Day01
AI Foundations for For Banking Operations
- AI capabilities, limitations and business value
- Machine learning, generative AI and large language model concepts
- Selecting high-value AI use cases
- Data requirements and model inputs
BFSI-017
Banking, Financial Services and Insurance
PROGRAMME BROCHURE
Generative AI for Banking Operations
Five days of practical AI application, governance and implementation for For Banking Operations.
KAIZEN EUROPEAN ACADEMY
Executive & Professional Development
www.kaizeneurope.academy
01
Programme Overview
This five-day Kaizen European Academy programme is specifically about Generative AI for Banking Operations; AI is the core subject throughout all five days. Participants learn how artificial intelligence and generative AI can be applied to For Banking Operations, design practical workflows, evaluate tools and outputs, manage governance and risk, and build an implementation roadmap supported by hands-on exercises.
02
Learning Objectives
Explain the AI, generative AI and automation concepts most relevant to For Banking Operations.
Identify and prioritize high-value AI use cases in For Banking Operations.
Design practical human-AI workflows and validate AI outputs for For Banking Operations.
Manage privacy, bias, security, governance and human-oversight risks when using AI in For Banking Operations.
Build a practical AI pilot and implementation roadmap for For Banking Operations.
Who Should Attend
Professionals, specialists, supervisors and managers whose responsibilities involve generative ai for banking operations or who need to build practical capability in this area.
Programme Methodology
Instructor-led explanation, facilitated discussion, subject-specific case studies, practical templates, individual and group exercises, simulations or technical scenarios where appropriate, peer review and a final implementation workshop.
Learning Outcomes
Explain the AI, generative AI and automation concepts most relevant to For Banking Operations. Identify and prioritize high-value AI use cases in For Banking Operations. Design practical human-AI workflows and validate AI outputs for For Banking Operations. Manage privacy, bias, security, governance and human-oversight risks when using AI in For Banking Operations. Build a practical AI pilot and implementation roadmap for For Banking Operations.
Prerequisites
No formal prerequisite is required. Relevant professional experience is helpful; technical courses may assume basic familiarity with the operating environment.
03
Course Outline
Day02
AI Use Cases and Workflow Design in For Banking Operations
- Prompt design and interaction patterns
- Human-AI workflow design
- AI-assisted analysis and decision support
- Automation and intelligent agents
Day03
AI Tools, Data and Automation for For Banking Operations
- Evaluating accuracy, hallucination and output quality
- AI governance and accountability
- Bias, fairness and responsible AI
- Privacy, confidentiality and information security
Day04
Responsible AI, Risk and Governance in For Banking Operations
- Model risk and human oversight
- AI adoption and change management
- AI value measurement and ROI
- Building an AI implementation roadmap
Day05
Applied AI Lab: For Banking Operations Implementation
- Vendor and platform evaluation
- AI policy and acceptable-use controls
- Practical AI workflow prototyping
- Scaling AI safely across teams
04
What You Will Receive
Programme learning materials
Practical resources and templates where applicable
Kaizen completion certificate
Participant support throughout the learning week
Kaizen European Academy
Executive & Professional Development across selected European destinations.
CONTACT & INFORMATION
Website: www.kaizeneurope.academy
Contact: www.kaizeneurope.academy/#contact