95% Adoption, 9% Readiness: The RegTech Industry's Data Infrastructure Gap

Ninety-five percent of financial institutions say they have scaled enterprise use of RegTech across at least one regulatory domain. That is the headline finding from the Global State of RegTech 2026 report, published on 12 May by RegTech Analyst and Parker & Lawrence Research. The report surveyed 300 senior compliance decision-makers and 100 RegTech vendors. It describes a market that has, in its own telling, reached maturity.

Set that number next to another one, from a different survey published earlier this year. Only 9.5% of financial institutions describe themselves as "very prepared" to support AI and machine learning with their existing data infrastructure. That figure comes from the Wolters Kluwer regulatory compliance survey of 148 financial institutions, published in February 2026.

The distance between those two numbers is the story of the RegTech industry in 2026. Almost everyone has bought the tools. Almost no one has built the foundation those tools need to work.

The Adoption Numbers Look Impressive Until You Read Them Carefully

The Global State of RegTech 2026 report introduces a RegTech Adoption Index to measure maturity across six compliance domains. Financial Crime recorded the highest score at 68 out of 100, reflecting strong investment in sanctions screening, KYC/KYB, fraud prevention, and transaction monitoring. Information and Technology Security followed at 61. Market Conduct came in at 54.

At the spending level, 62.7% of firms plan to increase RegTech budgets in 2026. Nearly half (48.3%) expect to adopt new vendor solutions. Another 39% plan to expand use cases with existing providers.

These numbers describe a procurement cycle, not an operational outcome. Buying a RegTech platform and deriving defensible compliance value from it are different activities. The report itself hints at this. Its taxonomy covers 24 subcategories across six domains. The fact that Financial Crime scores highest at 68, in a domain where institutions have been investing for over a decade, suggests that adoption maturity across the remaining domains is still substantially below that threshold.

The Wolters Kluwer data fills in the gap. Only 31.8% of institutions have deployed AI or machine learning into production. Only 12.2% describe their AI/ML strategy as well-defined and resourced. Only 26.4% expressed confidence that their AI initiatives align with regulatory requirements. These are the institutions that already bought the tools. The tools are sitting on top of data infrastructure that is not ready for them.

The Bottleneck Has Moved

Five years ago, the RegTech bottleneck was adoption. Compliance teams were running on spreadsheets, legacy case management systems, and manual processes. The pitch from every vendor was: buy the tool, automate the workflow, reduce the headcount.

That pitch worked. The tools were bought. But the bottleneck did not disappear. It moved downstream, into the data layer. The FinTech Global analysis from May 11 captures this shift. Multiple RegTech vendors and industry leaders now describe the same pattern: the value is no longer in the point solution. It is in the orchestration layer, the data architecture, and the ability to connect compliance decisions to structured, queryable evidence.

Sebastian Hetzler of IMTF put it directly in that analysis: standalone tools will struggle in an environment where financial crime is increasingly cross-domain and real-time. The shift, he argues, is toward integrated platforms that act as orchestration layers, connecting detection, data sources, and workflows into unified decisioning.

This is a market signal, not a vendor pitch. When multiple competitors in the same sector independently describe the same structural problem, the problem is real. The RegTech industry has collectively discovered that the tool layer was the easy part. The data layer underneath it is what determines whether the compliance output is defensible.

Why Data Readiness Is Not a Technical Problem

The instinct at most firms is to treat data readiness as a technical project. Clean up the database. Migrate to a new system. Run a data remediation programme. Hire a consultant.

This misframes the problem. Data readiness in compliance is not about having clean data. It is about having structured, version-pinned, queryable evidence that connects every compliance decision to the documents and sources it was made on, at the time it was made, under the policy that applied at that time.

The Wolters Kluwer survey found that 58% of respondents still operate at a "Basic" or "Dependent" maturity level, meaning compliance functions remain largely manual, spreadsheet-driven, or heavily reliant on outside counsel. Nearly four in ten institutions operate with just one or two compliance professionals. A quarter of compliance staff across surveyed institutions are retirement-eligible within five years.

These numbers describe organisations that bought RegTech tools and are still running compliance on institutional memory and spreadsheets, because the data layer was never built to support anything else. The tool sits on top. The work still happens underneath, in the same manual processes the tool was supposed to replace.

For management companies and TCSPs, this is not an abstraction. A CSSF or FSC inspection does not test whether the firm purchased a sanctions screening tool. It tests whether the screening produced auditable, evidence-linked decisions that the firm can reproduce and defend. The tool is invisible to the supervisor. The data trail is everything.

The AMLA Supervisory Cycle Will Test the Data Layer, Not the Tool Layer

AMLA's direct supervisory cycle begins in 2028. The supervisor methodology published in December 2025 makes explicit how the scoring will work: inherent risk assessed on structured indicators across customer, product, geography, and channel dimensions. Controls quality assessed across seven categories. Residual risk derived from the combination.

The supervisor will not ask which RegTech vendor the firm uses. The supervisor will ask whether the firm's risk assessments are grounded in structured data, whether the customer due diligence files contain substantive reasoning (not template language), whether the business-wide risk assessment is queryable and traceable to individual customer decisions, and whether the firm can reproduce any compliance decision with the evidence that existed at the time it was made.

A firm that bought a RegTech tool and runs it on top of unstructured PDF files, inconsistent registry data, and manually maintained spreadsheets will not pass that test. It does not matter how sophisticated the tool is. The supervisor tests the output, and the output is a function of the data, not the tool.

The Global State of RegTech 2026 report notes that the industry has grown from fewer than 100 specialist providers to a multi-billion-dollar sector in just over a decade. What it does not say, but what the Wolters Kluwer data makes plain, is that the buyers of those tools have not made equivalent progress on the data infrastructure those tools require.

What This Means for Management Companies and TCSPs

For compliance officers at Luxembourg management companies, Mauritius fund administrators, and TCSPs under CSSF or FSC supervision, the practical question is not whether to increase RegTech spending. Most firms already have. The question is whether the data architecture underneath the tool stack can produce the outputs that a supervisor will actually test.

Three diagnostic questions are worth asking now. First, can the firm reproduce any compliance decision made in the last 12 months against the exact documents and policy that existed when it was made? If the answer involves searching email, calling a colleague, or opening a shared drive, the data layer is not ready. Second, are customer risk assessments stored as structured, queryable records, or as narrative text in PDF files? The AMLA methodology requires indicators that can be compared and scored. Narrative text cannot be scored. Third, does the firm's RegTech investment connect end-to-end, from document ingestion through risk assessment to periodic review, with a single auditable chain? Or does the chain break at some point into a manual step, a spreadsheet handoff, or a separate system with its own data model?

The firms that can answer those questions positively have a RegTech stack that works. The firms that cannot have a RegTech stack that reports well but does not produce defensible compliance.

The Industry's Next Phase Is Not More Tools

The Global State of RegTech 2026 report describes a market entering maturity. The data says otherwise. The market has matured at the procurement layer. It remains structurally immature at the data layer. The 95% adoption figure and the 9.5% readiness figure are not contradictory. They describe the same industry from two different vantage points: the vendor's pipeline and the buyer's operational reality.

The next phase of the RegTech industry will not be defined by new tools, new features, or new vendor categories. It will be defined by whether the data layer underneath the existing tools gets built to the standard that regulators are about to enforce. The firms that built the data layer first, before buying the tools, will spend the next two years optimising. The firms that bought the tools first will spend the next two years rebuilding underneath them.

Compliance is a data infrastructure problem. The RegTech industry has spent a decade proving it can sell tools. The supervisory cycle starting in 2028 will test whether anyone built the infrastructure those tools were supposed to run on.

If your firm is evaluating whether your RegTech investment is producing defensible, audit-ready outputs, or just dashboard metrics, we can help you assess the gap.