How AI compliance is shaping the future of regulated gaming
As regulated gaming takes root in the Gulf, operators are betting that artificial intelligence will deliver the trust regulators demand without sacrificing scale. The Game LLC, the licenced operator of The UAE Lottery, has moved to embed AI-driven screening from Napier AI as part of a broader push to pair innovation with demonstrable compliance. The choice is an early indicator of how regulated gaming in emerging jurisdictions may be governed and scaled going forward.
The Game LLC was awarded the UAE Lottery licence by the General Commercial Gaming Regulatory Authority (GCGRA) in July 2024, and the operator has been working to align its product rollout with international best practice. As part of that work, Napier AI’s Client Screening solution was integrated in under 11 weeks, with the vendor reporting early reductions in false positives that free compliance teams to focus on genuine threats. Those operational improvements matter in a newly regulated market where onboarding volumes and public visibility will both scale quickly.
Why AI screening matters to gaming
Gaming platforms combine large volumes of consumer accounts with frequent financial flows. That creates three linked risks that AI screening is designed to mitigate: identity impersonation, sanctioned or high risk individuals slipping through onboarding, and transactional abuse.
Discussing this matter further, SiGMA News spoke to Aaditya Uthappa, Co-Founder of Accorian and GORICO. He said, “Around 15 years ago most of the data was on servers, from there it went to network, from there it went to cloud and today it went to AI. So, the entire landscape of how data moves through the entire networks for an organisation has completely changed. Also, most companies are on a lot of third-party solutions like third-party SaaS, various cloud service providers. Because of that, the complexity of protecting your data is a lot more and that is why you need tools of today.” Those are operational realities that a lottery operator must address at scale.
He also named impersonation as the single biggest immediate risk for money handling platforms. “I think the biggest security risk is, you know, first is impersonation. There are a lot of defects that are going around. So having very strong Know Your Customer (KYC) is important for these organisations.”
He emphasised the payments side too and said, “Second is because it’s money so it’s very important for these organisations to protect the entire pipe, wherein money can be added seamlessly but securely and similarly taken out seamlessly but securely.”
AI reduces burden on human teams
Legacy name screening and sanctions checks suffer from high false positive rates that create significant manual workload. Independent vendor case studies and industry analyses show AI models and data enrichment can lower false positives and save investigators time. For example, Silenteight cites project results showing false positive reductions of up to 45 percent under the right data conditions. That kind of efficiency gain is precisely what operators say they are seeking when they choose modern screening platforms.
Similarly, HSBC reported a 20 percent reduction in false positives for money laundering detection by automating system rules with AI, demonstrating how operational efficiency and compliance effectiveness can be improved through modern technology.
Inside compliance with Napier AI
To understand how AI is reshaping compliance from within, SiGMA News also spoke to Dr. Janet Bastiman, Chief Data Scientist at Napier AI. Speaking on how AI-driven platforms like Napier AI’s solutions are reducing manual compliance workloads and improving operational efficiency, Dr Janet said that smarter systems can reduce false positives, sharpen detection, and deliver real economic savings, but AI must be implemented responsibly, with human oversight at its core to ensure compliance remains effective. She said, “The Napier AI / AML Index 2024-2025 finds that money laundering costs $5.5 trillion across the globe, around 5 percent of GDP. But regulated firms could recover more than $3.3 trillion annually by implementing AI into Anti-Money Laundering (AML) solutions. Smarter systems can help reduce the noise, sharpen detection, and deliver real economic savings. Not only could it increase the effectiveness of anti-financial crime strategies, but also efficiency.”
She further explained that shifting geopolitics and technological innovations are rapidly changing the way criminals operate under the radar. “AI can play a central role in navigating these risks and is often seen as the silver bullet for reducing alert volumes for compliance teams, lowering false positive rates, and improving accuracy in flagging suspicious transactions. While AI is a powerful tool for enriching the context of alerts, detecting patterns in customer behaviour, or predictive risk scoring, it needs to be implemented in the right way, with humans at its core,” she said.
“When we trust AI systems without question, criminals can quickly learn how to get past the algorithms. If human judgement is lost, crime can slip through the net. There may be a reduction in false positives, but in reality it is just happening under the radar. In anti-money laundering, the most effective way of implementing AI to put compliance first, and this looks different for every regulated institution,” added Dr. Janet.
On future AI trends in compliance, Dr. Janet said generative AI has reached its hype peak, with institutions often chasing novelty over suitability. She emphasised the need for trustworthy AML solutions that deliver automation from day one and said, “Generative AI has peaked in its hype cycle, and some financial institutions are chasing its novelty, rather than its suitability. High upfront costs and complex implementations are huge risks. The technology is not the problem, rather, the approach. There will be a growing need for the delivery of trustworthy AML solutions that improve automation from the day of go-live, and not simply AI bolt-ons to improve inefficient systems.”
“Progress is already underway. Supervision in Europe is particularly setting the trend to explainable AI. As regulators continue to pave the way for greater AI guardrails around transparency, explainability and auditability, organisations should start focusing on data readiness, and governance. The future of AI and compliance is not going to be about jumping on the newest trends, but embedding it responsibly, with measurable impact from day one,” she added.
Market momentum & regulator expectations
Regulatory and market drivers are converging to accelerate RegTech adoption. The global regtech market was valued at about US$15.8 billion in 2024 and is projected to grow sharply in the coming years as firms invest in automation, monitoring and AI to meet complex cross-border rules. That expanding market reflects demand not only from banks and payments firms but from other sectors that handle regulated flows, including gaming.
For a federal licence holder such as The Game LLC, early adoption of AI screening provides concrete proof points to regulators. If regulators see clear reductions in false positives and low-risk alerts, along with faster, more accurate investigations, licence holders may gain greater operational flexibility and quicker approvals for new product features.
Regional implications
The UAE has positioned itself as an early mover in the Gulf by creating a federal commercial gaming regulator and awarding a national lottery licence. By publicly embedding AI compliance tools, The Game LLC provides a model for other Gulf operators entering newly regulated markets. Membership of the UAE Lottery in international bodies and the public reporting of compliance investments will make it easier for regulators in neighbouring jurisdictions to benchmark expected controls.
Uthappa framed the regulatory contrast succinctly, noting that while operational challenges are similar across regions, the regulatory landscape differs significantly. The United States and Europe are at the forefront of security regulations, including the Health Insurance Portability and Accountability Act (HIPAA) for electronic health data, System and Organisation Controls (SOC and SOC2) for customer data, and standards from the National Institute of Standards and Technology (NIST). The European Union (EU) also enforces the General Data Protection Regulation (GDPR) and the EU Artificial Intelligence Act (EU AI Act), one of the leading frameworks for AI security. In contrast, many countries in Africa and Asia lack comparable regulations, leaving the international standard ISO/IEC 27001 (Information Security Management System) as the default benchmark.
Practical trade offs and what to watch
According to the AIFinTech100 Report 2024 by FinTech Global, AI screening is not a complete solution on its own. Three key questions will determine its effective adoption:
- Measuring Effectiveness: Can vendors provide clear, auditable data showing that false positives have fallen while true positives are still detected?
- Customer Onboarding: Can AI screening be added without slowing down or frustrating legitimate customers during onboarding?
- Responsible AI Use: Can operators demonstrate that AI tools are used responsibly, without bias and with transparent decision-making for regulators?
These issues are considered solvable, but the answers will determine how quickly AI screening becomes standard practice.
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