Course : Detecting Risks and Fraud with AI

Practical course - 2d - 14h00 - Ref. IUA
Price : 1720 € E.T.

Detecting Risks and Fraud with AI



New course

This training course provides an understanding of modern fraud mechanisms and teaches participants how to leverage artificial intelligence to strengthen monitoring systems. Participants will learn how to detect anomalies, automate controls, and secure sensitive processes in order to improve decision-making and manage operational risks.


INTER
IN-HOUSE
CUSTOM

Practical course in person or remote class
Disponible en anglais, à la demande

Ref. IUA
  2d - 14h00
1720 € E.T.




This training course provides an understanding of modern fraud mechanisms and teaches participants how to leverage artificial intelligence to strengthen monitoring systems. Participants will learn how to detect anomalies, automate controls, and secure sensitive processes in order to improve decision-making and manage operational risks.


Teaching objectives
At the end of the training, the participant will be able to:
Identify the main types of fraud and areas of vulnerability in business processes.
Analyze weak signals and atypical behaviors to detect operational risks.
Leverage AI approaches to automate controls and improve monitoring systems.
Secure sensitive processes by incorporating regulatory requirements and best practices in governance.

Intended audience
Fraud managers, finance departments, auditors, internal auditors, compliance officers, and anyone involved in risk prevention, internal controls, or ensuring the security of operational processes.

Prerequisites
None

Practical details
Teaching methods
The instructor assesses the participant's learning progress throughout the training course using multiple-choice questions, role-playing exercises, hands-on activities, and so on.

Course schedule

1
Understanding Modern Fraud Schemes

  • Identify the main types of financial, operational, and document-related fraud.
  • Analyze the behaviors and methods used by fraudsters within organizations.
  • Identify areas of vulnerability within sensitive processes.
  • Detect weak signals and early warning indicators of incidents or anomalies.
Hands-on work
Analysis of a fraud scenario and mapping of the associated risks.

2
Strengthen controls over operational processes

  • Monitor disbursement transactions and secure sensitive payments.
  • Prevent supplier fraud and ensure the reliability of procurement processes.
  • Secure HR, payroll, and administrative processes for employees.
  • Strengthen controls related to expense reports and financial documentation.
Hands-on work
Development of a control framework for a sensitive business process.

3
Leveraging Artificial Intelligence to Improve Surveillance

  • Understanding the uses of AI in detecting anomalies and atypical behavior.
  • Implement predictive approaches to identify fraud risks.
  • Automate alerts, checks, and operational monitoring mechanisms.
  • Speed up investigations through automated data and event analysis.
Hands-on work
Identification of an AI use case applicable to a business context.

4
Analyze anomalies and expedite investigations

  • Develop a process for analyzing detected alerts and incidents.
  • Prioritize investigations based on risk level and business impact.
  • Use the available data to strengthen the analysis.
  • Document the findings of the investigation and the security recommendations.
Case study
Case study on anomaly analysis and alert prioritization.

5
Regulating AI Use and Securing Data

  • Understanding the regulatory issues related to the use of artificial intelligence.
  • Ensure the reliability and quality of the models used in control systems.
  • Reduce algorithmic bias and enhance transparency in data processing.
  • Secure sensitive data and control access to critical information.
Hands-on work
Development of a plan for the security and governance of AI applications.

6
Implement a strategy for risk prevention and management

  • Develop a comprehensive approach to preventing fraud and operational risks.
  • Define monitoring indicators and mechanisms for managing controls.
  • Raise awareness among teams about best practices for detection and prevention.
  • Develop a plan for the continuous improvement of monitoring systems.
Hands-on work
Development of a prevention action plan tailored to a specific work environment.



This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.

Dates and locations
Select your location or opt for the remote class then choose your date.
Remote class

Dernières places
Date garantie en présentiel ou à distance
Session garantie

REMOTE CLASS
2026 : 17 Dec.

2027 : 18 Jan., 24 May, 1 July, 26 Aug., 14 Oct., 2 Dec.

PARIS LA DÉFENSE
2026 : 10 Dec.

2027 : 18 Jan., 24 May, 1 July, 26 Aug., 14 Oct., 2 Dec.

BRUXELLES
2027 : 18 Jan., 24 May, 1 July, 14 Oct.

LUXEMBOURG
2027 : 18 Jan., 24 May, 1 July, 14 Oct.



This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.