system, on April 14, 2025, the Financial Crimes Enforcement Network (FinCEN) implemented a new Geographic Targeting Order (GTO) requiring money services businesses (MSBs) in 30 ZIP codes near the U.S. Southwest border to file Currency Transaction Reports (CTRs) for cash transactions between $200 and $10,000. This new threshold is significantly lower than the standard $10,000 CTR requirement. It is designed to curb illicit cash flows linked to drug trafficking and transnational criminal activity—two of FinCEN’s national AML/CFT priorities.

While this GTO does not directly apply to banks or credit unions, it does impact MSB customers and members. It also presents significant implications for traditional financial institutions that serve or monitor those entities. Understanding the operational effects of the FinCEN GTO for Southwest border areas is essential, especially for those in AML/CFT compliance or risk oversight roles.

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Why FinCEN issued this GTO

Although deaths due to drug overdoses have declined slightly in the U.S., the opioid epidemic continues to be a significant issue, with an estimated 87,000 deaths reported in 2024. The GTO supports a broader federal initiative to combat the flow of fentanyl and other narcotics into the U.S.

In early 2025, the Trump Administration issued Executive Order 14157, designating major drug cartels as Foreign Terrorist Organizations (FTOs) and Specially Designated Global Terrorists (SDGTs). This designation gives law enforcement and financial regulators additional tools to block access to the U.S. financial system and go hard after these dangerous organizations.

FinCEN’s latest GTO reinforces this approach by lowering the cash transaction reporting threshold to detect small-dollar activity, which is often used to structure or obscure illicit money flows.

Geographic targeting order requirements for Southwestern counties

The FinCEN GTO applies to MSBs located in 30 ZIP codes across California (including Imperial, San Diego, and Cameron counties) and Texas (including El Paso, Hidalgo, Maverick, and Webb counties).

Covered MSBs must:

File a CTR for any cash transaction between $200 and $10,000, within the 15-day deadline.
Include the keyword “MSB0325GTO” in Field 45 of Part IV of the CTR.
Maintain records of these transactions for five years after the GTO expires.

This latest geographic targeting order does not replace existing obligations, so covered MSBs must still:

File standard CTRs for transactions over $10,000.
Submit Suspicious Activity Reports (SARs) for any transaction involving or aggregating to $2,000 or more when appropriate.
Consider voluntary SARs for transactions structured to avoid the $200 threshold.

What it means for banks and credit unions

While the FinCEN GTO for Southwest border regions doesn’t impose new filing requirements on financial institutions, banks that serve MSBs, particularly in or near the affected areas, should take proactive steps. Here are some recommendations for making sure you truly know your customers:

Understand customer exposure

Review your customer base to determine whether you serve MSBs that operate in the listed ZIP codes. This includes businesses such as check cashers, money transmitters, or prepaid providers that may now fall under the GTO.

Refresh due diligence efforts

The GTO offers a timely reason to review enhanced due diligence (EDD) measures for MSBs, particularly in high-risk geographies. Ensure you have clear records of where MSBs operate and how they comply with regulatory requirements.

Monitor for compliance challenges

Be aware of the operational burdens your MSB clients now face. Some may struggle to adjust systems or train staff for lower-dollar CTR filings. Monitoring for unusual gaps in transaction reporting or increased risk behaviors can help banks detect when an MSB may be failing to comply.

Prepare for the examiner's questions

Regulators may ask about your institution’s exposure to MSBs affected by the GTO. Being able to demonstrate awareness of which clients are impacted—and any monitoring enhancements you’ve implemented—can strengthen your overall compliance posture.

Watch for structured activity

Even outside the affected ZIP codes, small-dollar cash transactions designed to avoid reporting requirements may increase. Ensure your transaction monitoring systems are tuned to flag behavior that could indicate structuring around the $200 threshold.

A strategic opportunity for financial institutions

The FinCEN GTO for Southwest border regions reflects a broader expectation that financial institutions, while not directly responsible for these new filings, will remain engaged partners in detecting and preventing financial crime. This is an opportunity for AML/CFT Officers to strengthen MSB onboarding and monitoring practices, align program efforts with national priorities, and collaborate with MSB clients on education and risk management.

Duration of the GTO and what’s next

The GTO is effective through Sept. 9, 2025, and may be renewed depending on evolving enforcement priorities. During this period, MSBs in the covered regions will face heightened regulatory scrutiny and increased reporting burdens, adding complexity to their operations and, by extension, to the institutions that serve them. Financial institutions that bank these MSBs should take steps now to validate their risk assessments, monitoring strategies, and due diligence procedures. If your team could benefit from additional support, Abrigo Advisory Services offers deep experience in helping institutions assess, document, and strengthen MSB oversight programs, ensuring your bank remains confident and compliant in a changing regulatory environment.

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Finding and managing vulnerabilities in credit portfolios

Fresh reminders of why it's important to manage credit concentration risk are everywhere. Effective loan review is a key element of managing concentration risk in loan portfolios.

Key topics covered in this post:

Recent regulator comments on overseeing concentration risk
Concentration risk management framework
How credit risk review can help manage concentrations
Overcoming barriers to concentration risk insight

Credit concentration risk: Navigating the landscape

Whether it’s uncertainty over potential tariff impacts, elevated interest rates, or commercial real estate (CRE) credit health, fresh reminders of the importance of managing credit concentration risk are all around financial institutions.

A recent Federal Reserve newsletter for community banks reiterated guidance and supervisory expectations for prudent concentration risk management practices. It’s a good reminder that in today’s environment, risk managers and credit professionals should reexamine how they identify, assess, and communicate portfolio vulnerabilities.

An effective credit risk review function is a key element of managing concentration risk in credit portfolios. Modern loan review processes can help financial institutions satisfy examiners while accommodating the staffing pressures facing many loan review departments.

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Regulator comments on overseeing concentration risk

Concentrations often arise naturally for community banks and credit unions due to the types of businesses and industries that they serve in their communities. A bank in an urban corridor might understandably have a CRE credit concentration. A rural credit union might amass numerous agricultural loans.

Concentrations can also develop from over-exposure to specific borrowers, collateral types, or loan products. Concentrated credit exposure may build gradually. But a shift in rates, asset values, or borrower conditions can quickly turn that exposure into vulnerability. “Concentration risk must be managed in conjunction with credit, interest rate and liquidity risks; as a negative event in any category may have significant consequences on the other areas, as well as strategic and reputation risks,” says the NCUA.

The Fed’s June 2024 Community Banking Connections newsletter noted that concentration risk, particularly commercial real estate (CRE) risk, has remained a central supervisory focus since the Great Recession—and recent history has added a new layer of urgency.

Banks’ relative exposures to CRE (as a share of assets) increased in recent years, according to the St. Louis Federal Reserve. In addition, charge-off rates on CRE loans (excluding farmland) have increased from 0.02% in Q4 2022 to 0.26% in Q4 2024, FRED economic data from the St. Louis Fed shows. During a recent Abrigo credit risk webinar, 51% of bank and credit union credit risk professionals responding to a poll reported an increase in problem loans over the last three months, and 42% said their borrowers are seeing declining economic conditions.

The newsletter for community bankers also noted that the 2023 failures of Silicon Valley Bank and other regional institutions highlighted the dangers of unmonitored deposit concentrations, emphasizing that concentration risk isn’t limited to the asset side of the balance sheet.

Indeed, managing asset concentration is among the areas that “have become top priorities for regulators,” wrote Andrew Giltner, Lead Examiner within the Chicago Fed’s Supervision and Regulation Division, in the Community Banking Connections newsletter.

The regulatory message for financial institutions is clear: Know where you’re concentrated, understand the risk dynamics, and maintain the capital and oversight necessary to weather downturns.

Concentration risk management framework

Credit concentrations “should not necessarily be avoided by bankers because doing so may neglect the banking needs of their community members,” the article said. However, the degree and level of credit concentrations affect a bank’s risk profile. To control concentration risks, bankers need a comprehensive risk management framework.

A strong framework, according to the article, includes:

A strategic plan incorporating the institution’s desired asset or funding concentrations and its commensurate policies, procedures, and risk limits.
Management information systems that are tailored to appropriately capture concentrations so that management and the board can more easily provide oversight.
Capital planning that accounts for concentrations to maintain an acceptable level of capital.
Contingency plans to raise capital or reduce concentration levels when predetermined parameters are triggered.

The newsletter points to Supervision and Regulation (SR) letter 07-1, “Interagency Guidance on Concentrations in Commercial Real Estate,” for more details on strong risk management practices related to having a CRE loan concentration. Those practices include conducting portfolio stress testing and sensitivity analysis, market analysis, and having an effective credit risk review function. The National Credit Union Administration, too, has noted the importance of an independent review function in managing concentration risk in credit union loan portfolios.

How credit risk review can help manage concentrations

While some credit teams think of loan review as a compliance mechanism for retrospectively validating individual loan risk ratings and verifying the adequacy of loan documentation, the function of credit risk review has more strategic value tied to handling concentration risk.

Ongoing, independent analysis by loan reviewers represents a critical link in an institution’s defense against concentration risk. Continuous monitoring in loan review helps determine whether large or correlated loan concentrations align with the financial institution’s risk appetite and lending policies. It can provide context to detect emerging vulnerabilities that might lead to elevated losses if adverse conditions impact the concentrated segments.

A modern, data-informed loan review framework helps financial institutions connect the dots between individual loan file findings and systemic portfolio risks. It identifies patterns across loans that share similar characteristics, whether those be:

industry
geography
collateral type
borrower structure, or
funding source.

Overcoming barriers to concentration risk insight

As noted earlier, one challenge with keeping an eye on any concentration of credit risk is that credit accumulations tied to a characteristic can build quietly. Loan review cycles that are segmented or siloed by lending team or product type can make it difficult for decision-makers to fully recognize how that exposure is aggregating—or deteriorating—until it’s too late.

Time-consuming, manual processes and turnover in loan review staff or constrained staff can also hamper the institution’s ability to recognize increasing loan exposure or deteriorating trends in a particular category. And it’s clear that many loan review departments are facing such challenges in their day-to-day work.

A recent Abrigo loan review webinar found that 56% of respondents consider time-consuming manual processes their biggest challenge in the loan review process. Another 24% said the top challenge is limited staff resources, and 12% said it’s identifying emerging credit risk.

That’s where standardized, software-enabled loan review processes become critical. Most institutions have a firm grasp on their largest credit relationships. But understanding aggregate exposure across similar loans—especially when loans span business lines, geographies, or periods—requires the ability to extract structured insights from the credit data already being collected.

Centralizing review data and applying consistent risk rating methodology across the portfolio helps credit risk teams:

Tag and analyze loans by concentration categories (e.g., NAICS codes, property types, geographic zones)
Identify sector-specific risk trends in risk ratings, exceptions, or performance metrics
Compare actual exposure to risk tolerances set by policy or board-level limits
Detect participation layering or overexposure in sectors that have experienced recent stress
Surface actionable insights for management and the board before concentrations create systemic vulnerability

Using some loan review software, users can leverage concentration tracking dashboards and reporting features to drill down into high-risk segments and flag others for investigation. They can evaluate risk rating consistency and assess borrower performance within those concentrations. Abrigo’s DiCOM Loan Review Software has these features.

Abrigo Senior Consultant Kent Kirby, a retired banker with experience in all aspects of commercial lending, loan review, and portfolio management, has said that one reason identifying emerging trends can be difficult is that loan review analysis is resource-intensive, even when it’s automated.

Kent Kirby

Many loan reviewers, he said, are “so tired just doing the analysis, you never get around to doing the root causes and patterns.”

The newest feature available with DiCOM is aimed at addressing that. An AI-powered loan review assistant analyzes loan data and automatically generates insights. It uses generative AI to build narratives to quickly inform credit risk decisions aligned with an institution’s policies.

“Artificial intelligence allows you to do that initial analysis, to cut that time down so you can focus on root causes and patterns,” Kirby said.

Asking the right questions before the regulators do

Risk reviewers equipped with data-driven tools can provide insights beyond file-level observations. They provide strategic intelligence that can inform loan policy, underwriting standards, and capital planning.

Notably, such tools also allow loan review officers and credit analysts to communicate quantified risk trends clearly across the organization. Highlighting to leaders insights tailored to the institution’s unique risk profile will make it easier for senior management to make timely, well-informed decisions about credit concentration limits, capital buffers, and loan participation strategies.

That’s especially important in an environment where CRE vacancy rates are shifting, farmland values are responding to commodity volatility, and interest rates and the economy are placing pressure on debt service coverage ratios.

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Human smuggling indicators for financial crime professionals

New and stricter border policies mean human smuggling networks may shift in the near future. Learn what your financial institution can do to prepare.

What is human smuggling?

Human smuggling is a multi-billion-dollar industry for transnational criminal organizations and is once again in the national spotlight. In early 2025, the new administration in Washington wasted no time reinstating stricter immigration policies, resuming border wall construction, and ramping up law enforcement efforts to dismantle human smuggling at the border. These changes may reshape migration patterns, pushing more people into the hands of smugglers and creating more financial risk exposure for financial institutions.

At its core, human smuggling at the border is a profit-driven crime, illegally transporting people into the country to evade immigration laws. Smugglers, or “coyotes,” are motivated by money, and their operations are designed to maximize revenue—often at the expense of human life.

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Smuggling vs. trafficking: Know the difference

Human smuggling and human trafficking are often used interchangeably, but they are very different crimes. The Financial Crimes Enforcement Network (FinCEN) has added both to its list of eight national priorities, which resulted from the Anti-Money Laundering Act of 2020.

While both crimes are horrific, it is essential to understand the difference between human smuggling and human trafficking. According to HSI, human smuggling involves the provision of a service—typically transportation or fraudulent documents—to an individual who voluntarily seeks to gain illegal entry into a foreign country. The criminals behind this highly lucrative business seize the opportunity created by migrants' need or desire to escape poverty, lack of employment opportunities, natural disasters, conflict, or persecution.

Human trafficking, on the other hand, is a crime in which force or coercion is used to compel a person to perform labor, services, or commercial sex. Human trafficking gets much more exposure in the media and with law enforcement than human smuggling, but the latter can be just as deadly. Smuggling sometimes becomes trafficking—especially when migrants are extorted, held against their will, or forced into labor or sex work when they can’t repay inflated fees.

How smugglers operate

Smugglers are savvy. They’ve moved from word-of-mouth to full-on digital marketing. TikTok, WhatsApp, and Facebook all play a role in advertising services and coordinating logistics. Transnational criminal organizations run some smuggling operations, while others are small-time groups working locally. Either way, the payments tell a story, one that financial institutions may be the first to see.

Migrants often pay in stages, depending on how far they want to go and what risks they’re willing to take. That means you may see wire transfers or deposits from multiple people, structured to avoid detection, supporting one journey.

The cost of human smuggling at the border

According to Homeland Security Investigations (HSI), human smugglers typically exploit legitimate trade and travel routes to move individuals across borders. They may conceal migrants in cargo shipments, using vehicles, boats, boxcars, or tractor-trailers. At the border, human smugglers frequently supply false identification, alter or forge official documents, steal identities, and, in some cases, corrupt government officials to facilitate border crossings.

The individuals being smuggled often pay large sums of money for this illegal transport, and the conditions are rarely safe. From the smuggler’s perspective, payment is the priority; human life is secondary if considered at all. Many migrants die of thirst in deserts, perish at sea, or suffocate in containers in desperate search of a better life.  This is evidenced by the San Antonio, Texas discovery of 53 migrants—including children—who  died in a tractor-trailer as they attempted to enter the United States illegally. The smuggler abandoned the locked trailer in sweltering South Texas temperatures with no water.

What financial institutions can do

Behind every tragic news headline, there’s often a financial footprint. Smugglers are moving money through wires, funnel accounts, P2P apps, and other informal channels. That means banks and credit unions are in a unique position to help spot these networks early, and FinCEN is counting on them to do just that.

While the mechanics of smuggling have evolved, the guidance hasn’t changed. FinCEN’s January 2023 alert on human smuggling remains one of the most detailed roadmaps available for financial institutions. It outlines common typologies, behavioral red flags, and how institutions should report suspicious activity.

Due to a convergence of factors, human smuggling has become even more urgent for financial institutions to track. Migration into the United States, particularly along the southwest border, continues to soar, with over 2.9 million U.S. Customs and Border Protection encounters in 2024. At the same time, the reinstatement of Trump-era enforcement priorities is reshaping the landscape, bringing back large-scale detentions, expedited removals, and tighter asylum restrictions.

Meanwhile, the financial side of smuggling is evolving rapidly. Criminal networks are leveraging technology to move money faster, in smaller amounts, and through platforms that didn’t even exist a few years ago, making it harder for institutions to detect illicit flows.

FinCEN red flags

FinCEN’s 2023 alert was clear: financial institutions are a frontline defense against human smuggling, which deserves as much attention as drug trafficking or cybercrime. The red flags highlighted in the alert are still relevant today:

Transactions involving multiple wire transfers, cash deposits, or P2P payments from multiple originators from different geographic locations with no apparent business purpose.

Deposits made by multiple individuals in multiple locations into a single account with no apparent business purpose.

Currency deposits into U.S. accounts without explanation, followed by rapid wire transfers to countries with high migrant flows.

A “funnel account” in one geographic area receives multiple cash deposits, often in amounts below the cash reporting threshold, from which the funds are withdrawn in a different geographic location with little time elapsing between the deposits and withdrawals.

Frequent exchange of small-denomination for larger-denomination bills by a customer who is not in a cash-intensive industry.

Multiple customers sending wire transfers to the same beneficiary inconsistent with the customer’s usual business activity and reported occupation.

A customer making significantly greater deposits—including cash deposits—than those of peers in similar professions or lines of business.

A customer making cash deposits that are inconsistent with the customer’s line of business.

Extensive use of cash to purchase assets, such as real estate, and to conduct transactions.

Cash is used to purchase big-ticket assets like vehicles or real estate, but there is no apparent source of funds.

If your team sees signs like these, FinCEN wants suspicious activity reports (SARs) filed with FIN-2023-HumanSmuggling in the narrative and in Field 2. A crime does not have to be confirmed; a well-explained suspicion is enough.

The bottom line

Human smuggling isn’t only a border issue; it’s a financial one. It’s fast-moving and increasingly digital, but the signs are there if you know what to look for. Now’s the time for financial institutions to:

Train teams on relevant red flags

Deploy robust transaction monitoring systems to review customer activity that doesn’t align with known business or personal profiles

File SARs when suspicious patterns emerge, even if you’re not 100% sure what the crime may be

Stay current on FinCEN guidance and future alerts

Smuggling isn’t new, but the scale, tactics, and consequences are evolving quickly. Today’s smugglers operate like organized businesses, using digital tools, informal payment networks, and complex financial layering to move both people and money. Financial institutions, especialy those located near the border, are in a unique position to disrupt these operations by spotting suspicious activity early. The faster the detection, the sooner the harm can be stopped.

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