Risk & Fraud Analyst / Manager – iGaming

We are seeking a highly analytical professional to own and evolve our in-house risk assessment, scoring and player behaviour modelling systems across our online casino brands.

You will work closely with Data, BI, Product and Engineering to ensure our scoring engine is accurate, scalable, regulatory-aligned and capable of detecting high-risk behaviour in real time. This role blends fraud/risk expertise, data analysis, and product thinking. You will analyse player patterns, fraud typologies and operational outcomes to design, refine and optimise our internal risk algorithms, risk weights, and automated decision flows.

You’ll monitor gameplay and payment activity, identify fraud patterns (multi-accounting, bonus abuse, chargebacks, account takeovers, affiliate fraud), and implement effective controls and rules. In this role you’ll work closely with Payments, Customer Support, Compliance/AML and Product to keep our platforms safe, compliant and friction-free.

Key Focus Areas:Fraud monitoring & investigations

• Monitor player activity, game sessions and transactions across casino and sportsbook to identify suspicious behaviour and fraud patterns.
• Detect and investigate: multi-accounting and identity manipulation, bonus abuse, arbitrage and promotion misuse, payment fraud, chargebacks, card testing and stolen card usage, account takeovers, collusion, chip dumping and affiliate abuse.
• Perform in-depth case investigations, collect evidence, and document findings in line with internal policies and regulatory requirements.​​​​​​​Escalate complex or high-value cases to Compliance, AML, Legal or Senior Management as appropriate.

​​​​​​​Data Analytics & Behavioural Insights

• Analyse large datasets (transactional, gameplay, KYC, incident outcomes) to identify fraud patterns, bonus abuse signals, collusion indicators and account takeover risk.
• Build and maintain dashboards/reports for risk scoring KPIs, including model performance, trigger frequency, risk distributions and trend changes.
• Conduct retrospective analysis on fraud losses, blocked cases and resolved investigations to refine scoring mechanisms.
• Work with Product and Developers to translate fraud patterns into automated risk rules, workflow logic, and real-time decision pathways.
• Design rule hierarchies, exception handling and escalation logic for the risk engine.
• Validate that model outputs integrate cleanly with player flows, payments processes, and back-office workflows.
• Assist in testing, QA and versioning of new risk engine releases and rule updates.

Payments & withdrawals

• Review and approve deposits, withdrawals and refunds in line with internal fraud, KYC and AML policies.
• Handle chargeback cases end-to-end: gather evidence, prepare representments, liaise with payment providers and optimise win rates.Identify trends that impact payment operations (e.g., payment method abuse, PSP issues) and propose improvements.

KYC, CDD & compliance support

• Review and verify player KYC documents (ID, proof of address, payment instruments) and ensure adherence to internal onboarding standards and regulatory guidelines.
• Support ongoing CDD/EDD reviews of higher-risk or VIP players in line with AML and Responsible Gambling obligations.Work closely with Compliance / AML teams to ensure fraud processes support licensing requirements (e.g., MGA, UKGC, local regulators) and internal policies.

Risk Scoring Model Development, Tools Rules and Analytics

• Develop and enhance in-house risk scoring models for player activity, transactions, gameplay behaviour and identity integrity.
• Define risk factors, scoring weights, thresholds and logic rules for automated decisions (e.g., auto-blocks, auto-holds, auto-verifications).
• Incorporate behavioural analytics, device intelligence, velocity checks, payment fingerprints and lifecycle events into scoring logic.
• Evaluate scoring performance (precision, false positives/negatives, operational impact) and continuously iterate to improve detection accuracy.
• Use internal risk engines, third-party fraud tools and manual controls (velocity checks, device fingerprinting, geo/IP analysis, behavioural rules) to prevent and detect fraud.
• Maintain and fine-tune fraud rules and alerts to minimise false positives while reducing loss.
• Analyse player and transaction data to identify emerging trends, new typologies and gaps in current controls; propose and implement enhancements.
• Prepare regular reports and dashboards (KPIs such as fraud rate, chargeback ratio, bonus abuse, block/approval rates, false positive rates) for management.
• Own the fraud & risk strategy, roadmap, KPIs and budget for your area.
• Evaluate and select new tools or vendors (KYC providers, device intelligence, risk engines).

Collaboration & process improvement

• Work closely with Customer Support, Payments, AML/Compliance, Responsible Gambling, Product and Business Intelligence to ensure a seamless, low-friction but safe player experience.
• Provide feedback and training to Support and Payments teams on emerging fraud patterns and how to handle player contacts.
• Contribute to the continuous improvement of policies, SOPs and documentation for fraud, risk and payments.
• Participate in regulatory audits and internal/external reviews related to fraud and risk.
• Line-manage Analysts / Specialists: hiring, coaching, performance reviews and scheduling.
• Set clear objectives and development plans for team members, and foster a culture of data-driven decision-making.

What we’re looking for:

• 4+ years’ experience in fraud, risk, payments or KYC/AML – ideally in iGaming, payments, fintech or e-commerce
• Strong analytical skills ( SQL, Excel, BI tools (Power BI / Looker / Tableau) and a data-driven mindset, with the ability to translate patterns into structured logic and scoring components.
• Great attention to detail and comfort making decisions with imperfect information
• Direct experience in online casino
• Experience handling chargebacks and payment disputes.
• Experience with risk rules, scoring logic, alert design or workflow automation in a risk engine.
• Understanding of iGaming fraud types: multi-accounting, bonus abuse, chargebacks, botting, collusion, ATO, affiliate abuse.
• Comfortable working with product/engineering teams in a structured development environment.
• Experience with predictive modelling, machine learning features, or supervised learning in a risk context, exposure to data exploration or model testing.
• Experience working with device fingerprinting, behavioural biometrics or real-time risk evaluation tools, understanding of AML/EDD requirements and how they intersect with fraud and risk scoring.

Why join us?

• Competitive salary and performance bonus
• Remote work options (depending on location)
• Opportunity to work with /develop modern fraud tools and tech
• A fast-moving, international team where your work has visible impact