Fraud Intelligence Specialist

Role Purpose

The primary role of the Fraud Intelligence Specialist is to identify, assess and communicate emerging fraud and integrity risks through the effective application of Fraud intelligence analysis principles. The role transforms information into actionable intelligence by understanding Risk Owner requirements, evaluating relevant information sources, applying appropriate analytical techniques, collaborating with stakeholders, and developing clear, evidence-based assessments. As a critical 2nd Line of Defence role, the Specialist supports informed decision-making, strengthens fraud risk awareness, by providing intelligence that can help identify control vulnerabilities and opportunities for improvement.

Key Accountabilities

As part of fulfilling a 2nd Line of Defence role, tasks include

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Monitor and review of transactional reports daily to identify suspicious activities and mitigate fraud.

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Collect data through daily tracking of identified and reported fraudulent transactions and through ad hoc reports from Business Objects.

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Analyze and synthesize data and information from a variety of sources and translate it into meaningful intelligence.

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Provide data-driven analysis to formulate forecasts and actionable insights.

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Produce weekly and monthly overviews and trending of existing and emerging fraud threats.

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Identify emerging fraud threats and provide recommendations on system controls, establishment of policies and improvement of operational procedures.

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Conduct intelligence-led investigations and targeted assessments into identified or emerging fraud and integrity risks, drawing together relevant information to establish patterns, linkages and potential business impact.

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Provide timely notification to Teams Leads/Manager of any identified emerging fraud trends or issues.

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Disseminate monthly and ad hoc reports to support Risk Owners with regard to observed fraud trends and related recommendations; this includes delivering monthly verbal updates.

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Establish and review of internal (Fraud Intelligence Team) and external (Risk Owners and other support teams) ways of working.

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Liaise with IHG teams that provide operational support to Risk Owners to provide recommendations on improvement of operational procedures.

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When required, liaise with hotels in confirming fraudulent transactions.

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Liaise with third party service providers of Risk Owners to discuss on identified fraud trends and related recommendations to improve daily flagging of suspicious activities.

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Provide support in Fraud Dashboard’s development and assist in establishing reporting capabilities to easily identify emerging fraud patterns.

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Contribute in optimising the team’s Fraud Data Analytics (FDA) capability through daily collection of data and review of flagged transactions.

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Use approved AI capabilities responsibly, including developing AI agents, to enhance intelligence analysis, identify relevant patterns, automate appropriate workflows and improve efficiency, while ensuring outputs are critically assessed and validated through analyst judgement.

Key Skills & Experiences

Education

Formal education in a relevant field of work or an equivalent combination of formal education and work-related experience in Fraud & Integrity Risk Management, Data Analysis, Investigation and Case Management.

Experience

The role requires experience in large-scale Data Analysis, Fraud Detection and Investigation preferably in the hotel/hospitality sector, with a Loyalty Programme.

Technical Skills and Knowledge

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• Good understanding of key Intelligence and Fraud Risk Management principles
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• Good grasp and application of the Intelligence Process and analytical techniques
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• Strong analytical, critical thinking and problem-solving skills
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• Ability to analyse large and complex datasets to identify patterns, trends and anomalies
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• Good investigation skills and ability to develop evidence-based intelligence assessments
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• Strong written and verbal communication skills in English
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• Intermediate to advanced Excel and data analytics skills
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• Working knowledge of responsible AI use, including AI-assisted analysis, automation and agent development
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• Working knowledge of SQL for querying and analysing data is an advantage
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• Experience in dashboard and data visualisation tools such as Tableau, Looker Studio or similar is an advantage