AI Powered Anomaly Detection and Fraud Prevention Course

Master AI anomaly and fraud detection using unsupervised, supervised and graph methods, cost-sensitive alerts and real-time monitoring.

Artificial Intelligence and Machine Learning Courses Confirmed

AI Powered Anomaly Detection and Fraud Prevention Course

Training Outlines

Introduction

Anomaly and fraud detection must identify rare, evolving behaviour without overwhelming investigators or disrupting legitimate customers. Historical labels are often incomplete, criminal strategies adapt to controls and the cost of false positives can be substantial. Effective systems therefore combine machine learning with risk typologies, operational rules, investigation evidence and continuous feedback.

This five-day course develops practical competence in AI-powered anomaly detection and fraud prevention. Participants will compare unsupervised, supervised, graph and sequence approaches; manage severe class imbalance; select cost-sensitive thresholds; and design real-time detection workflows. The course connects technical performance to investigation capacity, customer impact and fraud-loss reduction.

Objectives

By the end of this course, participants will be able to:

Define fraud events, anomalies and risk indicators.
Prepare transaction and behavioural detection data.
Apply unsupervised anomaly-detection methods.
Build cost-sensitive fraud-classification models.
Use graph and sequence evidence.
Optimise alerts for investigation capacity.
Monitor drift and adversarial adaptation.
Design a governed fraud-detection operation.

Course Content

Day 1: Fraud Risk and Detection Design

Fraud typologies and anomaly definitions
Events, entities and behavioural windows
Rules, supervised and unsupervised detection
Label delay and incomplete outcomes
Loss, customer and investigation costs
Detection-use-case design workshop

Day 2: Unsupervised Anomaly Detection

Statistical and robust anomaly scores
Isolation forests
One-class and density methods
Autoencoder-based anomaly detection
Temporal and peer-group anomalies
Anomaly-model comparison laboratory

Day 3: Supervised Fraud Modelling

Transaction and behavioural features
Imbalanced-data treatment
Tree and gradient-boosting models
Cost-sensitive learning
Calibration and alert thresholds
Fraud-model development laboratory

Day 4: Advanced Detection and Investigation

Graph-based fraud detection
Sequence and velocity patterns
Hybrid rules and model ensembles
Explanations and investigation evidence
Case ranking and alert prioritisation
Adversarial-pattern review

Day 5: Real-Time Prevention and Governance

Streaming scores and decision latency
Investigator feedback and label quality
Drift and fraud-strategy monitoring
Privacy, fairness and customer impact
Model change and incident control
Capstone fraud-prevention solution

Training Locations

This AI Powered Anomaly Detection and Fraud Prevention Course is available in multiple cities. Please select your preferred location from the list below

Durrës

Albania

Tirana

Albania

Andorra la Vella

Andorra

Escaldes-Engordany

Andorra

Innsbruck

Austria

Salzburg

Austria

Vienna

Austria

Gomel

Belarus

Minsk

Belarus

Antwerp

Belgium

Brussels

Belgium

Banja Luka

Bosnia and Herzegovina

Sarajevo

Bosnia and Herzegovina

Plovdiv

Bulgaria

Sofia

Bulgaria

Dubrovnik

Croatia

Split

Croatia

Zagreb

Croatia

Limassol

Cyprus

Nicosia

Cyprus

Brno

Czech Republic

Prague

Czech Republic

Aarhus

Denmark

Copenhagen

Denmark

Tallinn

Estonia

Tartu

Estonia

Helsinki

Finland

Tampere

Finland

Lyon

France

Marseille

France

Nice

France

Paris

France

Berlin

Germany

Frankfurt

Germany

Hamburg

Germany

Munich

Germany

Athens

Greece

Thessaloniki

Greece

Budapest

Hungary

Debrecen

Hungary

Akureyri

Iceland

Reykjavík

Iceland

Jakarta

Indonesia

Cork

Ireland

Dublin

Ireland

Florence

Italy

Milan

Italy

Naples

Italy

Rome

Italy

Osaka

Japan

Tokyo

Japan

Pristina

Kosovo

Prizren

Kosovo

Liepāja

Latvia

Riga

Latvia

Schaan

Liechtenstein

Vaduz

Liechtenstein

Kaunas

Lithuania

Vilnius

Lithuania

Esch-sur-Alzette

Luxembourg

Luxembourg City

Luxembourg

Kuala Lumpur

Malaysia

Malé

Maldives

St. Julian's

Malta

Valletta

Malta

Bălți

Moldova

Chișinău

Moldova

La Condamine

Monaco

Monte Carlo

Monaco

Budva

Montenegro

Podgorica

Montenegro

Amsterdam

Netherlands

Rotterdam

Netherlands

The Hague

Netherlands

Abuja

Nigeria

Lagos

Nigeria

Port Harcourt

Nigeria

Ohrid

North Macedonia

Skopje

North Macedonia

Bergen

Norway

Oslo

Norway

Gdańsk

Poland

Kraków

Poland

Warsaw

Poland

Faro

Portugal

Lisbon

Portugal

Porto

Portugal

Bucharest

Romania

Cluj-Napoca

Romania

City of San Marino

San Marino

Serravalle

San Marino

Belgrade

Serbia

Novi Sad

Serbia

Singapore

Bratislava

Slovakia

Košice

Slovakia

Bled

Slovenia

Ljubljana

Slovenia

Incheon

South Korea

Seoul

South Korea

Barcelona

Spain

Madrid

Spain

Valencia

Spain

Sri Jayawardenepura Kotte

Sri Lanka

Gothenburg

Sweden

Stockholm

Sweden

Bern

Switzerland

Geneva

Switzerland

Zurich

Switzerland

Kaohsiung

Taiwan

Taipei

Taiwan

Ankara

Turkey

Istanbul

Turkey

Kyiv

Ukraine

Lviv

Ukraine

Odesa

Ukraine

Dubai

United Arab Emirates

Birmingham

United Kingdom

Edinburgh

United Kingdom

London

United Kingdom

Manchester

United Kingdom

Rome (Vatican-adjacent)

Vatican City

Training Schedule

Below is the table of cities along with the respective dates for the upcoming training sessions of AI Powered Anomaly Detection and Fraud Prevention Course. Please review the schedule to find the most convenient option for you. You can also use the below search bar to type the city name and filter the results.