MGA 2025 Report: Where AI Fits in Malta iGaming

Most companies treat regulation like a brake. The MGA’s Interim Performance Report for January–June 2025 reads more like a steering wheel.

Across just six months, the Malta Gaming Authority processed 28 new licence applications and issued eight licences, ran 723 criminal probity screening checks, completed seven full-scope compliance audits, handled 1,720 player assistance requests, reviewed 75 URLs tied to unregulated activity, and carried out 4,198 inspections of gaming premises. Those aren’t “nice-to-have” numbers. They describe the operating reality for iGaming in Malta: high-volume, high-accountability, and constantly audited.

This is exactly where intelliġenza artifiċjali fl-iGaming f’Malta becomes practical—not as a buzzword, but as infrastructure. If you’re running marketing, compliance, player support, risk, or product for an MGA-licensed operator, AI isn’t about doing more “cool stuff”. It’s about coping with scale without losing control.

The MGA report signals a simple truth: scale demands automation

The key message is straightforward: the MGA is supervising a sector where the workload is measurable, repeatable, and time-sensitive. That’s prime territory for automation—especially AI for iGaming compliance, monitoring, and multilingual player communications.

Look at the supervisory footprint in the first half of 2025:

• 87 thematic reviews focused on compliance, player protection, and sports betting integrity
• 891 player funds reports received and 9 data extractions carried out
• 11 AML/CFT Compliance Examinations initiated and 11 concluded (plus remediation measures on three licensees)

When regulators operate at this cadence, operators need systems that produce consistent evidence, traceable decisions, and fast responses.

Here’s my stance: AI is most valuable in Malta’s iGaming sector when it reduces “manual risk”—the mistakes, gaps, and delays that happen when you rely on spreadsheets, inboxes, and ad-hoc human processes.

What “good” AI looks like under MGA oversight

Under a regulator like the MGA, “good AI” is:

• Auditable: you can explain how an output was produced
• Constrained: clear rules and guardrails exist (no free-form chaos)
• Logged: actions and decisions are recorded for later review
• Human-owned: accountability stays with the operator, not a vendor tool

That mindset aligns with the report’s emphasis on structured authorisation and supervision.

Licensing and fit-and-proper: AI’s role is speed, not shortcuts

The authorisation section of the report shows the MGA is actively filtering risk:

• 34 Fit and Proper Committee decisions, with four not meeting criteria
• 16 licence applications reviewed by the Supervisory Council
• Two applications rejected due to false, misleading, inaccurate, or materially incomplete information (after the Minded Letter process)

This matters because many operators want AI to “handle” documentation. That’s the wrong target.

The right target is using AI to reduce admin friction while increasing consistency.

Practical AI use cases for licensing readiness

Answer first: AI helps operators prepare cleaner, more complete submissions and maintain evidence-ready records.

Examples that actually fit the Maltese regulatory environment:

1. Document quality checks

   • Flag missing fields, inconsistent dates, mismatch between policies and operational procedures
   • Compare versions of key documents (AML policy, RG policy, complaints handling) and highlight differences

2. Controlled knowledge retrieval

   • Use an internal, permissioned AI assistant trained only on your approved internal policies to answer staff questions like: “What’s the escalation time for player complaints?”

3. Board and key-person onboarding workflows

   • Automate checklists, reminders, and evidence packaging for due diligence files

The goal isn’t to “write a policy with AI”. It’s to operationalise the policy so your team follows it, and you can prove it.

Supervision, player protection, and support: AI should reduce response time

The report states the MGA resolved 1,720 requests for assistance (including spill-over from 2024). That number reveals something operators often underestimate: player communication volume is regulatory volume. Every complaint, clarification, or payment issue creates potential exposure if mishandled.

Multilingual player communication is no longer optional

Malta-based operators serve global markets, and that means multilingual support and content. This is where AI content generation for iGaming can be helpful, provided you treat it as a controlled system.

What works in practice:

• Drafting multilingual FAQs and help-centre content, then human-reviewing for accuracy and tone
• Building intent-based routing so players are guided to the right process (payments, KYC, RG, complaints)
• Summarising support tickets to improve handover between agents

What doesn’t work:

• Letting a chatbot improvise on topics like withdrawals, bonuses, or self-exclusion rules

A better approach is “answer-with-sources” support: the AI responds only if it can cite an approved internal article; otherwise it escalates to a human. That keeps you fast without becoming reckless.

Player funds reporting and audit readiness

Between January and June 2025, the MGA received 891 player funds reports and conducted 9 data extractions. For operators, that points to one operational discipline: your data has to be exportable, reconcilable, and explainable.

AI can help by:

• Detecting anomalies in balances and transaction flows earlier
• Auto-generating reconciliation narratives for internal review (not for final submission without checks)
• Monitoring for patterns that indicate operational issues (failed withdrawals, repeated chargebacks, suspicious account behaviour)

If you’re thinking, “We can do that with BI,” you’re right. The advantage of AI is speed in interpreting messy, multi-source data—especially when paired with strict controls and sign-off.

AML/CFT and integrity: AI is a force multiplier, but governance is non-negotiable

The MGA report highlights significant AML oversight: 11 AML/CFT Compliance Examinations initiated, 11 concluded, and 16 interviews on prospective MLROs to ensure knowledge and awareness of the Maltese framework.

That tells you the bar is not dropping. It’s rising.

Where AI helps AML teams (without creating new risk)

Answer first: AI improves detection and triage, but you still need explainability and human decision-making.

Strong, realistic applications include:

• Alert triage: clustering similar alerts, prioritising by risk factors, reducing analyst fatigue
• Narrative assistance: drafting internal case summaries using structured inputs (transactions, player profile, trigger reason)
• Entity resolution: matching players across systems and identifying linked accounts more reliably

If your AI can’t explain why it flagged an account, it’s not ready for regulated operations. Treat “black box scoring” as a liability unless you can defend it.

Sports betting integrity and suspicious betting reports

The MGA received 149 suspicious betting reports and shared 88 alerts with licensees, participating in 30 investigations globally. This is one of the clearest signals that Malta’s ecosystem is built for cross-border data exchange.

AI can support integrity by:

• Detecting unusual betting patterns in near real-time
• Correlating event-level anomalies with account networks
• Improving the quality of reports by standardising descriptions and evidence packaging

The operators that do this well don’t just “catch more”. They produce cleaner, more actionable intelligence.

Enforcement and advertising: AI should prevent mistakes before they become penalties

Enforcement actions from January to June 2025 included:

• 23 cease and desist letters
• 15 warnings
• 23 administrative penalties totalling €139,360
• One licence cancellation

On the commercial side, the Commercial Communications Committee made four decisions regarding possible breaches of the Gaming Commercial Communications Regulations.

That’s the business case for AI in iGaming marketing in Malta: not just higher output, but safer output.

AI guardrails for marketing and commercial communications

If you’re producing multilingual ads, landing pages, CRM messages, affiliate briefs, and social content, the risk is consistency. One poorly translated line can create a compliance headache across multiple markets.

A practical setup I’ve found effective looks like this:

• Pre-approved copy blocks for sensitive topics (bonuses, terms, eligibility, RG messaging)
• An AI compliance checker that flags restricted phrases, missing T&Cs cues, or risky claims
• Market-specific rules (what’s acceptable in one jurisdiction may be prohibited in another)
• A mandatory human approval step with logging and version control

This is where AI shines: it catches “small” issues at scale, before they become warnings or penalties.

A simple operating model for AI adoption in MGA-licensed businesses

If you’re planning AI projects in Malta’s regulated iGaming space, the winning pattern is boring—but it works.

Start with the regulator’s favourite words: evidence and controls

Build AI projects around:

1. Clear scope (what the AI can and can’t do)
2. Approved knowledge base (policies, help-centre articles, SOPs)
3. Audit logs (who asked what, what was answered, what was approved)
4. Human sign-off for player-impacting outcomes
5. KPIs that matter (response time, complaint resolution time, false positives, QA scores)

A quick checklist for operators

Use this before rolling anything out:

• Can we reproduce the same output tomorrow with the same input?
• Do we know which policy or rule supports the output?
• Is there a defined escalation path when the AI isn’t confident?
• Are we storing prompts and responses securely?
• Can compliance and RG teams review the system without engineering help?

If you can’t answer “yes” to most of these, you’re not blocked—you’re just early.

What the MGA’s interim report really means for AI in Malta iGaming

The MGA’s January–June 2025 activity levels show a mature regulatory environment that expects pace, accuracy, and proof. That’s the soil where AI automation in iGaming grows best—especially for multilingual content delivery, player engagement, and compliance operations.

As this series on Kif l-Intelliġenza Artifiċjali qed tittrasforma l-iGaming u l-Logħob Online f’Malta keeps building, one theme is getting clearer: the winners won’t be the operators who “use AI”. They’ll be the operators who build controlled systems that make audits easier, support faster, and marketing safer.

If you’re thinking about AI for your MGA-licensed operation, don’t start with a chatbot. Start with one workflow you can measure—say, ad copy QA, ticket summarisation, or AML alert triage—then build the governance around it. Speed comes naturally once the controls are in place.

Where do you see the biggest bottleneck in your operation right now: compliance evidence, player support volume, or multilingual marketing throughput?