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Responsible Artificial Intelligence (AI) in Banking and Insurance

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In the words of Einstein, "Technological progress is like an axe in the hands of a pathological criminal." This statement underscores the intricacies of technology. Artificial Intelligence (AI), beyond just ChatGPT, empowers intelligent machines to make decisions about loans, employment, claim handling, and more. However, AI is far from flawless. The intricate models sometimes result in incomprehensible decisions, which can lead to unconscious bias and severe errors.  We will shed light on the risks faced in the financial sector, and solutions like stricter regulation, heightened awareness, and responsible AI tools. 

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

These objectives aim to provide participants with a comprehensive understanding of responsible AI practices, particularly in the context of banking and insurance. By examining real-world examples and case studies, participants will gain insights into potential pitfalls, ethical considerations, and the tools necessary for shaping a responsible AI future.  This course  is not about learning how to create or use AI in your daily activities but to cope with AI in a responsible and ethical way.

 

Level Advanced
Learning format Classroom training

Total price *

Members: € 330
Non-members: € 360
Partners/ BZB: € 330
Incompany: tailor-made, prices on request

* Are you entitled to an allowance or subsidy?
* Price: service in the context of continuing professional training, exempt from VAT

CPD Hours Banking: 3h general
Insurances: 3h general
Consumer credit: 3h general
Mortgage credit: 3h general
Compliance: 3h

Continuing Professional Development

Available dates

13/12/2024 - 09:00u - 12:30u - Responsible Artificial Intelligence (AI) in Banking and Insurance

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Please let us know you're interested in this training should there be no date available, the planned date does not suit you and/or this session is full. As soon as about 5 people are registered on the interest list, we will propose a new course date. Your registration on the interest list is free of charge and without any obligation.

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Target group

This training course can be followed by multiple target groups:

  • legal and regulatory professionals;
  • compliance officers;
  • Fintech entrepreneurs;
  • data protection officers;
  • technology and IT professionals;
  • risk Managers;
  • financial analysts and consultants;
  • data analysts;

Required prior knowledge

Advanced level training: this training requires a general basic knowledge of AI concepts or prior experience with them. This course assumes familiarity with basic AI terminology and principles to effectively engage with the content.

Programme

CONTENT

  • Introduction
    • Responsible AI: Definition and Significance
    • Main Risks of AI (Non-discrimination, Privacy, Black Box)
  • Fairness in AI
    • Understanding Non-discrimination and Protected Groups
    • Origins of Bias in AI Models
    • Measuring Fairness in AI
    • Mitigating Bias in AI
    • Case Studies: Credit Scoring and HR Analytics
  • Explainable AI
    • Importance of Explaining Predictive Models
    • GDPR and AI Act Requirements for Explanation
    • Link Between Explainability and Fairness
    • Case Studies: Credit Scoring, Fraud Detection, and Healthcare
  • Generative AI: Risks and Benefits
    • Potential Risks of Generative AI
    • Opportunities in Generative AI
  • Responsible AI Governance
    • Establishing a Responsible AI Program
    • Key Components of AI Governance
  • Conclusion

 

PRACTICAL INFORMATION

  • Duration: ½ day of training (3 class hours)
  • Hours: 09:00 to 12:30
  • Location: Febelfin Academy: Phoenix building, Koning Albert II-laan/Boulevard du Roi Albert II 19, 1210 Brussels
  • Language: This training will be given in English

Methodology

You follow a ‘Classroom training’ in a group. You, the other participants and the teacher are all present in the same classroom at an agreed time. There is an opportunity for interaction and feedback, both from the participants to the teacher and vice versa. The teaching material consists as a basis of a presentation via the MyFA learning platform, supplemented with various other items (such as digital syllabus, presentation, audiovisual fragments, etc.).



Training material: 

  • PowerPoint presentation (slides)

Teachers

David Eric K Martens
Compliance & audit
Risk, finance & treasury