The document summarizes a webinar on AI-driven fraud detection. The webinar was hosted by Maxime Dehaut from Codit Luxembourg and Frank Roessig from Telindus Luxembourg. The agenda included discussing the context of AI-driven fraud detection, use cases, and the outlook for the field. It also provided information on how fraud is a significant cost factor, how fraudsters are using increasingly complex strategies, and how fraud touches many sectors. Additionally, it reviewed AI/ML adoption rates, the fraud management lifecycle, functionalities for prevention and detection, and presented a reference case study on an AI design experience program.

1. Webinar: AI-Driven Fraud Detection
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2. Your Hosts
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Lead Architect
Codit Luxembourg
Maxime Dehaut
Head Cloud Apps, Data & AI
Telindus Luxembourg
Frank Roessig

3. Agenda
| Context on AI-Driven Fraud Detection
| Use-Cases
| Outlook
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4. Online Transactions
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5. Fraud is a significant cost factor
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6. Fraudsters using Increasingly Complex Strategies
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7. Fraud touches many Sectors
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8. AI/ML Adoption
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Operationalised
Models 20% Adopters80%
Model
Management
Business driven
initiatives
Company Culture
25%
40%
Skills & Expertise
55%
50%
Source: Gartner, McKinsey, O’Reilly – Reports from 2019 & 2020

9. Fraud Management
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Prevention
Treatment
Detection
Recovery

10. Prevention & Detection
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Data
Operations
Practices

11. Functionalities
October 2020 Webinar: AI-Driven Fraud Detection 11
PracticesData
Operations
ENRICHMENT
INGESTION
VISUALISATION
EXPLORATION
EXPLAINABILITY
GOVERNANCE
SECURITY
MONITORING
EXECUTION
AUTHORING
CASE MANAGER
PIPELINE
ANALYTIC ENGINE
RULE ENGINE

12. Augmented Rule Engine
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As a ServiceUncertainty
Accountability
& Ownership
Feedback loop

13. ML-driven Fraud Management System
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MATURITY
SOPHISTICATION
AI/ML
Platform
CTI
Explainability
Fairness & Diversity
Governance
Robustness &
Security
Rule-based &
Analytic
Models
Cognitive &
Probabilistic
Analytics

14. Reference case
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AI Design
Experience
Transform your AI vision into reality with this
jumpstart program
| Finetune your AI business case during an
interactive workshop
| Sharpen your AI vision with real-world use
cases
| Demonstration of how an AI solution is
operationalized with MLOps
| First Proof of Concept with your actual
data
| Insights on the Azure PaaS architecture

15. Thanks for Attending
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