AI for Banking & Financial Institutions is a course in using AI safely and within regulation at banks and financial institutions, covering documents and reports, transaction and portfolio analysis, customer service, and risk and compliance support. It suits staff at banks, securities firms and insurers, and risk, compliance and internal audit teams.
Banks and financial institutions are an industry with large volumes of data and documents, under strict regulation, and demanding very high data accuracy and security. Routine tasks such as preparing documents and reports, communicating with customers, analyzing transaction and portfolio data, summarizing policies and regulations, and risk and compliance work are time-consuming and costly. Generative AI greatly reduces the time spent on these tasks, but because the data is sensitive and the industry is regulated, the key is using AI the right way, with verification mechanisms and strong data governance. This course is designed to help banking and financial institution teams use AI
in real work confidently, safely and in a compliant way, covering documents and reports, financial data analysis, customer service and products, risk and compliance work, setting up internal assistants and a knowledge base, and automation with n8n, with data governance, security and PDPA for customer data as the core of every topic. All content is taught through workshops on real financial institution tasks using simulated data, finishing with a capstone project where learners set up an end-to-end AI toolkit for their own work. (2 days, 6 hours per day, 12 hours in total, Beginner to Intermediate level, no AI or programming background required.)
Course Details
A 2-day course, 6 hours per day (12 hours in total), delivered as a hands-on workshop on simulated data with a capstone project. Beginner to Intermediate level, no AI background required. The course focuses on using AI as an assistive tool within a data governance framework, with decisions in regulated work remaining with the organization's people and processes. Learners take home a prompt library, an internal assistant (Custom GPT/Gem), document and product FAQ templates, and a data governance framework with a PDPA checklist.
Section 1: AI in Banking and Financial Institutions
Section 2: Prompts and Output Control for Finance Work
Section 3: Documents, Reports and Customer Communication
Section 4: Financial Data Analysis and Reporting
Section 5: Customer Service and Financial Product Work
Section 6: Risk, Regulation and Compliance with AI
Section 7: Risk Analysis and KYC/AML Support
Section 8: Internal Assistants and Knowledge Base
Section 9: Financial Institution Automation with n8n
Section 10: Data Governance, Security and PDPA
Section 11: Capstone Project and Real-world Adoption
No public rounds are open right now. Join the waiting list and we will contact you first when the next round opens, or ask us on LINE. Or call 02-570-8449 or 088-807-9770
AI works best as an assistant: summarising customer documents, checking them against a checklist, summarising relevant news or public sources and drafting notes for reviewing suspicious transactions, which saves a great deal of paperwork time. Decisions on onboarding customers, assigning risk ratings and reporting transactions must stay with staff and the organisation's own processes, and only tools approved for data security should be used.
Have the AI answer from documents your organisation has approved, such as regulatory notices, internal rules or product manuals, rather than the model's general knowledge. Ask it to cite the section or page it used and to say when it does not know. Calculate figures through formulas or systems that can be audited, and require human review of anything going to customers or regulators so every step is traceable.
Attach the actual regulation or notice and ask the AI to summarise it into the requirements you must meet, citing the clause each comes from. Then attach your internal policy or manual and have the AI compare them point by point, showing which requirements are covered and which are missing or inconsistent, laid out as a gap analysis table. The compliance team should then review the results and interpret anything that needs judgement.
It suits staff and managers at banks, securities firms, insurers and other financial institutions, operations, product and relationship manager teams, risk, compliance and internal audit teams, and data teams who need to use AI safely. You need general computer skills, basic Excel or Google Sheets use and an understanding of your unit's processes. No AI or programming knowledge is required.
You will be able to write prompts that give citable, traceable output, use AI to draft documents, reports and customer communications, analyse transaction and portfolio data with number checks, summarise regulations and review policies, use AI as an assistant for KYC and AML work, set up internal assistants with Custom GPTs or Gems, and apply data governance in line with PDPA. Participants who complete the training receive a Certificate of Completion with its own number, which can be verified online.
Yes. It can be run in-house for your team, with examples adapted to your own work, such as your unit's document types and processes practised on simulated data, and practices aligned with your organisation's data policies. You can request a quotation from this page, or contact us on LINE @itgenius or by phone on 02-570-8449.
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