INTERVIEW
Player Protection Reimagined: How AI and Neuroscience Drive Early Detection at Mindway AI
Inside the partnership of advanced artificial intelligence and neuroscience expertise powering new standards in player protection, risk detection, and responsible gambling.
Interview with Paula Murphy
Our editor had a conversation with Paula Murphy, Head of Business Development (UK) at Mindway AI, exploring how neuroscience, artificial intelligence, and regulatory insight are driving advances in player protection and risk detection. Readers will gain a clear, evidence-based perspective on the measurable benefits, challenges, and industry best practices shaping innovation in responsible gambling.
Paula Murphy, Mindway AI – Championing transparency in responsible gambling, June 2025. Photo courtesy of Mindway AI / Paula Murphy
Box-out: Paula Murphy – Industry Bio
Current Title: Head of Business Development (UK)
Company: Mindway AI
Previous Roles: Founder & Managing Director, KnowNow Ltd; Managing Director, Wilmington PLC Legal Division
Sector Experience: Over 8 years in responsible gambling, regulatory compliance, and commercial partnerships across Europe
Expertise: Player protection technology, regulatory engagement, industry compliance standards
Recognition: European Casino Awards 2025—Woman of the Year nominee; Hipther Top 50 iGaming Speakers 2024
Introduction
For Mindway AI and its UK business development lead Paula Murphy, player protection is not just about the technology—it’s about leveraging specialist decision-making from psychologists with extensive experience in gambling behavior and teaching algorithms to identify real player risk. The core principle is simple: using patterns from clinical assessment to make early detection actionable for operators.
Neuroscience & AI: Mapping complex behavioral data
The Interview: Mindway AI and the Human Touch
Paula Murphy’s journey in player protection began with a focus on compliance rather than technology. “Fifteen years ago, working in compliance at Wilmington PLC, I saw a need for credible standards in an industry often facing negative public perception,” she recalls.
This conviction drove her to found KnowNow in 2017, one of the UK’s first firms dedicated solely to compliance and safer gambling strategy. Murphy ran the KnowNow Limited Responsible Gambling Conference for five years, building an impressive network and a deep understanding of the operational challenges UK operators face.
Her transition to Mindway AI was both timely and serendipitous: “I noticed a post from a longstanding client on LinkedIn that matched exactly what I was looking for—helping operators meet increasingly strict legislative requirements with science-based technology. I reached out to Mindway AI’s CEO, Rasmus Kjaergaard, and the partnership began.” Now, in her role as Head of Business Development for the UK, Murphy helps drive the adoption of responsible gambling innovation in a rapidly evolving regulatory landscape.
From Medicine to Gambling: How GameScanner Works
Mindway AI began as an academic spin-out from Aarhus University in Denmark, led by Professor Kim Mouridsen—whose pioneering work initially trained AI to help doctors interpret brain scans on stroke patients.
The transition toward gambling harm detection began after a collaboration with a Danish clinic treating people with gambling problems. Inspired by the methodology used for stroke detection, Mouridsen and his team began to research whether the same approach—using expert ratings and clinical assessments—could train an algorithm to identify, detect, and most crucially, prevent gambling problems at an early stage.
Rather than relying solely on statistical modeling, GameScanner’s system was designed to learn the subtle markers of risk validated by psychologists, who reviewed comprehensive data—from spin-by-spin play and transaction history to patterns of customer contact—and scored player behaviors on a scale from 0 to 100.
One of GameScanner’s unique outputs is this risk score, used to segment players into five escalating bands. At the lowest levels, the system might trigger a simple pop-up or self-help tool. As the score rises, the operator’s response escalates: direct outreach, deposit controls, and referral to support services. This nuanced progression reflects real-world therapeutic logic, calibrated to shift from automated notification to focused human contact as the risk increases.
Early detection is the centerpiece of Mindway’s strategy, separating their approach from blunt intervention or pure statistical flagging.
Night-time gambling risk depends on behavioral context, not just timing—understanding this difference is key to effective harm detection
Night Play Example—Context Matters when evalutaing risk:
Let’s explain it a bit further:
Gambling at night was long considered a universal risk marker for problem gambling, but Murphy explains the importance of context:
Player A: Plays at night only to place occasional sports bets in a timezone where games air late; this might reflect no underlying risk.
Player B: Gambles intensively most nights without a clear external trigger, signals escalating risk.
GameScanner is designed to distinguish these behavioral roots, avoiding overflagging while allowing real harm to be surfaced for early intervention.
Commercial Value – The Operator’s Perspective
Retaining customers in a safe and engaged manner generates a higher lifetime value than pursuing short-lived “binge bursts” of high spending, which often result in churn and reputational risk. Recent research suggests that up to 70% of iGaming revenue is generated during periods of active player engagement—not at registration—while retention can yield five times the return of acquisition, according to analyses by SOFTSWISS and Optimove (“Human Touch, Digital Reach in iGaming Marketing”).
Player Protection and Cultural Differences
Today, Mindway AI’s GameScanner is deployed in a wide range of markets, where local gambling patterns—from Brazil’s surge in micro-betting to Europe’s established casino verticals—often reflect national preferences and technology use.
Paula Murphy notes that, while the expressions of problematic gambling—like loss-chasing or impulsive betting—are consistent across regions, the root causes can differ by gender, age, and cultural norms.
Mindway AI’s approach adapts to these nuances: the system learns from region-specific data and player profiles, yet ensures that early intervention and player protection standards are met, regardless of market environment.
Regulation and the Rule Shift: A UK Example
The UK is often seen as a bellwether for player protection regulation, with the Gambling Commission pushing for a transition from passive compliance to active intervention.
The new three-part requirement—identify, act, and evaluate—requires operators to use real-time risk screening and to log every instance of intervention for regulatory review.
Paula Murphy explains: In the UK, operators are expected not just to monitor high spenders but to act long before hard monetary thresholds are crossed. GameScanner and Gamalyze give operators instant risk scores, detailed reports, and a compliance dashboard logging every step—from pop-up warnings to direct outreach—over time, which makes it easier to detect but also provide evidence of what has been done to strengthen gambling protection.
Mindway AI’s tools are built to be configurable for each market, mirroring local rules and reporting needs: for example, stricter intensity scoring and auditing in the UK, different documentation and intervention protocols in Germany, Spain, or Brazil.
Murphy notes, however, that rapidly diverging regulatory models—such as strict mandatory interventions in Germany—pose industry-wide risks, especially if requirements fragment rather than harmonize.
The ultimate goal, she emphasizes, is to maintain a flexible technical and audit trail framework that supports early, meaningful player protection and cross-jurisdictional compliance, without sacrificing operational efficiency or the core mission of early intervention.
Machine learning transforms complex data into actionable insights, powering advanced AI solutions for gaming analysis and regulatory compliance.
The Future: AI’s Promise and Perils
“Think of it as still the Nokia brick phone era, and we have many leaps to go to the iPhone,” says Paula Murphy, highlighting the early stage of AI adoption in responsible gambling.
The true transformative steps—integrating machine learning with large language models for adaptive, timely interventions—are just starting to materialize. Mindway AI’s latest product modules now address both player protection and anti–money laundering, aiming to increase operational efficiency as well as the reach of these safeguards.
Yet substantial risks remain. Regulation continues to evolve, and so do the ways AI can be misapplied. AI tools, Murphy notes, may blur the line between protection and engagement, or risk drifting into surveillance. “There’s a risk that the industry can drift into surveillance if we’re not vigilant—and it’s not enough to claim to be responsible, we need the evidence and transparency to back it.” She points out that calls for transparency and auditability are not just ethical imperatives, but are fast becoming industry norms.
Perceptions present a further challenge. “The industry is still viewed as a faceless monster that does not care. We have to show—not just tell—that we’re building a more genuinely protective environment,” Murphy observes. For operators and third-party suppliers alike, she argues, independently audited solutions and open dialogue with regulators are critical to building trust.
Mindway AI, for its part, is prioritizing transparency through its partnerships with regulatory bodies such as the Hellenic Gaming Commission in Greece. By publishing its Gamalyze tool on the HGC’s official site and co-developing risk frameworks tailored to the Greek market, Mindway seeks to create a model of collaborative, evidence-based player protection that spans entire jurisdictions, not just single licensees.
The Competitors and The Expanding Landscape
Mindway’s strategy sits alongside both other vendors and evolving in-house systems.
Competitors include BetBuddy (IGT), Gaming Analytics, Genius Sports, and Tecpinion, all offering variations of behavioral analysis, risk detection, and personalized interventions. Some, like FullStory and LeanConvert, focus on UX-driven risk scoring.
A key risk, sector analysts warn, is that unregulated or poorly audited AI might be used for exploitative retention rather than harm prevention. Only transparent, independently audited, and regulator-approved solutions will gain long-term acceptance.
Personal perspective
“At the end of the day, when I come home to my children after a long day, I can say I spent the whole day making a difference in people’s lives—and that feels good.”
— Paula Murphy, Head of Business Development at Mindway AI
Conclusion
Mindway AI’s evolution from university spin-out to international supplier reflects broader trends in the responsible gambling field, where technology, clinical expertise, and regulatory demands are increasingly intertwined. Early detection, scalable intervention, and transparent reporting have become central to the player protection agenda.
For operators, new platforms offer gains in efficiency, risk management, and compliance, but also bring new challenges as regulators refine their demands and public trust remains mixed. As player protection moves from regulatory checkbox to commercial value, the interaction between AI, personalized intervention, and direct regulatory engagement will likely shape the future landscape.
Recent partnerships with regulators—such as the Hellenic Gaming Commission—and advances in explainable AI suggest the sector is seeking a more collaborative, transparent approach. Whether these efforts are enough to address established concerns about industry reputation and accountability remains an open question, but the groundwork is being laid for more robust, data-driven standards in years to come.
