The Fraud Detection with Data Analytics Training Course offered by Imperial Corporate Training Institute is a comprehensive and practical programme designed to equip professionals with advanced analytical skills to identify, prevent, and investigate fraud using modern data-driven techniques. In today’s digital economy, organisations face increasingly sophisticated financial crimes, cyber fraud, insider manipulation, and transactional anomalies. This data analytics training course provides participants with structured methodologies, real-world case studies, and hands-on tools to detect fraudulent patterns, analyse risk indicators, and build predictive fraud detection models.
This course combines statistical analysis, machine learning concepts, forensic data examination, and fraud risk management frameworks to help professionals proactively combat fraud across banking, insurance, retail, telecommunications, healthcare, and public sectors. Participants will learn how to extract actionable insights from large datasets, detect red flags through anomaly detection techniques, and implement internal control systems powered by analytics. By the end of this programme, learners will confidently apply data analytics tools to strengthen organisational integrity, reduce financial losses, and improve compliance mechanisms.
Objectives
By completing this Fraud Detection with Data Analytics Training Course, participants will be able to:
- Understand the fundamentals of fraud risk management and fraud typologies.
- Identify common fraud schemes including financial statement fraud, payment fraud, cyber fraud, and procurement fraud.
- Apply statistical and analytical techniques to detect irregularities and suspicious patterns.
- Use data visualisation tools to uncover hidden trends and anomalies.
- Implement predictive modelling techniques for fraud risk assessment.
- Develop machine learning-based fraud detection models.
- Design internal controls supported by data analytics.
- Conduct fraud investigations using structured analytical approaches.
- Evaluate transactional datasets to identify red flags.
- Build automated fraud monitoring dashboards.
- Strengthen compliance and regulatory reporting using analytics-driven insights.
- Improve decision-making through risk scoring models.
- Interpret key fraud detection metrics such as false positives, precision, recall, and ROC curves.
- Create fraud prevention frameworks aligned with organisational policies.
- Apply forensic data analytics techniques for investigative reporting.
Target Audience
This data analytics training course is ideal for:
- Data analysts and business intelligence professionals
- Internal auditors and external auditors
- Risk and compliance officers
- Finance managers and financial controllers
- Fraud investigators and forensic accountants
- Banking and financial services professionals
- Insurance claims analysts
- Cybersecurity professionals
- IT audit specialists
- Government regulatory officers
- Corporate governance professionals
- Business managers responsible for risk oversight
- Professionals seeking to specialise in fraud analytics
- Graduates and early-career professionals interested in fraud detection careers