Accounting and Finance

Artificial Intelligence in Banking and Financial Services

This course provides a comprehensive foundation in the application of Artificial Intelligence (AI), machine learning, and cognitive modelling within the financial services sector. Designed specifically for professionals in banking, asset management, financial services and governance, it explores how these technologies are reshaping client engagement, risk profiling, predictive analytics, and operational efficiency. Course participants will gain a solid understanding of the fundamental logic behind AI and machine learning within the industry, and how these tools can be applied to better understand client behaviour, assess risk appetite, and tailor services to individual objectives. The course also highlights the transformative potential of AI in enhancing the customer experience across various touchpoints in financial services. In addition to practical applications, such as time-series analysis and predictive modelling, the course also explores the integration of AI with legacy systems, identifying both opportunities and operational challenges.

AF-002Vienna - AustriaAccounting and Finance
Course schedules
Upcoming dates Classroom
Start date End date Location Fee Registration
Vienna - Austria
€2,125 + VAT
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Barcelona - Spain
€1,925 + VAT
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Paris - France
€2,250 + VAT
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London - United Kingdom
€2,100 + VAT
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Amsterdam - Netherlands
€2,125 + VAT
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London - United Kingdom
€2,100 + VAT
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Istanbul - Türkiye
€1,425 + VAT
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Vienna - Austria
€2,125 + VAT
→
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Why Attend

This course provides a comprehensive foundation in the application of Artificial Intelligence (AI), machine learning, and cognitive modelling within the financial services sector. Designed specifically for professionals in banking, asset management, financial services and governance, it explores how these technologies are reshaping client engagement, risk profiling, predictive analytics, and operational efficiency.

Course participants will gain a solid understanding of the fundamental logic behind AI and machine learning within the industry, and how these tools can be applied to better understand client behaviour, assess risk appetite, and tailor services to individual objectives. The course also highlights the transformative potential of AI in enhancing the customer experience across various touchpoints in financial services.

In addition to practical applications, such as time-series analysis and predictive modelling, the course also explores the integration of AI with legacy systems, identifying both opportunities and operational challenges.

Course Objectives
  • Understand how AI and machine learning can be used to assess client profiles, risk appetite, and financial objectives
  • Identify how AI technologies enhance customer experience across various areas of financial services
  • Apply AI concepts to time-series analysis and broader predictive analytics
  • Evaluate practical challenges and integration issues when adopting AI alongside legacy systems
  • Assess gaps between AI expectations and real-world outcomes, including the risk of overpromised benefits
Designed for

This program is intended for professionals involved in Accounting and Finance.

  • This course is ideal for anyone in the banking and financial services industry, who are exploring the use of AI to support their role or organization.
Course Methodology

The courses focuses on an interactive approach to knowledge transfer as well as practical studies and engagement of participants in an interactive Q&A format.

Course content
Day1

Foundations of Artificial Intelligence (AI) and Machine Learning (ML) in Finance

  • Introduction to AI and ML - Evolution of search algorithms (Google, Microsoft, etc.)
  • Overview of cognitive modelling and neural networks
  • Supervised vs. Unsupervised learning
  • Training vs. Inference - Teaching models to learn from data
  • Making predictions from trained models
The certificate

SPARK Training Certificate of Completion is awarded to participants who attend and complete the full training course.

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