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Data Mining Techniques for Fraud Analytics

An Interactive 5-Day Training Course

Data Mining Techniques for Fraud Analytics

Uncovering Hidden Patterns and Anomalies to Strengthen Fraud Detection Efforts

NASBA
Classroom Schedule
Date Venue Fees
04 - 08 May 2026 Dubai $ 5,950
17 - 21 Aug 2026 Dubai $ 5,950
05 - 09 Oct 2026 Amsterdam $ 5,950
14 - 18 Dec 2026 London $ 5,950

Course Summary

In an increasingly data-saturated world, organisations face growing volumes of transactions and interactions that can mask sophisticated fraudulent behaviour. Traditional detection systems often fall short in identifying emerging risks hidden within complex datasets. The Data Mining Techniques for Fraud Analytics training course bridges the gap between raw data and actionable fraud intelligence by introducing core data mining techniques that support fraud detection and proactive risk management. Participants will gain practical knowledge on uncovering unusual patterns, relationships, and trends that signal potential fraud, enhancing both investigative and preventive capabilities.

Throughout five days, participants are guided through essential components of data mining including data preparation, model evaluation, classification, clustering, and association techniques tailored to fraud analytics. The training course emphasises practical application of analytical workflows to detect anomalies, evaluate model effectiveness, and integrate data mining within broader fraud strategies. By focusing on real-world scenarios and analytical methods, the Data Mining Techniques for Fraud Analytics training course equips professionals with the ability to support robust fraud detection frameworks and contribute to organisational fraud prevention goals.

Skills & Competencies

From this Data Mining Techniques for Fraud Analytics training course, participants will develop the following key skills and competencies:

  • Data mining methodology and application
  • Anomaly detection and pattern recognition
  • Classification and clustering proficiency
  • Fraud analytics model evaluation
  • Data preparation and feature engineering
  • Analytics-driven risk detection

Key Learning Outcomes

At the end of Data Mining Techniques for Fraud Analytics training course, you will learn to:

  • Understand key concepts and methodologies of data mining.
  • Identify fraud types detectable through analytical techniques.
  • Apply classification and clustering methods for anomaly detection.
  • Evaluate effectiveness of data mining models for fraud analytics.
  • Prepare and validate data for analytical workflows.

How You Will Learn

Participants will explore structured learning modules that explain data mining concepts and fraud analytics workflows through visual demonstrations, step-by-step explanations, and practical examples. Learning emphasises clear communication of analytical techniques without requiring programming expertise, making the content accessible to both technical and non-technical professionals.

Who should Attend?

This training course is designed for professionals responsible for fraud risk management, auditing, compliance, analytics, and related roles involving data-driven fraud detection.

This Data Mining Techniques for Fraud Analytics training course is suitable to a wide range of professionals but will greatly benefit:

  • Fraud investigators and analysts
  • Internal and external auditors
  • Risk and compliance officers
  • Data and business analysts
  • IT professionals supporting fraud detection initiatives
  • Managers seeking enhanced fraud detection capability
Course Outline
Day 1

Introduction to Data Mining and Fraud Analytics

This day introduces the scope of fraud analytics and the fundamentals of data mining processes tailored to fraud detection. Participants explore fraud types suited to analytic approaches and frameworks like CRISP-DM. The topics covered will include:

  • Understanding the scope of fraud and fraud analytics
  • Introduction to data mining: objectives and process
  • Types of fraud suitable for data mining approaches
  • Key components of a fraud analytics program
  • Overview of the CRISP-DM framework
Day 2

Data Preparation and Exploration

This day focuses on data preparation, cleaning, transformation, and exploratory analysis techniques essential for fraud analytics. Participants learn feature engineering and handling imbalanced data. The topics covered will include:

  • Identifying and sourcing relevant data for fraud analysis
  • Data cleaning, transformation, and integration techniques
  • Exploratory data analysis and visualization for anomaly detection
  • Feature engineering and selection for fraud indicators
  • Handling imbalanced datasets and missing values
Day 3

Classification and Prediction Models

This day examines key classification techniques and model validation strategies for fraud detection. Participants explore performance metrics and methods to optimise predictive models.
The topics covered will include:   

  • Introduction to classification techniques (decision trees, logistic regression, etc.)
  • Training and validating predictive models for fraud detection
  • Performance evaluation metrics: accuracy, precision, recall, ROC curves
  • Overfitting, model tuning, and cross-validation strategies
  • Applications of classification in transaction and identity fraud
Day 4

Clustering and Association Techniques

This day emphasises unsupervised learning techniques such as clustering and association rules to detect patterns in behaviour and transactions. Participants explore segmentation and link analysis. The topics covered will include:   

  • Understanding unsupervised learning in fraud analytics
  • Clustering methods (K-means, DBSCAN) for behavioral analysis
  • Market basket analysis and association rule mining
  • Identifying fraudulent patterns through segmentation and link analysis
  • Selecting appropriate models for specific fraud cases
Day 5

Integrating Data Mining into Fraud Strategy

This day integrates data mining practices into operational fraud management workflows. Participants learn how to operationalise models and ensure interpretability and alignment with business objectives. The topics covered will include:  

  • Building a data mining workflow for fraud detection
  • Operationalizing fraud analytics models
  • Ensuring model interpretability and business alignment
  • Challenges and limitations of data mining in fraud prevention
  • Summary and practical steps for implementation
Certificates
  • On successful completion of this training course, GLOMACS Certificate will be awarded to the delegates.
  • Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.
Providers

Endorsed Education Provider

NASBA
Options & Brochure
Related Certificates
NASBA

Customisation & In-House Delivery

Delivering this in-house training course enables organisations to align data mining and fraud analytics techniques with internal detection frameworks, business priorities, and industry-specific risk considerations. Customisation ensures that analytical skills and methodologies directly support organisational fraud prevention strategies and analytical maturity.

Why Choose Saudi GLOMACS?

Saudi GLOMACS is the official Saudi Arabian division of GLOMACS International (glomacs.com), delivering internationally recognised training courses both within Saudi Arabia and across international locations. Our training courses are aligned with the highest professional and institutional standards, supported by a strong understanding of the professional landscape in Saudi Arabia and access to global expertise.

Saudi GLOMACS enables professionals and organisations to strengthen leadership, capability, and long-term excellence through consistently high-quality learning experiences.

Official Saudi Presence

Official Saudi Arabian division of GLOMACS with established global credibility.

International Benchmarks

Internationally benchmarked training courses aligned with professional best practices.

Trusted Across Sectors

Trusted by professionals and institutions across public and private sectors.

Flexible Delivery

Training courses delivered within Saudi Arabia and across international locations.

Additional Benefits of this course for Organisations and Professionals in Saudi Arabia

Organisations & Professionals in KSA will have the following additional benefits from this Data Mining Techniques for Fraud Analytics training course:

  • Improved capability to detect complex fraud patterns
  • Stronger analytics-driven fraud prevention frameworks
  • Enhanced data interpretation and risk insight
  • Increased investigative confidence and accuracy
  • More effective collaboration with data science teams
  • Reduced operational and fraud risk impact
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Frequently Asked Question

No. Saudi GLOMACS delivers courses in Saudi Arabia and internationally, including delivery across Europe and Asia. This allows organisations and professionals to access training both locally and abroad.

No. While governance and leadership are part of the portfolio, Saudi GLOMACS delivers training across the entire business and professional lifecycle, including administrative, technical, legal, regulatory, and sector-specific training.

No. Our training courses are delivered globally through international locations and online platforms, enabling participants from Saudi Arabia and around the world to learn together. This global delivery approach ensures exposure to diverse perspectives, international best practices, and cross-cultural insights while maintaining strong relevance to regional and organisational needs.

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Yes. Saudi GLOMACS designs and delivers bespoke in-house training tailored to organisational objectives, sector requirements, and workforce needs. Training can be delivered in Saudi Arabia or internationally, depending on requirements.

Yes, in-house and customised strategy training courses are available to support organisations seeking tailored strategic capability development. These courses can be aligned with your industry context, organisational challenges, and long-term strategic objectives.

For further details or to discuss customisation requirements, you may call or WhatsApp +966 (54) 286 8546 or email info@glomacs.sa . You can also submit a detailed enquiry through our in-house training page at: https://sa.glomacs.com/in-house-seminars

If you would like further information about these training courses, our team is available to provide professional guidance and support. We are pleased to assist with course selection, the registration process, and any other related enquiries.

For personalised assistance or detailed enquiries, please contact our team on +966 (54) 286 8546 or email us at info@glomacs.sa

Courses delivered in Saudi Arabia are adapted to reflect local regulatory frameworks, organisational structures, sector conditions, and professional expectations. This ensures training is relevant, practical, and aligned with Saudi workplace realities.

GLOMACS has been delivering professional training for over thirty years, with courses delivered across Europe, the Middle East, Asia, and other international markets.

Saudi GLOMACS combines three decades of global training experience with a clear focus on Saudi market relevance. This allows it to deliver training that is both internationally credible and locally applicable, across a broader range of disciplines than niche or single-focus providers.

Saudi GLOMACS is a Saudi-based professional training provider delivering courses tailored to the Saudi market and applicable internationally. It operates within the global GLOMACS framework and draws on more than three decades of international training experience.

Saudi GLOMACS offers professional training across a wide range of disciplines, including administration, leadership and management, governance and regulation, law, oil and gas, energy, engineering, finance, digital technologies, and sector-specific specialisations.

Training supports professionals across all career stages, from operational roles to specialist and senior responsibilities.

Participants include professionals from public sector, semi-government, and private sector organisations, across a wide range of roles and industries. Attendees range from administrative and operational professionals to technical specialists, managers, and senior decision-makers.

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