Key insights:

• • • SAR volume is significantly underreported — Continuing and amended filings add approximately 20% to the official count yet remain invisible in trend analyses.

    • Filing activity is highly concentrated — A few large financial institutions dominate SARs volume, meaning trends reflect their practices more than systemic changes.

    • Agentic AI will drive a surge in SARs — Agentic AI risks increased noise over actionable intelligence, without addressing the unresolved question of whether current filings yield meaningful law enforcement outcomes.

The Suspicious Activity Reports (SAR) that financial institutions file with the U.S. Treasury Department’s Financial Crimes Enforcement Network (FinCEN) provide valuable insight, although they may not offer a comprehensive picture.

Prior to meaningful discussions regarding the future of SARs, it is essential for the financial crime community to clarify what is being measured. In 2025, for example, SAR filings of more than 4.1 million, representing an almost 8% increase compared to the total number of SARs filed in 2024.

Every figure FinCEN has published reflects original SARs only. Continuing activity SARs, which represent roughly 15% of all filings, are submitted under the original Bank Secrecy Act (BSA) identification number and never appear as new filings. Corrected and amended SARs add another 5% on top of that. This makes the real volume of SARs activity approximately 20% higher than what is reported.

The average community bank files fewer than one SAR a week, while the largest institutions file more than 500 a day.

Recent FinCEN guidance giving financial institutions more flexibility around continuing activity SARs sounds significant on paper, but as former Wells Fargo BSA/AML chief Jim Richards points out: “It won’t change the reported numbers — because those filings were never counted to begin with.” Financial crime professionals need to keep that gap in mind every time a trend line gets cited.

2025 was steady, not spectacular

There were roughly 300,000 SARs filed every single month of 2025, and the most notable thing is that nothing notable happened. That is likely a first on the volume side and worth acknowledging, but beyond that milestone the year did not hand financial crime professionals anything noteworthy. In a space that has dealt with pandemic distortions, crypto chaos, and fraud spikes that seemed to come out of nowhere, steady volume and predictable patterns are a little surprising. A quiet data set, however, is not the same as a quiet landscape, and financial crime professionals who are reading stability as stagnation may find themselves flat-footed when the numbers start moving again.

For example, one of the most underleveraged insights in the SARs space is just how concentrated filing activity really is. The numbers are stark: The top four banks file more SARs in a single day than 80% of the rest of the banks file in 10 years, according to 2019 data from a .

The average community bank files fewer than one SAR a week, while the largest institutions file more than 500 a day. “50 a year versus 500 a day,” notes Wells Fargo’s Richards, adding that such asymmetry has real implications for how the financial industry interprets trends. Meaningful movement in SARs data, up or down, is almost entirely dependent on what a handful of mega-institutions decide to do.

Not surprisingly, money services businesses (MSBs) are the second largest filing category, and virtual currency exchanges are almost certainly driving recent growth there, even if outdated category definitions make that difficult to confirm directly. Credit unions round out the top three.

The filing philosophy hasn’t changed and shouldn’t

Regulatory noise occasionally suggests that institutions should be more selective about what they file. However, compliance and legal reality have not shifted. No institution has ever faced serious consequences for filing too many SARs, and the cases that result in enforcement actions, reputational damage, and regulatory scrutiny are consistently about missed filings or late ones.

“You’re not going to get in trouble from filing too much,” Richards says. “Nobody ever has, and I doubt if anyone ever will.” For financial crime professionals, the calculus remains exactly what it has always been — when in doubt, file. That posture isn’t going to change, and frankly it shouldn’t.

Yet, here is where the SARs space gets genuinely interesting. Agentic AI use in SARs filings — systems in which multiple AI agents work through a case from screening to decision to documentation — is beginning to move from concept to deployment. The impact on filing volume likely will be significant.

The risk is a system flooded with AI-generated SARs of variable quality, creating more noise for law enforcement to sort through rather than sharper intelligence to act upon.

Whereas a small team today might work through a handful of cases a week, AI-assisted workflows could push that into the dozens. Multiply that across institutions already inclined to file rather than miss something, and the result is a coming surge in SARs volume that could play out over the next two to four years.

“Agentic AI has the potential to be a game changer on how we do our work,” Richards explains. “But I believe it’ll guarantee that there will be more SARs filed and not necessarily better and fewer SARs filed.” Indeed, the critical point for the financial crime community to internalize is exactly that.

The risk is a system flooded with AI-generated SARs of variable quality, creating more noise for law enforcement to sort through rather than sharper intelligence to act upon. Once the largest institutions adopt agentic AI as a best practice, others will follow quickly, and regulators will likely be several steps behind.

The value question can’t wait

The has been in place since 2014. Yet after 12 years of filings, the financial crime community still lacks a clear public accounting of whether that data has produced actionable law enforcement outcomes.

So, the question Richards is asking is one the entire industry should be asking: “Has anybody asked law enforcement?”

This question reflects a larger challenge that the industry needs to confront more aggressively, especially as AI technology is set to dramatically increase filing volume across the board. Increasing the volume without improving how the information is used does not represent progress. If SARs are not generating real investigative value, the solution is not to file more of them faster — instead, the pipeline should be fixed before it grows any bigger.

You can find more about the challenges that financial institutions face in managing SARs here

Key insights:

• • • Convenience has outpaced consumer understanding —ĚýMany users treat apps, prepaid accounts, and rewards programs as simple payment tools, remaining unaware they are entrusting their money to entities with few safeguards.

    • Risk is no longer confined to traditional banks — Some of the most significant financial activities now occur within platforms and brands that do not resemble banks at all.

    • Opacity enables systemic vulnerability — The less transparent an institution’s obligations, leverage, and oversight, the easier it is for financial fragility, misconduct, and systemic risk to grow unchecked.

When you think of where money is held, you generally think of a bank. However, as we look at the financial landscape today, money is being held at a wide range of institutions that often have varying levels of safety and oversight. Entities from Starbucks to Visa to Coinbase hold money for individuals, effectively serving as a bank, but often without the regulatory framework that comes with it.

Behind the scenes, it can seem like . In its daily operation, it collects prepaid funds that resemble deposits, holds them as liabilities, and uses them internally — all without offering interest, cash withdrawals, or FDIC insurance. Starbucks’ rewards program holds $1.8 billion in customer cash, and if it were a bank, that would make it bigger, , than 85% of chartered banks, making the coffee chain one of the .

This dynamic extends well beyond coffee shops. “Popular digital payment apps are increasingly used as substitutes for a traditional bank or credit union account but lack the same protections to ensure that funds are safe,” warns the . If a nonbank payment app’s business fails, your money is likely lost or tied up in a long bankruptcy process.

Shadow banking

Think of a Starbucks gift card as a financial instrument. Technically it is one, but no one seriously worries about it being weaponized for any large-scale financial crimes. Most people’s concerns about a gift card is either losing it. The real concern lies not in lost gift cards, however, but in the broader trend: Nonbank institutions managing vast sums without commensurate oversight — and scale matters. A lost gift card is a personal inconvenience; but an unregulated institution managing billions of consumer dollars in leveraged capital is a systemic one.

Shadow banking encompasses credit and lending activities by institutions that are not traditional banks, and crucially, they do not have access to central bank funding or public sector credit guarantees. And because they are not subject to the same prudential regulations as depository banks, they do not need to hold as high financial reserves relative to their market exposure, allowing for very high levels of leverage which in turn can magnify profits during boom periods and compound losses during downturns.

The shadow banking ecosystem is diverse, and each segment of it presents distinct risks:

• • Hedge funds and private equity firmsĚý— Firms like Blackstone, KKR, and Apollo manage vast capital pools using leveraged strategies under limited oversight. Their size and borrowing levels may mean that market reversals can trigger rapid deleveraging, spilling risk into broader markets.
  • Family officesĚý— A private company or advisory firm that manages the wealth of high-net-worth families, these can operate with even less transparency and often outside direct regulatory scrutiny, enabling them to engage in extreme leveraging and posing risks of sudden collapse.
  • Nonbank mortgage lenders and FinTechsĚý— This group faces lower capital requirements than traditional banks, leaving thinner buffers to absorb losses during downturns, which can be especially concerning considering this sector’s rapid growth.
  • Crypto exchangesĚý— Like much of the cryptocurrency ecosystem, these exchanges operate in jurisdictional gray zones, complicating enforcement and enabling illicit financial flows.
  • Money market funds — While these are generally perceived as safe, they can suffer runs if confidence in underlying assets erodes, which can force fire sales that destabilize related markets.
  • Special Purpose Vehicles (SPVs) and Structured Investment Vehicles (SIVs)Ěý— These investment instruments allow large institutions to move risk off their balance sheets, rendering such activity invisible to regulators.

Shadow banking may be the single greatest challenge facing financial regulation. These non-traditional institutions act like banks, but without the safeguards that make banks accountable. And where accountability is absent, opportunity often fills the void.

The same opacity that makes shadow banking difficult to regulate also makes it attractive to those with less legitimate intentions. Without mandatory reporting requirements, standardized oversight, or the threat of deposit insurance revocation, these institutions can become conduits for money laundering, fraud, terrorist financing, and sanctions evasion in ways that traditional banks simply cannot. The question is no longer whether these vulnerabilities exist, but how they continue to be exploited.

The challenge of regulation

The global financial system has always evolved faster than the rules designed to govern it. What began as a coffee loyalty program and a few alternative lending platforms has quietly morphed into a parallel financial universe, one that moves trillions of dollars with a fraction of the transparency that traditional banking requires. That gap between innovation and oversight is not just a regulatory inconvenience, it’s an open door for illicit actors.

Closing that door will require more than periodic enforcement actions or piecemeal legislation. It will require regulators, lawmakers, and institutions to reckon honestly with how broadly the definition of a financial institution has expanded, and who bears the risk when things go wrong. Because historically, it has not been the institutions themselves; rather it has been the customers, the investors, and ultimately the public.

The first step, of course, is awareness. Recognizing that your money does not need to be in a bank to be at risk and that the custodians of that money need not be offshore shell companies to operate in shadows, can transform how we think about financial safety.

The line between a convenient app and an unaccountable financial intermediary is thinner than most realize. And in the world of financial crime, thin lines have a way of vanishing entirely.

You can learn more about theĚýmany challenges facing financial institutions todayĚýłó±đ°ů±đ

Key insights:

• • • Geopolitical crises fuel financial volatility and illicit activity — Conflicts have traditionally accelerated capital shifts and flows, creating cover for bad actors.

    • Predictable patterns emerge — Financial institutions should watch for sudden cross-border activity, unusual cash deposits, and transactions from border areas.

    • Conflict zones enable black market expansion — They also should adapt their compliance systems to detect more sophisticated methods used by criminals, tightening screening and enhancing staff training.

While business and international politics may appear cold and calculating, these things are often driven by emotion, especially fear — and fear of instability often drives market volatility.

So it goes as the United States attacks one of the world’s largest militaries and supporters of regional terror groups, causing deepening instability in a Middle East already beset by violence. It is certain that there is already a surge of money flowing in and out of the region for different reasons. Legitimate and illegitimate actors alike will seek to both run away from the crisis and profit from it. However, there are some anti-money laundering specific thoughts that financial institutions need to consider during a time of global uncertainty.

The bottom line — lots of money is on the move. Funding will send aid groups towards the crisis; it will also send logistical supplies, war material, and other necessities. All of these cost money, and defense sectors in multiple countries will be pumping out munitions to refill stockpiles in any country that is related to or in the neighborhood of the conflict.

Not every large transaction is an unusual, reportable event, but financial institutions now need to look one or two layers below the surface. What does not seem related on the surface is always a red flag. Look at beneficial ownership of companies and vessels, look at relations of the owners, not just the Ěý(OFAC) results of those people themselves. The financial system will, and should, allow the legitimate funds to flow. However, financial investigators must remain diligent to catch bad actors that take advantage of the surge in non-profit activity or the urgency with which legitimate businesses operate in a conflict zone.

Risk Factor 1: Capital flight from regime change

Just as the fall of the Al-Assad regime in Syria caused family funds to flow to as regime members fled the country, you will see the same with politically exposed persons (PEPs) who are inevitably fleeing regime change in Iran. A political crackdown will come. Whether the victors are on the side of the West or not remains to be seen, but some factions are going to flee the country and take family wealth with them.

Banks and other financial services should watch for anyone connected to people moving money through neighboring countries in which they may have literally hiked or driven before depositing cash into a financial institution. There are stories of refugees leaving places with gold bands on their arms, cash and false bottom purses, and diamonds in the lining of sweaters. These things will be converted to cash in neighboring countries and put into financial systems less affected by the conflict. An influx of cash throughout the region, therefore, could indicate this type of capital flight.

Risk Factor 2: Illicit finance and black markets

Since the fall of Syria, we have also become aware of that helps fuel addiction and armed conflict. There are certainly other substances and drug trafficking networks about which we know very little on this side of the secrecy veil.

Therefore, this instability will be seen as a time of opportunity for criminal groups. Indeed, with Assad’s security forces no longer controlling middle eastern captagon and other narcotics trade and various armed groups looking for funding sources, this is an illicit business opportunity.

Financial institutions can expect rapid movement of money between unrelated shell corporations, new corporations, and shadow vessels. They also should expect the black market to boom with drugs, contraband Iranian oil, and funds tied to narcotics that they have only yet to discover. Illegal arms will also generate funding, so all of the methods, both formal and informal, used to transfer value will become active.

In fact, large portions of such funding will flow through financial institutions; and peer to peer payment providers, FinTechs, and money transmitters should be especially wary of funds moving rapidly through their platforms. A burst in conflict means a burst in activity from illicit sources; therefore, enhanced, targeted monitoring is a must.

How financial institutions’ risk & compliance teams should respond

First, all financial institutions’ risk & compliance departments need to assess their institutions’ OFAC and sanctions screening search parameters. This is a good time to dial up fuzzy logic capability and reduce match percentage thresholds. In other words, risk tolerance should go down while the metaphorical dragnet gets wider. Surge the department’s personnel capability to compensate if you have to, because that is better than a strict-liability OFAC fine. Remember, OFAC sanctions are closely tied to national security, especially when it comes to Iran. This is not an arena in which leniency can be expected. Compliance teams should look at monitoring systems and thresholds immediately, create geographical targeting models to cover the conflict zone, and consider a command center approach to deal with the fluidity of the situation until things settle.

If your institution has not already taken the hint from regulators, this also is an opportunity to double down on Customer Due Diligence and identity verification. Front line staff and embedded business compliance personnel should receive updated training and job aids to increase awareness and hone internal reporting. Indeed, it is an advanced business skill to understand complex corporate beneficial ownership, much less to detect when it may be tied to illicit activity or corrupt regimes. Now is the time to increase that level of knowledge and thereby make the culture of compliance more robust.

In every crisis there is opportunity as well as risk: Managing the risk allows every company to take advantage of the opportunity, shore up its mission, and strengthen the institution.

You can find out more aboutĚýthe geopolitical and economic outlook for 2026Ěýhere

Key insights:

• • • AI scales deception — Fraudsters automate convincing scams, create synthetic identities, and overwhelm legacy controls, making AI an essential part of financial institutions’ anti-fraud solution.

    • “All-green” fraud is rising — The biggest losses often happen in correctly authenticated sessions, making them much harder to detect.

    • Behavior plus collaboration wins — Financial institutions need to shift from point-in-time checks to real-time, cross-channel behavioral signals and tighter inter-institution cooperation to spot coordinated campaigns and reduce friction without stalling growth.

How financial institutions are facing fraud in 2026 isn’t what it was like even two years ago. AI has industrialized deception, synthetic identities bypass traditional checks, and scams manipulate legitimate customers into moving their own money even as every security control shows green.

Today, financial institutions face a perfect storm, according to Michal Tresner, CEO of ThreatMark, and SaraĚýSeguin the DirectorĚýofĚýEnterprise Banking at Alloy. Indeed, they’re trying to manage attacks that scale automatically, identities that look real but aren’t, and victims who authenticate correctly before being convinced to hand over funds.

5 trends financial institutions need to understand in 2026

Looking at each of these five key challenges individually can offer both perspective and possible solutions.

1. The AI threat multiplier

Generative AI (GenAI) and large language models (LLMs) have fundamentally changed the fraud landscape. “AI is now the biggest threat facing financial institutions in 2026,” Tresner notes, adding that fraudsters are leveraging these technologies to create highly convincing content while automating attacks at unprecedented scale — a combination that overwhelms traditional security systems.

Seguin agrees and confirms this trend is . “Financial institutions are seeing a measurable increase in AI-enabled financial crimes, while consumers increasingly expect banks to deploy AI-based security in response,” she explains. The reality is stark: AI has become an essential tool for both fraudsters and those fighting against them.

2. The onboarding dilemma

In another area, the account opening process represents a critical vulnerability. Seguin points to rising first-party fraud and scams as particularly challenging because perpetrators often appear indistinguishable from legitimate customers going through the onboarding process. “A person may open an account with seemingly normal intentions — direct deposit or everyday banking — only to later engage in fraudulent activity,” she explains.

Onboarding is where institutions have the least certainty about either the authenticity of the identity or the legitimacy of the intent.

Tresner identifies a related threat: Synthetic identities. “Rather than stealing real identities, fraudsters now generate convincing fake ones, complete with realistic identity documents and even AI-generated images or video,” he says, noting that these synthetic identity accounts are exploding and frequently serve as infrastructure for moving stolen funds.

The common thread is that onboarding is where institutions have the least certainty about either the authenticity of the identity or the legitimacy of the intent.

3. Authentication under siege

Similarly, and even as financial institutions work to strengthen onboarding controls, account takeover remains a persistent threat. Fraudsters are now using AI to bypass authentication mechanisms at scale, making previously reliable security gates less trustworthy, Tresner explains. “Successful authentication can no longer serve as a definitive indicator of safety.”

Indeed, a properly authenticated session may still be the entry point for fraud, whether committed by an intruder or through a legitimate customer who is being manipulated.

4. The “all green” problem

Which brings us to another fraud scenario faced increasingly by financial institutions, and one that Tresner says may be 2026’s most operationally challenging issue — the fact that many scams don’t trigger traditional fraud controls. When the legitimate account holder initiates a transaction from their usual device and location using correct credentials, every standard check appears normal. The difference is the persuasion happening on the other side as fraudsters convince victims they’re interacting with trusted entities like banks, law enforcement, or romantic partners, and then direct them to transfer money.

Seguin notes that detecting these scenarios requires new approaches, such as identifying subtle behavioral signals like hesitation immediately before a money transfer. “Traditional device and credential checks won’t help when the customer is genuinely authenticated but acting under manipulation,” she explains.

5. Fraud as an industrial operation

Tresner emphasizes that modern fraud is not a series of isolated events but a coordinated, multi-step operation. Campaigns typically begin with establishing or compromising mule accounts, then deploying automated phishing kits to harvest personal data.

Younger users represent a growing target due to their online activity and platform usage, and the emergence of human trafficking-linked fraud operations has worsened this problem.

Not surprisingly, younger users represent a growing target due to their online activity and platform usage, Seguin says, adding that the emergence of human trafficking-linked fraud operations, including sextortion and overseas scam compounds, has worsened this problem.

What works in 2026

Tresner’s core recommendation for fraud investigators in financial institutions is for them to shift their focus from static, point-in-time checks to behavior-based detection. “Behavior profiling and analytics across channels can identify sophisticated actors and manipulation patterns invisible in single transactions or logins,” he explains, stressing that real-time cooperation among financial institutions is critical because fraudsters collaborate, and isolated defenses are insufficient.

Further, Seguin reframes fraud prevention as a growth enabler. “Effective risk controls allow institutions to launch products faster, set higher transaction limits with confidence, and avoid overly restrictive policies driven by fraud concerns,” she notes. Indeed, modern fraud defense isn’t just about reducing losses but about enabling safe expansion.

The 2026 fraud landscape presents compounding challenges: AI-driven scale and realism, onboarding uncertainty from synthetic identities and hidden intent, weakening authentication boundaries, scams that produce legitimate-looking transactions, and industrialized fraud operations that can span channels and institutions. Success in this area requires financial institutions to treat fraud as a behavioral, multi-channel, collaborative challenge because that’s exactly how their adversaries are operating.

You can learn more about the many challenges facing financial institutions today here

Key insights:

• • • Old laundering patterns have modern wrappers— Nefarious actors now cooperate to move value through mirror-trade commodity flows and sometimes crypto, blending legal transactions with illicit proceeds.

    • FinTech expands laundering options— Peer-to-peer apps, reloadable cards, kiosks, and virtual assets allow for the execution of many small conversion transactions that break up funds and blur clean-to-dirty movement.

    • Fraud scales cheaply in an AI era— As cash use drops, scams and extortion become lower-risk and easier to industrialize — sometimes through forced-labor scam operations — making verification and policy adaptation urgent.

When incentives align, strangers can become business partners. In the 21st century, traditional finance, banking, and cash payments have been disrupted by a watershed of technological advances for which we are all unprepared. This time of crisis and opportunity has created an unexpected alliance between FinTech firms and traditional banking institutions.

To fight financial crime, however, it is important to deal with the ever-evolving ways for currency to change forms and change hands across vast distances. This new way of moving money mirrors ancient systems of debt ledgers & interpersonal trust, often known as Hawala or Fei Chien. Criminals continue to innovate with both methods, creating unsettling partnerships.

The cartel-business partnership

Cartels, underground banking networks, and legitimate businesses now collaborate — sometimes unwittingly — to launder money by moving value through mirror-trade commodity flows and cryptocurrency, merging legal trade with illegal profits. Near-cash-style FinTech methods — such as peer-to-peer apps, reloadable cards, kiosks, and virtual assets — can expand laundering opportunities by enabling numerous small conversion transactions that fragment funds and obscure the movement of illicit money. As cash use declines, fraud, including scams and extortion (sometimes executed through forced-labor scam operations) becomes less risky and easier to scale in the AI era, underscoring the urgent need for verification and policy adaptation.

The flow of illicit cash also extends to digital assets. Some of the cash money that gets stuffed into bitcoin ATM-style kiosks is from the drug trade. Indeed, the U.S. Treasury Department’s Financial Crimes Enforcement Network (FinCEN) issued an alert on this topic as well and, while the two schemes seem distinct, we can speculate that some of the resulting Bitcoin, crypto, or other virtual assets went to underground bankers facilitating a mirror trade for a countryman.

What is old is new again

In the world of finance, the dawning of a new era of digital, on-demand, borderless transactions provides access to an exciting frontier of possibility. New coins, new blockchain tokenization uses, and new FinTech tools with cool names are all rising and falling faster than the price of bitcoin.

The players in this intersection have figured out that trade is profitable, and legal trade leading to illicit substance trade is even more profitable. Underground shipping, sanctions evasion, and dark web services for money laundering are all profitable by themselves, and when combined, they represent an illicit economic blitzkrieg.

Cartels, underground banking networks, and legitimate businesses now collaborate — sometimes unwittingly — to launder money by moving value through mirror-trade commodity flows and cryptocurrency.

Crypto is the new Hawala or Fei Chien because, with no bank or government involved, people can keep common copies of a ledger instead of relying on a hawaladar or Chinese underground banker to keep records. Virtual assets could facilitate the currency side of mirror trades, refilling a person’s coffers via digital transfer which can then be moved to an exchange and on to a local bank.

Commodities are the new cash because mirror trades are physically settled in commodities. For example, investment in source chemicals for drugs, negotiated at a discount, helps expand the illicit cartel business. Similarly, one-off items can be used for large-cash replacement transactions.

FinTech is the new money service business (MSB). We know that they are regulated the same but often serve different market segments, and many now exchange government fiat currency for one or more forms of cryptocurrency. Money laundering thrives on breaking up funds into smaller amounts to avoid reporting; therefore, a multitude of near-cash options like peer-to-peer payment apps, reloadable cards, and virtual assets help the launderer with this problem.

One might imagine that lower-tier street dealers could have several peer-to-peer payment app accounts for ease of use, because although the criminal is running an illicit business, it’s a business, nonetheless. Industry experts call these small payments conversion transactions because they usually come from a clean, legitimate payroll source but are converted to dirty funds when spent on an illicit substance or activity.

Fraud is low risk and AI fuels the fire

In this rapid-fire digital transaction world, fraud is the new mugging, complete with racketeering and slave labor farms. The profit margin on physical intimidation has gone down because people use cash less often, and many seldom carry it at all.

Due to digital innovation, communication technology, and AI, however, the barrier to entry for fraudulent theft, extortion, or scamming has gone down dramatically as well. Presumably, the margins are high because the ability to fraudulently communicate has become exponentially enabled by these tech advances. Fraud and scams are ubiquitous to the point of impeding legitimate business from communicating with customers effectively.

The players in this intersection have figured out that trade is profitable, and legal trade leading to illicit substance trade is even more profitable.

Further, slave labor has reared its ugly head in yet another strange intersection among these many things. Fraudsters in Southeast Asia build warehouses filled with tech and then force local people to operate scams and fraud schemes at scale. Aggregated funds from these efforts are sometimes moved via commodity or artifact, but often these funds are gathered from kiosks or peer-to-peer apps and then moved through cryptocurrency transactions until they become increasingly arduous to track.

Looking to the new dawn

It seems every few minutes brings us a new tool, a new opportunity, a new way to move money, and a new way to get scammed out of it all. This expanding capability is fueled by GenAI and even more advanced forms of AI. Business expands, productivity expands, and resources are consumed faster. Fraud is enabled, scaled, and seems to hang in the very air.

With the proliferation of digital, borderless, and AI-enabled everything, the human touch is more important than ever. Business owners note that requests for memorabilia and other tokens of physical value continue to rise. Cash will not go away, but its share of transactions is already diminished with the advent of crypto, new intersections in commodity exchange, and other person-to-person ways to settle accounts.

For the financial institutions, government agencies, and fintech firms that populate this world, creating informed best-practices and sensible policy documents is critical at this phase of innovation. Without a proactive approach we cannot hope to stay ahead of criminals and keep legitimate markets secure.

You can find out more about how organizations are using new methods to detect and prevent financial fraud here

Key insights:

• • • Blockchain’s transparency is a double-edged sword— While criminals use crypto for illicit activities, the permanent and public nature of the blockchain ledger creates an undeniable trail, making it a powerful tool for law enforcement to track and seize illicit funds.

    • The rise of crypto forensics— A growing industry of specialized firms and investigators is leveraging blockchain’s inherent design to unravel complex financial crimes, demonstrating that “±ô´Ç˛őłŮ” crypto funds can often be recovered.

    • An evolving battlefield— Despite the ongoing challenges posed by tools like mixers and privacy coins, blockchain technology is fundamentally shifting how financial crime is fought, turning the very system criminals exploit into the means of their capture.

Cryptocurrencies and other digital assets are used by criminals, which is great for catching them. Indeed, the biggest criticism of crypto since its inception has been its criminal use, which was estimated to be almost half of all activity by the end of 2017. In the past three months alone, asset seizures and forfeitures of more than $22 billion in crypto have been made by authorities in the United Kingdom, the United States, and their international partners.

These historic interceptions of illicit funds prove that the fundamental architecture of blockchain — the digital ledger that underpins most virtual transactions — makes it the perfect tool for catching criminals, validating the hypothesis of Satoshi Nakamoto, the presumed pseudonym of the person or persons who developed bitcoin, that fraud could be prevented through intentional system design.

While criminals assumed they could optimize their illegal activities using crypto to obfuscate fund flows, the blockchain ledger’s immutability has created a niche for financial crime investigators seeking to unravel these cases. Companies like Chainalysis, Elliptic, and TRM Labs have become synonymous with these investigations, joined by a growing network of smaller firms that are democratizing crypto investigations, combating terrorist financing and online child abuse. Ultimately working to secure seized assets and prevent further harm. By all measures, the ecosystem is expanding rapidly.

Every crypto transaction creates a permanent trail that allows investigators to catch criminals even years after their crimes. This is how, a digital exchange hack in 2016 that resulted in the theft of 120,000 Bitcoin worth $72 million (at the time) and was chronicled in the Netflix documentary was wrapped up years later with the seizure of $4.5 billion in crypto and the arrest of the two alleged perpetrators in 2022. Law enforcement may not move as fast as crypto, but if the whale is big enough, they will catch it.

Indeed, the scale of cryptocurrency-enabled crime threatens Western economic stability. The FBI received 149,686 crypto-fraud complaints in 2024, totaling $9.3 billion in losses, likely significantly lower than the true figure. More than 100,000 people are trafficked and forced to operate scams from compounds in Cambodia and Myanmar. The Prince Holding Group, a transnational criminal organization headed by Chen Zhi, generated , approximately $10.95 billion annually.

Financial crime as economic warfare

These are just headlines. Further research in the Netherlands shows that only 11.8% of fraud victims actually report being victimized. While many dismiss fraud and blame victims, crypto-related fraud is becoming economic warfare systematically draining wealth from Western economies while enslaving hundreds of thousands in forced labor camps across the Global South. With potentially $80 billion lost annually to crypto fraud, the impact extends beyond the 1.14% of the US federal budget it represents. This illicit outflow causes loss of productive capital, tax base erosion, and reduced economic activity.

Yet the technology accused of enabling this new generation of fraud simultaneously provides the tools to detect and combat these criminal organizations more successfully than any financial crime fighting technology in history. The Chen Zhi case, easily the largest asset forfeiture in US history at around $15 billion, demonstrates this perfectly.

Every crypto transaction creates a permanent trail that allows investigators to catch criminals even years after their crimes.

This is why I’ve spent the last four years studying the crypto ATM industry. While most financial crime professionals saw a problematic service in a problematic industry, I saw a massive dataset of criminal activity that could predict other illicit activity beyond crypto ATMs. This dataset helped identify terrorist financiers, vendors of child sexual abuse material (CSAM), and countless scams and frauds. Layer data-rich sources like crypto ATMs with blockchain data, and a good investigator can achieve remarkable results.

Modern blockchain analytics leverage the features Nakamoto designed for trust and verification. Immutability makes evidence tampering impossible and investigations public; and verifiability allows investigators to validate every step of a criminal’s crypto trail. Consensus mechanisms create a distributed jury of millions, validating the evidence chain further. These features enabled authorities to map the , revealing 76,000 fake social media accounts operated from facilities using 1,250 phones across 10 Cambodian compounds, and tie it to $15 billion in bitcoin.

The same technology facilitating billions of dollars in pig butchering scams annually enables law enforcement to catch the transnational criminals and recover funds. Traditional financial crimes disappear into offshore accounts and shell companies, often leaving investigators blind. However, as anyone in blockchain forensics knows, Locard’s Exchange Principle remains true: Every contact leaves a trace. Blockchain’s public ledger means every suspicious transaction leaves a permanent clue.

Nakamoto’s vision of “electronic transactions without relying on trust” inadvertently created a system for establishing criminal culpability. The blockchain’s public nature convinced criminals they could hide in plain sight, but Nakamoto saw that participants would be deterred from fraud by this transparency. The naive assumption that users had nothing to hide if doing nothing wrong quickly revealed plenty were doing wrong. Still, the system proved fit for purpose once tools were built to catch bad actors. Nakamoto’s white paper’s emphasis on preventing double-spending through public verification created a framework in which crime-spending leaves permanent evidence. All a good investigator needs is time.

The rise of crypto forensics

As crypto advances, tools like bridges, mixers, and privacy coins pose constant challenges for investigators, but claiming the money is gone when crypto is involved is simply false. As blockchain forensics advances, criminals face an uncomfortable truth: They’ve been conducting operations on a permanent, public, immutable ledger. Their only protection is time and cryptographic puzzles that an entire industry is working to unravel.

While some has been diligent in pointing out some of the challenges in the industry and some of what’s been missed, there are a lot more illicit fraud cases that never see the light of day because of what has been prevented by blockchain forensics. And while it may not be perfect, the fact that there is an industry working to build a safer financial system than what has gone before is commendable, and the accountability that public ledgers have enabled is energizing for those that must police it.

Unfortunately, the $15 billion Chen Zhi seizure isn’t the end but the beginning. With at least $64 billion stolen annually, these criminals have little incentive to stop. While some scam compounds have been dismantled, reports indicate they’re simply being relocated.

Nevertheless, blockchain is setting a new paradigm in financial crime, one in which the technology enabling crime will eventually become the weapon that defeats it.

You can learn more about financial crimes and other regulatory issues involving cryptocurrencies here

Key insights:

• • • Traditional fraud breaks systems; scams break people — Scams directed against individuals weaponize trust, urgency, and emotion and hit victims when they’re stressed or distracted.

    • Nearly 1-in-4 adults have lost money to scams, and that number is climbing — Criminals now wield deepfakes, voice cloning, and AI to make their pitches eerily convincing — and the curve is still bending in their favor.

    • By the time someone reaches the payment screen, manipulation has already won — Real protection means flagging suspicious outreach early, verifying identities in real-time, and building friction into high-risk transactions, all before emotions override logic.

One of the most fundamental distinctions in financial security is this: Every scam is a fraud, but not all fraud is a scam. During this week’s , it’s worth pausing to note what makes scams different — and why that difference matters more than ever in 2025.

Traditional fraud typically exploits weak systems, such as stolen credentials, manipulated data, or technical vulnerabilities. Scams, on the other hand, exploit something far more powerful and harder to patch — human nature itself. Scams can weaponize trust, urgency, and emotion; and when those psychological levers are pulled at just the right moment, even savvy people can find themselves wiring money to someone they’ll never see again.

The threat is only growing

The numbers tell a sobering story. More than 1-in-5 (22%) of adults report losing money to scams, according to the . And Ayelet Biger-Levin, founder ofĚýand creator of ScamRanger, a technology designed to stop scams before they happen, doesn’t mince words about the growing threat of scams: “From a numbers perspective, scams are on the rise,” she says. “They’re going to continue to rise because criminals are becoming more sophisticated, leveraging the latest technology advancements including large language models (LLMs) and AI agents to scale operations.”

Indeed, her definition cuts straight to what makes scams unique. “A scam is social engineering to convince an individual to either disclose personal information or transfer money directly to a criminal,” she explains, adding that it’s not a system breach; rather, it’s a conversation that goes wrong — often in ways the victim doesn’t realize until it’s too late.

And the trajectory isn’t encouraging. Biger-Levin says that she expects that the number of adults being victimized over the next 12 to 18 months will only increase. “In the US, I expect it to rise,” she notes. “Criminals are rapidly leveraging tools that make scams more believable such as deepfakes and voice cloning, which are used for impersonation to increase both scale and success.”

And while we haven’t reached the tipping point yet, the curve isn’t bending in our favor.

Scams adapt to every new channel we create

Here’s the uncomfortable truth: Scams aren’t a glitch in the system; rather, they’re a feature of human society that adapts with every new communication channel we build. Romance scams, investment lures, fake shopping sites, cryptocurrency schemes — these aren’t amateur operations anymore. They’re often run by organized networks, sometimes operating out of compounds in Southeast Asia, and they’re supercharged by technology that makes deception easier and more convincing than ever.

Deepfakes can put your CEO’s face on a video call. Voice cloning can mimic a family member in distress. Increasingly, agentic AI can personalize phishing at scale, crafting messages that feel eerily tailored to your life. Educating people about ways to keep from becoming victims helps, absolutely. However, when a persuasive story lands at exactly the wrong moment — when you’re stressed, distracted, or emotionally vulnerable — logic often takes a back seat.

And if those fighting fraud are waiting until a victim reaches the payment screen to intervene, they’re already too late.

Meeting manipulation where it starts

To make real progress, we need to meet manipulation at first contact — the moment persuasion begins. That means pairing human-centered design with protective technology across the entire scam lifecycle.

What does that look like in practice? It means flagging risky outreach before it reaches an inbox. Verifying websites and identities in real time, in context; and slowing down high-risk payments while prompting users with friction that feels helpful, not punitive. And critically, it means sharing signals and liability across the ecosystem — among banks, telcos, social platforms, and regulators — so they can all work from the same playbook.

The constant in all of this is human psychology. The variable is how well our systems anticipate it.

Biger-Levin says she is optimistic about enforcement improving over time. “I do predict that long-term, these scam compounds are going to be taken down,” she says, adding that she’s also realistic about what comes next. “Criminals are not going to stop there, and by using advanced technology will continue to attack individuals. The one common denominator, though, is human psychology, and that is something we can tackle and protect with the right consumer empowerment in place”

That’s the core challenge. Regulators or financial services compliance agents can shut down a scam operation, but they can’t patch human emotion. Technology solutions must be designed around how people actually think and behave under pressure — not how we wish they would. That means building systems that recognize when someone is being groomed, when urgency is being manufactured, and when trust is being weaponized.

The old advice still holds… because it reflects how we think

There’s a reason the classic warnings never go out of style. The old saying of, If something seems too good to be true, it probably is, is not outdated wisdom — it’s a reflection of how scams work by promising outsized returns, instant solutions, or emotional rewards that bypass our rational filters.

Gut checks still matter, Biger-Levin reminds us, adding that doesn’t mean we can rely on individuals to shoulder the entire burden of vigilance, especially when criminals are using industrial-grade tools to manipulate them.

Scams will always evolve. So, the question isn’t whether they’ll disappear — they won’t. The question is whether we’re willing to build systems smart enough to protect the humans inside them.

That means reducing exposure at the source, disrupting grooming tactics before they gain momentum, and making the this doesn’t feel right moment easier to spot — and safer to act on. It also means treating scam prevention not as a user education problem, but as a systems design problem.

We can bend the curve, but only if we stop treating scams as individual failures and start treating them as the systemic, technology-enabled threats they’ve become. The tools already exist; however, the challenge is coordination, accountability, and a willingness to bake protection into every layer of the digital experience.

Because the denominator isn’t changing and human psychology remains constant, the aspect that we can change is how well our systems anticipate it — and how much harder we make it for criminals to exploit it.

Staying ahead of the scammers

To stay ahead of these scammers, organizations and consumers should take practical steps to prevent and minimize risks. For example, they should stay up to date on the latest scam tactics by keeping an eye on consumer protection updates. These can help you spot red flags, such as urgent demands or unusual payment requests, that may signal a scam.

Also, when you receive unsolicited calls or emails, take a moment to verify their authenticity. Instead of responding right away, contact the organization directly using official contact information. Legitimate companies typically won’t ask for sensitive information like passwords or account details out of the blue.

Finally, boost your digital security by using strong, unique passwords and enabling two-factor authentication. Be cautious when clicking links and avoid those that seem suspicious. Scammers often rely on high-pressure tactics to prompt rushed decisions; so by taking a step back and evaluating the situation carefully, you often can avoid falling prey to their schemes.

You can find out more about how businesses and individuals are navigating fraud schemes here

Key insights:

• • • Blockchain data exceeds Wolfsberg expectations — Public, attribution-rich ledgers give crypto firms immediate access to behavioral, network, and cross-chain signals that traditional banks must retrofit or request from third parties.

    • Crypto companies can leverage this data — With abundant labeled history and real-time on-chain context, crypto companies can combine rules, supervised machine learning, and unsupervised discovery to identify emerging typologies faster and with clearer explainability.

    • SARs become actionable intelligence, not just checked boxes — By including wallets, hashes, and traceable flows, this data can turn SARs filings into ready-to-investigate leads for law enforcement, thereby converting compliance from a cost center to a competitive advantage.

The Wolfsberg Group’s on modernizing suspicious activity monitoring comes at a crucial time for cryptocurrency companies. Traditional financial institutions are being encouraged to go beyond basic transaction monitoring by including behavioral analysis, network effects, and various risk indicators in their anti-money laundering (AML) programs. For cryptocurrency companies, the framework describes capabilities that blockchain data infrastructure was essentially built to support.

Wolfsberg’s recommendations map almost perfectly to what blockchain businesses already are able to do. While traditional banks work to update legacy transaction monitoring systems with new capabilities, crypto companies operate in an environment in which the data for complex monitoring already exists. For crypto companies, this shouldn’t be seen as simply having to adapt to a new standard, but rather as a unique opportunity to set a new standard.

Investigation advantages built into the technology

Traditional financial investigations operate within closed systems. Investigators, at the start of an investigation, primarily have access to data points from their institution and what is available online. They may then need to gather additional information, each controlled by different institutions with their own legal requirements and timelines. The financial trail crosses multiple organizations, jurisdictions, and record-keeping systems that do not communicate with each other. With Suspicious Activity Reports (SARs) filings, investigators are often forced to close an investigation with gaps in the full picture.

Cryptocurrency investigations begin with transparency. Blockchain attribution tools offer visibility into fund flows throughout the entire ecosystem. The financial trail is recorded on a public ledger, in which tracking money doesn’t require negotiating with counterparts or waiting for legal approvals. This fundamentally changes what’s possible during an investigation. Questions that would take traditional investigators weeks to answer through formal channels or go unanswered by the time the SAR is due can be resolved in hours using attribution data and on-chain analysis.

The data available to cryptocurrency companies means they can move past compliance as a check-the-box exercise and start getting creative when thinking about what’s actually possible.

The Wolfsberg framework emphasizes “expanded risk indicator coverage” by analyzing data points beyond transaction amounts, dates, and counterparties. Blockchain companies have easy access to this data — wallet age, complete transaction history, interaction patterns with decentralized finance protocols, network connections to known bad actors, mixing service usage, cross-chain behavior, and anomalies that would be invisible in traditional banking. The data exists and is readily available for use in innovative and unique ways.

Detection models that can do more than react

Wolfsberg recommends combining three approaches: i) rules-based monitoring for known risks; ii) supervised machine learning for identifiable patterns; and iii) unsupervised methods for detecting emerging threats. Cryptocurrency companies can implement all three at the same time because the underlying data supports each approach.

Rules-based monitoring handles obvious cases such as sanctioned wallet addresses, direct transfers from darknet marketplaces, and transactions routed through high-risk jurisdictions. This represents baseline coverage that almost every crypto company will already have implemented. Adding the ability to look up scam wallets that are self-reported by victims online and community reporting capabilities in blockchain forensic tools, the foundation for much more effective risk mitigation is easily established.

Using blockchain’s historical data, models can be trained on years of confirmed criminal activity that law enforcement or blockchain tools have already identified. As traditional banks can’t access validated historical data across the entire payment ecosystem at this scale, they typically must rely on internal data and industry guidance to develop their models. Cryptocurrency companies, however, can utilize blockchain history and attribution databases that document known illicit activity. This means models can be trained on nearly unlimited applicable data from the past and can even be trained on near-real-time data as it gets added to databases.

Yet, it is with unsupervised learning that crypto companies can genuinely innovate beyond what traditional finance does by feeding attributed wallets, self-reported fraud wallets, and public blockchains directly into machine learning or AI models. With this, companies can analyze complex, interconnected patterns of activity that allow models to continuously identify emerging typologies and patterns in near real-time and potentially instantly expose gaps in a scenario’s current coverage.

It is with unsupervised learning that crypto companies can genuinely innovate beyond what traditional finance does by feeding attributed wallets, self-reported fraud wallets, and public blockchains directly into machine learning or AI models.

The data available to cryptocurrency companies means they can move past compliance as a check-the-box exercise and start getting creative when thinking about what’s actually possible.

SAR quality as intelligence product

The Wolfsberg framework addresses SAR quality directly, highlighting the problem of financial institutions filing too many low-value reports because their systems generate alerts that they cannot fully resolve. Indeed, institutions file thousands of SARs because they have unanswered questions or are unsure of exactly what is going on due to a lack of available data, not because they’ve identified actual money laundering.

Blockchain data changes what SAR filings can look like in ways that matter for law enforcement. When attribution tools indicate that funds originated from a wallet cluster associated with ransomware, were transferred through a mixing service, appeared in a customer’s deposit address, and were immediately withdrawn to a known cash-out service, the SAR can describe the exact pattern of suspicious activity with on-chain evidence for each step.

Including wallet addresses and transaction hashes in SAR narratives provides investigators with something traditional bank SARs rarely offer: immediate starting points they can follow without additional legal process, immediately making the SAR actionable intelligence.

Law enforcement agencies are overwhelmed with SARs, and it often feels like an investigator’s SAR filings don’t lead anywhere. However, when investigators can include information that helps law enforcement investigate and prosecute cases quickly and effectively, those investigators also may start seeing activity on the blockchain, such as illicit actors’ wallets slow down or funds be seized from a scammer’s wallet. This not only helps with the feedback loop but also confirms to an investigator that their work is making a real difference.

Building programs that lead instead of follow

The Wolfsberg framework also makes clear that innovation in AML isn’t optional. Criminal networks evolve too quickly for static rule sets and outdated monitoring systems. Advanced approaches need to be explainable, properly validated, and integrated into broader risk management frameworks.

Financial institutions need to build models that fully use available blockchain data, then validate them against on-chain patterns that can be directly observed. They should also train their investigators to understand blockchain attribution and network analysis — not just how to read a blockchain explorer, but how to interpret what attribution tools reveal about fund flows and network connections. When filing SARs, institutions need to include the on-chain evidence that makes their filings immediately actionable for law enforcement.

Traditional financial institutions are modernizing systems designed for the pre-internet era, while cryptocurrency companies are building compliance programs in a data-rich environment that makes certain investigations more effective than they’ve been in the past. The opportunity here isn’t just about meeting the Wolfsberg recommendations; rather the opportunity is showing what becomes possible when compliance programs are built with these capabilities from the ground up and when the data advantages inherent to blockchain technology get used to their full potential.

That will be what changes how regulators think about the industry — and what turns compliance from a cost center into a competitive advantage.

You can find more ofĚýour coverage of SARs and related effortsĚýto combat financial crimes here

Key insights:

• • • Debanking can have harsh consequences — Losing a bank relationship can abruptly cut off finances and damage reputations, often excluding people and firms from basic economic life, often without a clear explanation.

    • The core tension for banks — Financial institutions need to balance the risk between AML/KYC and fraud versus preserving fair access to financial services. As reputational and ideological factors enter into decision-making, concerns about discretion and due process grow.

    • Policy is moving toward guardrails — Already many policymakers are pushing for clearer documentation, transparent notices, a common-sense path to appeal, and a bright line between financial‑crime risk and other risks.

Financial institutions serve as the foundation of the modern economy. Nearly every transaction — from paying for services to buying a cup of coffee — depends on an institution that facilitates or underwrites these exchanges. In this interconnected system, access to banking relationships has become essential for meaningful economic participation for individuals and organizations.

This dependence creates significant consequences for society. Without access to banking services, both businesses and individuals face significant barriers to participating in the economy. Businesses cannot easily pay their employees, fulfill tax obligations, or conduct basic commercial activities. Similarly, individuals struggle to receive payments and manage their personal finances. When institutions terminate these relationships, they effectively exclude people and businesses from the broader economic system. This reality applies to both traditional banks and modern FinTech companies.

Given banking relationships’ critical role in economic participation, the circumstances under which these relationships end deserve careful examination. Financial institutions face ongoing challenges in determining which customers they can serve while meeting regulatory obligations and business objectives. This decision-making process has evolved and can ultimately lead to what experts call debanking — a practice that involves closing accounts and terminating interactions between debanked individuals or organizations and the financial institutions doing the debanking.

What debanking is — and isn’t

The impact of debanking extends far beyond the inconvenience of closing an account. Affected individuals may face extended periods without access to essential funds needed for survival, and they often suffer lasting reputational damage that may cause other financial institutions to reject them as well. Most concerning, however, is that banks rarely provide clear explanations for debanking decisions, leaving individuals unable to address potential misunderstandings or prevent future occurrences.

Without access to banking services, both businesses and individuals face significant barriers to participating in the economy.

This lack of transparency and the cascading effects of banking exclusion demonstrate the profound power that financial institutions hold in determining who can fully participate in the modern economy. This also causes concern about who holds this power and how it can ultimately be kept in check.

Not surprisingly, the concept of debanking has become a contentious issue in the financial sector, with proponents and critics presenting varying perspectives on its implications. At its core, debanking most often occurs when financial institutions terminate or refuse to establish customer relationships, often due to concerns about risk management or regulatory compliance.

Financial institutions argue that debanking is a necessary measure to mitigate potential risks, such as money laundering, terrorist financing, and other fraudulent activities by certain individuals or businesses. By terminating these illicit customer relationships, banks aim to protect themselves from reputational damage, financial losses, and regulatory penalties while maintaining financial system integrity and adhering to anti-money laundering (AML) and know-your-customer (KYC) regulations.

Critics, on the other hand, argue that debanking can have unintended consequences, particularly for marginalized communities and individuals who may not have access to alternative financial services. This can lead to financial exclusion, making it difficult for people to access basic banking services, such as deposit accounts, credit, and payment processing services.

However, the scope and application of debanking practices have expanded beyond traditional risk-based criteria. Questions have emerged regarding the appropriateness of account closures based on reputational concerns, political associations, or ideological considerations. This broader application has intensified public discourse about the boundaries of institutional discretion and the potential implications for financial inclusion.

Policymakers now are working to ensure that banks can address genuine risks without discriminating against customers based on their lawful views.

To navigate this issue, financial institutions need to follow a balanced approach. This involves enhancing transparency, providing channels for appeal or alternative services, and refining regulations to define acceptable grounds for debanking. The goal is to maintain a secure and inclusive financial system that effectively manages risk while protecting the interests of ordinary citizens and legitimate businesses.

Policymakers get involved

In response to concerns that non-financial factors may influence these decisions, an Executive Order was issued by the Trump administration in August to establish clearer guidelines for banking institutions, requiring that account management decisions be based primarily on financial and risk-related criteria. The order seeks to standardize practices across the industry and provide greater transparency in the decision-making process for account closures and financial service terminations.

In September, at the Association of Certified Anti-Money Laundering Specialists (ACAMS) Assembly held in Las Vegas, Mike Greenman, Senior Vice President and Chief Counsel of Financial Crimes Legal at US Bank, emphasized the critical importance that financial institutions present clear documentation for when and how debanking decisions were made about specific industries. Greenman strongly advised institutions to “always separate financial crime risk from other risks.”

Looking ahead at debanking

The issue of debanking has garnered attention due to high-profile cases and concerns about potential misuse. Investigations in several countries have found no evidence of widespread politically motivated debanking, but the perception of potential abuse has led many critics to re-examine this practice. Policymakers now are working to ensure that banks can address genuine risks without discriminating against customers based on their lawful views.

To navigate this issue, a balanced approach is necessary, one that involves enhancing transparency, providing channels for appeal or alternative services, and refining regulations to define acceptable grounds for debanking. The goal for financial institutions should be to maintain a secure and inclusive financial system that effectively manages risk while protecting the interests of ordinary citizens and legitimate businesses.

You can find out more about the regulatory challenges that financial institutions face here

Key takeaways:

• • • Navigating regulatory change — The Trump administration is introducing many regulatory changes that will affect how financial institutions meet their reporting obligations under the BSA.

    • AI helps and harms both sides — Advances in AI offer the promise of more accurate, efficient BSA compliance processes, but they also give criminals an ever-expanding toolkit for committing fraud and other types of financial crime.

    • Compliance pros are optimistic about AI — Corporate compliance personnel are cautiously optimistic about using AI, but insist that better guardrails, usage standards, and agreed-upon best practices still need to be developed.

LAS VEGAS — Those who assess and manage risk at financial institutions are caught in a whirlwind of change, and the health of the global financial system may very well depend upon how they manage the fallout.

At of the Association of Certified Anti-Money Laundering Specialists (ACAMS), the word disruption was used frequently to describe the kind of systemic change that experts in Bank Secrecy Act (BSA) and anti-money laundering (AML) compliance are up against. And this change is coming at them in many forms: regulatory, technological, geopolitical, digital, ethical, and criminal, just to name a few.

Dissatisfaction with the status quo

In his opening keynote address, John K. Hurley, the U.S. Undersecretary of the Treasury for Terrorism and Financial Intelligence, expressed the Trump administration’s dissatisfaction with the current state of financial crime enforcement. Hurley also outlined several reforms the administration is pursuing, all of which are aimed at delivering targeted, actionable intelligence to law enforcement much faster than the current system allows.

Hurley decried the proliferation of burdensome regulations and “not-so-useful” Suspicious Activity Reports (SARs), the main method that financial institutions use to report suspicious financial activity to the U.S. Treasury’s Financial Crimes Enforcement Network (FinCEN).

To address these problems, Hurley said the administration intends to simplify the SARs filing process and overhaul the government’s regulatory oversight of financial institutions to focus on “outcomes”, such as how effectively financial institutions identify criminal activity, rather than examiner evaluations (and criticisms) of an institution’s BSA and AML compliance processes.

One of the motivations behind these moves, Hurley said, is to encourage BSA compliance personnel to apply their “experience and creative talent” to devise better crime-detection methods using new technologies.

“I believe fully that well-governed technology is a force multiplier,” Hurley explained. “When a financial institution invests the time and money to experiment with AI and successfully drops its false-positive ratio [of SARs] and escalates vital information to law enforcement more rapidly, their team should be celebrated, not written up because this new approach reveals gaps in their previous manual method.”

AI in BSA/AML compliance: A double-edge sword

Indeed, the use of AI-enhanced technologies to improve know-your-customer (KYC) protocols and other risk-management practices was another main theme of the conference. During several sessions dedicated to AI, panelists and conference attendees expressed both optimism and wariness about the use of AI in BSA/AML compliance activities.

For example, the use of agentic AI — a form of AI that essentially thinks for itself and can proceed without constant human prompting — could be extremely useful for first-level KYC risk screening, but it remains to be seen whether the technology can be adequately controlled for BSA/AML compliance purposes.

The double-edged nature of new technologies was also discussed in-depth. Carole House, an ACAMS Distinguished Senior Fellow, pointed out that while new technologies may improve our ability to detect and deter financial crime, they also give criminals a robust set of high-tech tools to use to help subvert the financial system.

“When you democratize access to these systems, it opens to the door to illicit uses,” House said, adding that new and better forms of digital malfeasance — such as fake IDs, bogus credentials, deep fakes, identity scams, crypto-based money-laundering, ransomware, and more — are all on the rise, and ever-improving forms of generative AI (GenAI) will empower criminals even more.

Despite these caveats, there was almost unanimous agreement that AI will play an increasingly important role in BSA compliance and risk management, because there is no other way to keep up with criminals in the digital economy. And because AI adoption is inevitable (and is, in fact, already happening), efforts now need to be focused on building adequate regulatory guardrails, improving digital skillsets, and establishing AI best practices to ensure responsible use of advanced technology.

New rules, old problems

On the regulatory front, several recent changes that likely will impact how AML compliance personnel do their jobs were also discussed at length during the conference.

In March, for example, FinCEN issued a new rule exempting certain United States-based companies and citizens from their previous obligation under the Corporate Transparency Act (CTA) to report beneficial ownership information to FinCEN. (Foreign entities doing business in the US still have to file beneficial ownership information.)

FinCEN claims the rule change is intended to reduce the reporting burden on small companies, but AML experts are concerned because it gives financial institutions less information to assess the legitimacy of their customers, potentially re-opening a window to fraud that had previously been closed and hindering attempts to assist law enforcement.

Support for crypto-regulation

On another matter, AML experts are generally supportive of recent efforts to regulate cryptocurrency assets. For example, creates new regulatory framework for stablecoins, which are a type of cryptocurrency whose value is backed a fiat currency such as the US dollar.

Congress is also considering passage of the Digital Asset Market Clarity Act, which would create guidelines for the classification, sale, and oversight of digital assets. And a series of new policy directives collectively known as The Blanche Memo (because they were issued by Deputy U.S. Attorney General Todd Blanche) aims to end so-called “regulation by prosecution” of crypto exchanges and shift the emphasis of law enforcement to individuals who use digital assets to support “terrorism, narcotics and human trafficking, organized crime, hacking, and cartel and gang financing.”

In addition to these changes and concerns, BSA/AML compliance professionals are also contending with Chinese money laundering, ever-shifting sanctions, tariff evasion, global regulatory volatility, worldwide financial threats, lack of institutional trust, and pervasive economic uncertainty — so by any measure, they have very full plates.

As Dan Stipano, a partner at Davis Polk & Wardwell, remarked during one panel discussion: “The big problem with the BSA is that if everything is a priority, nothing is a priority,” — and that too must change.

You can find more of our coverage of ACAMS events here