eyeDP has closed a late seed funding round, the company said, with the round closing on 28 March. eyeDP did not disclose the amount raised or name its investors, describing them as a network of experienced angel investors and strategic industry figures.

The company, which launched in 2025, said it has seen early growth through pilot deployments and increased demand for document intelligence tools as AI-driven fraud rises.

Over the next 12 months, eyeDP said it will focus on product development, including expanding the range of documents the platform can process, improving accuracy, and progressing toward “fully automated, dynamic intelligent document processing.” It also plans to grow its team to support scaling.

eyeDP also pointed to partnership activity aimed at accelerating adoption, including an integration with the Provenir Data Marketplace, a reseller agreement with Devcode, a distribution partnership with Crucial Compliance, and a collaboration with IDVcheck focused on strengthening anti-money laundering capabilities.

Warren Russell, CEO at eyeDP, said: “We’ve been building towards this for some time. This investment gives us the ability to stay focused on what matters, improving the product, scaling the team, and solving a problem that’s only becoming more complex as fraud evolves. Our goal is simple: to give regulated organisations clarity and confidence in every decision they make.”

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SEON, the command centre for immediate Fraud Prevention and AML Compliance, has unveiled AI Reality Check: 2026 Fraud & AML Leaders Report, the second iteration of its sector research, derived from a worldwide survey of 1,010 leaders in fraud, risk, and compliance spanning payments, fintech, financial services, retail, eCommerce, and gaming.

The figures reveal an unforeseen narrative: AI is ubiquitous, yet operations are not becoming easier to manage. Currently, 98% of organizations utilize AI in fraud and AML processes, with 95% expressing confidence in its effectiveness; meanwhile, headcount plans rose from 88% to 94% year-over-year, and 83% anticipate budget increases in 2026.

Complexity Is Surpassing Automation

AI has not lessened the workload — it has revealed the extent of work that has always existed. Fraud losses are increasingly approaching revenue growth, threats are advancing more rapidly, and disjointed systems restrict the true potential of AI at scale. Key year-over-year shift:​

Leadership’s confidence in their teams’ performance is lagging. The number of leaders who disagreed with the statement, “fraud losses are growing faster than revenue,”​ dropped by almost 40% from the previous year

Inside the Numbers:​

AI is baseline, not experimental​

• 98% already integrate AI into daily workflows (only 2% still planning)​
• 95% are confident AI can detect and prevent fraud (52% very confident)​
• Top use case: AI/ML for transaction monitoring (30%)​

Fraud and AML investment keeps climbing​

• 83% expect fraud/AML budgets to increase in 2026​
• 94% plan to add at least one full-time hire (up from 88% in 2025)​
• 85% plan to add a vendor, 49% plan to replace one​

Fragmentation is the bottleneck​

• 95% claim “some integration” between fraud and AML systems​
• Only 47% run fully integrated workflows; the rest rely on partial connections​
• 80% say getting a unified view of data is challenging​

For many, time-to-value remains slow​

Only 10% go live in under two weeks​
38% take 1–3 months, 24% take 4+ months​
When implementations run long, top impacts include increased costs (52%) and prolonged fraud exposure (47%)​

Teams are growing, not shrinking​

94% plan to increase headcount despite automation gains​
85% see AI agents as support/augmentation, not replacement (only 12% see eventual replacement)​

Top fraud threats reported:​

• Account takeovers: 26%
• Promo/discount abuse: 18%
• Return fraud: 18%​

“Fraud and financial crime were supposed to become more manageable as AI matured,” said Tamas Kadar, CEO and co-founder, SEON. “Instead, 2026 is the year leaders are confronting a more complicated reality. AI adoption is real, confidence is high, but the scale and pace of fraud — compounded by fragmented systems — continue to drive increased investment rather than reduced overhead. The bottleneck is no longer whether AI works. It’s everything around it: disconnected data, siloed teams, slow implementations. The organisations that pull ahead will be the ones that unify fraud and AML intelligence, shorten the distance between threats and controls, and treat integration as strategy, not plumbing.”​

Fast-Growing Companies Invest in Integration Early​

Organisations growing 51%+ are nearly twice as likely as slower peers to report that achieving unified visibility is “not very challenging.” They treat integration as infrastructure, not an IT project.​

What’s Next: From “Does AI Work?” to “Can We Trust It?”​

With adoption near-universal, the conversation is shifting to governance, explainability and accountability:​

• 78% say decentralised digital identity will become central to fraud/AML​
• 33% cite data privacy regulations (GDPR, CCPA) as the biggest external force shaping AML​
• 25% point to criminals’ advancing use of AI and obfuscation techniques​

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Licensed online gambling groups operating in both the United Kingdom and Germany are subject to two distinct anti-money laundering (AML) supervisory architectures. The distinction is reflected in the allocation of statutory responsibility, the structure of reporting obligations, and the implementation of monitoring mechanisms under law.

This article presents a structural mapping of these frameworks based exclusively on statutory texts and official supervisory publications. No interpretive grading or comparative assessment is included.

Allocation of Supervisory Responsibility

In Great Britain, the Gambling Act 2005 designates the UK Gambling Commission (UKGC) as the regulator of licensed gambling activities. Casino operators are classified as “relevant persons” under the Money Laundering, Terrorist Financing and Transfer of Funds (Information on the Payer) Regulations 2017 (as amended). Accordingly, they are subject to AML obligations prescribed by law, including firm-wide risk assessment (Regulation 18), customer due diligence, enhanced due diligence where required, ongoing monitoring, and suspicious activity reporting pursuant to the Proceeds of Crime Act 2002.

Under the UK regulatory structure, AML monitoring and internal controls are implemented at operator level and supervised by the UKGC pursuant to its mandate, including licence conditions, compliance assessments, and published enforcement outcomes.

In Germany, the Glücksspielstaatsvertrag 2021 (GlüStV 2021) establishes the Gemeinsame Glücksspielbehörde der Länder (GGL) as the competent supervisory authority for licensed online gambling. In parallel, the Geldwäschegesetz (GwG) classifies operators of games of chance as obligated entities (Verpflichtete) and subjects them to AML requirements defined by statute, including institutional risk analysis, due diligence measures, ongoing monitoring, and suspicious transaction reporting to the Financial Intelligence Unit (FIU Germany).

Beyond the AML obligations under the GwG, GlüStV 2021 establishes centralized monitoring systems, including LUGAS (Länderübergreifendes Glücksspielaufsichtssystem) and OASIS (national self-exclusion system). Licensed operators are required to integrate with these systems in accordance with legal provisions.

The allocation of supervisory responsibility in each jurisdiction determines how AML controls are implemented and which authority reviews compliance.

Reporting Architecture

In the United Kingdom, suspicious activity reports (SARs) are submitted to the National Crime Agency (NCA) under the Proceeds of Crime Act 2002 and associated regulations. The reporting obligation arises where an operator knows or suspects, or has reasonable grounds for knowing or suspecting, that a person is engaged in money laundering, as defined by law.

Under German law, obligated entities must submit suspicious transaction reports to the Financial Intelligence Unit pursuant to the Geldwäschegesetz. The reporting obligation is triggered in accordance with the GwG.

For operators active in both jurisdictions, this results in reporting relationships with distinct competent authorities operating under separate legal mandates.

Group-Level Compliance Governance

For corporate groups holding licences in both jurisdictions, the allocation of AML responsibility differs in structure.

Within the UK system, AML supervision of licensed gambling operators is integrated into the mandate of the UK Gambling Commission, while suspicious activity reporting is directed to the National Crime Agency.

Within the German system, AML obligations arise under the Geldwäschegesetz, while gambling supervision is exercised by the GGL pursuant to GlüStV 2021, alongside the operation of centralized monitoring systems established by law.

Accordingly, compliance governance at group level must align with jurisdiction-specific legal structures. Internal control systems, documentation standards, reporting procedures, and monitoring integrations must reflect the supervisory architecture applicable to each licensed entity.

These structural distinctions do not alter the requirement to comply fully with the law in each jurisdiction. However, they determine how compliance responsibilities are distributed and supervised within a multi-license corporate structure.

Concluding Observation

A structural comparison of the United Kingdom and Germany confirms that AML supervision within the licensed online gambling sector is implemented through nationally defined legal and supervisory frameworks.

For multi-jurisdictional operators, effective compliance governance requires alignment with each jurisdiction’s defined legal structure rather than reliance on procedural uniformity across entities.

This mapping is derived exclusively from statutory texts and official supervisory publications. Detailed jurisdictional records are maintained within the GamingMarkets Regulatory Matrix.

Oren Dalal is the Founder & Publisher of GamingMarkets.com, an independent regulatory intelligence platform mapping statutory and supervisory frameworks across licensed online gambling jurisdictions. His work is grounded in primary-source legislative analysis, focusing on AML supervisory architecture and compliance governance in multi-jurisdictional groups.

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