By Deepak Shukla
Compliance as it stands now in 2026 has come quite far from what it was two years ago.
Regulatory changes will happen more quickly, AI will become better, and companies will have to demonstrate how they’ve verified things, reviewed information, and why they made certain decisions.
This article looks at the trends in KYC, AML and transaction monitoring. It includes how these trends will vary between the UK, EU, US and APAC regions and what options are available for small fintechs which can’t afford large teams of compliance specialists.
Compliance Has More Work, Not More People
Regulatory scope is expanding faster than most compliance budgets.
New AML supervision structures in Europe, changing beneficial ownership rules in the US, and the move towards continuous monitoring in parts of APAC all add more to the workload, while headcount tends to stay put.
The firms handling this best in 2026 are not necessarily the ones buying the most software. They are using technology to give smaller teams more room to think, covering more ground without handing the important decisions over to a machine.
From Automation to Continuous Compliance
For years, RegTech mostly meant rule-based automation. A system flags a transaction, someone reviews it, the case gets closed.
That still happens, but it is no longer where most of the value lies. Static rules have a hard time keeping up when regulations can change several times in a year.
The bigger shift is towards continuous compliance, with monitoring running in real time instead of in scheduled batches. Regulatory change management tools are becoming useful here too, tracking new requirements and linking them back to internal policies and controls.
This becomes particularly important for firms operating across borders. A compliance team manually keeping an eye on UK, EU, US and APAC rules is already playing catch-up. Adding more people is not always a realistic answer.
What AI Is Actually Good At in Compliance Right Now
AI now touches most parts of KYC, AML and transaction monitoring. The useful part is not that it somehow eliminates compliance teams. It is that it can change where those teams spend their time.
Customer Screening and Risk Scoring
One of the more practical uses of AI is customer screening. Dynamic risk scoring can update as a customer’s behaviour changes instead of leaving their risk profile frozen at onboarding and waiting for the next scheduled review.
That does not remove human judgement. It changes when it is needed, moving it away from routine checks and towards the accounts that actually deserve closer attention.
Alert Prioritisation and False-Positive Reduction
The clearest return often comes from alert prioritisation. Machine learning can rank transaction monitoring alerts by likely risk, helping analysts spend less time clearing obvious false positives and more time on cases that genuinely need a decision.
For a lean team, that can make a real difference. Cutting the noise is not just about saving hours. It leaves analysts with more attention for the cases where getting it wrong actually matters.
The Explainability Requirement
Regulators are no longer satisfied with knowing that a firm uses AI.
They increasingly want to know how the system reached a particular decision. Frameworks shaped by the EU’s AI Act, along with evolving expectations from US regulators including FinCEN, are pushing firms towards clearer explanations of why a transaction was flagged or cleared.
This is affecting vendor assessment as well. When the system cannot give a rationale for its decision, accuracy becomes less relevant. The software could be the cause of noncompliance.
Why Human Oversight Still Decides the Hard Calls
None of this means people disappear from the process. They should not.
There will always be the need for someone who can make sense of situations that may not have been seen before by the model during its learning process.
The reasonable strategy for 2026 is actually quite straightforward: the AI handles quantity and prioritisation, but humans are still responsible for the result.
Organisations that fail to recognise this may only discover their mistake when a regulator begins posing some questions.
Compliance Tools Are Only as Good as the Data Feeding Them
The ability to come up with good decisions cannot be achieved with a bad dataset, even when using a sophisticated analysis system. This implies that real-time feeds and open APIs could sometimes be more important than the analytics layer itself.
The cloud has also made jurisdictional compliance easier. Instead of running separate regional tools, firms can pull rules and data into a connected platform.
Cloud deployment now accounts for roughly 63.7 per cent of the RegTech market, according to 2026 figures from Future Market Insights, which says something about how central cloud infrastructure has become.
It is also pushing the market towards consolidation. Separate tools for onboarding, sanctions screening, transaction monitoring and reporting are gradually being replaced by platforms that connect those jobs together. This might work better for small groups than always trying to have the best feature in each category.
The Differences in Compliance Landscapes by Region in 2026
Regulation is not really converging in 2026. It is moving in parallel, with each major market setting its own pace. Businesses operating across borders need to understand those differences rather than assume that compliance in one market automatically covers another.
EU
Europe’s AML supervision structure has changed significantly this year. The EU’s Anti-Money Laundering Authority became operational in mid-2025 and formally took over AML and counter-terrorist financing responsibilities previously held by the European Banking Authority on 1 January 2026.
This comes ahead of a single EU rulebook and direct supervision of the highest-risk entities from 2028.
US
US firms are dealing with changing expectations around beneficial ownership reporting under FinCEN, alongside greater regulatory attention on crypto and stablecoin activity. Compliance systems therefore need to be flexible enough to adapt as those expectations shift.
UK
The UK continues to take its own approach in several areas. The FCA is pushing a more data-driven supervisory model, which means firms operating across the UK and EU increasingly need systems capable of applying different logic in each jurisdiction.
APAC
Financial centres such as Singapore and Australia are moving from periodic reviews towards continuous monitoring.
That is pushing firms towards the same kind of real-time RegTech infrastructure becoming common elsewhere, even though the underlying rules remain different.
The practical takeaway is pretty straightforward.
If a firm operates across several regions, its compliance technology needs to flex by jurisdiction. One global rule set rarely fits all of them properly.
Compliance on a Startup Budget: What’s Actually Achievable
Smaller fintechs cannot simply copy what a large bank does on a smaller scale. The regulatory expectations do not shrink just because the company does.
What changes is how the work gets covered. Three approaches are particularly useful for lean teams.
RegTech-as-a-Service
Smaller fintechs face many of the same regulatory expectations as larger institutions, but without the same budgets or headcount. RegTech-as-a-Service gives them access to institutional-grade KYC and AML capabilities through APIs, without the cost of building everything internally.
Managed and Outsourced Compliance Services
Outsourcing can work well for defined, high-volume tasks such as document verification and sanctions screening. A specialist provider may handle these more consistently and cheaply than a small internal team.
Risk ownership and regulatory relationships are different. Those should generally stay in-house, regardless of how small the company is.
What to Actually Look For When Buying
In 2026, the useful questions are fairly practical: Does the platform cover the jurisdictions you operate in? Does it provide a proper audit trail? Can it explain its decisions? And how much integration work will actually be required?
The basics still matter, too. Buying software does not create a compliance programme. Someone inside the business still needs to own the process.
The Compliance Team Now Has to Govern Its Own Tools
AI governance is becoming a compliance discipline in its own right. Firms need to know where AI is being used, who is responsible for each decision, and how those decisions can be reviewed if a regulator comes knocking.
Data security and privacy matter just as much. RegTech platforms deal with sensitive financial and personal information at scale, so a breach is not simply an IT problem. It can quickly become a regulatory one as well.
Then there are audit trails. Compliance teams increasingly need to show what was checked, when it happened and what happened afterwards. In an examination, that evidence can matter far more than another policy document sitting in a folder.
The Compliance Function Is Becoming Smaller and More Technical
Investment is following the change. Grand View Research estimates the global RegTech market at around US$29.3 billion in 2026, with growth concentrated in areas such as continuous monitoring, regulatory change management and AI governance.
The people inside compliance teams are changing along with the technology. Legal and policy knowledge still matters, but teams also need stronger data skills, model oversight capabilities and enough technical understanding to question how a system arrived at a particular result.
Smaller Teams, Sharper Judgement: What Comes Next for Compliance
The direction for 2026 is fairly clear. Compliance teams will be kept small in number, whereas technology will be used to do more of the grunt work. The people who will be left managing the process will be doing more exception-based activity.
That is not really a story about software replacing compliance professionals. It is about using their time differently. The firms that get that balance right should be in a much better position when the next regulatory change comes along.
About the Author
Deepak Shukla is the founder and CEO of Pearl Lemon Accountants, part of the Pearl Lemon Group. He works at the intersection of finance and AI, building tools and processes that make accounting, tax and compliance faster and more accurate for businesses across the UK, US and Europe. Under his leadership, Pearl Lemon Accountants has grown into a full-service practice supporting finance teams and CFOs with cross-border accounting, tax planning and financial compliance.
