Building Financial Modeling using Claude AI

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Master the art of AI-powered financial analysis in one intensive day.

from fundamentals to advanced financial applications.

Course Description

This intensive 1-day course equips finance professionals with practical prompt engineering skills for AI-assisted financial modeling using Claude AI. Through hands-on workshops and real-world case studies, participants will learn to craft effective prompts for DCF analysis, LBO modeling, 3-statement models, comparable company analysis, and more — transforming how they approach financial analysis workflows.

4 Sessions: Structured progression from prompt engineering fundamentals through advanced multi-model financial workflows

3 Workshops: Hands-on exercises building real financial models with guided prompt engineering practice

1 Day: Comprehensive 9 AM – 5 PM intensive covering zero-shot basics to advanced multi-model strategies

What is Claude?

Claude is a next-generation AI assistant and family of large language models (LLMs) developed by Anthropic, designed to be safe, accurate, and highly performant in reasoning, coding, and analysis. Known for its “helpful, honest, and harmless” approach, Claude is a popular alternative to ChatGPT, often used for complex tasks, creative writing, and processing long documents.

Baca juga: Building Financial Models with Claude AI

Trainer Profile

Purwadi Nitimidjojo

the trainer, started his financial modelling career in early 2005 after working for Indonesian Bank Restructuring Agency (IBRA / BPPN) during the monetary crisis from 1998 through 2004. At IBRA’s Credit Risk Management Division he developed various financial models for debt restructuring and corporate restructuring and learned that most of IBRA’s large debtors hired foreign financial consultants to develop financial models as they didn’t have any resources who could develop proper financial models, and financial modelling training courses were not available back then. This is when he saw an opportunity to deliver financial modelling training courses and develop best-practice financial models for clients in various industries in Jakarta.

In early 2005 Purwadi teamed up with two of his friends and used “Edward, Farral & Peterson” and “Edward & Peterson” as their brands to provide monthly public training courses and financial modelling services until early 2012 before he was hired by Deloitte Financial Advisory as a Financial Modelling Director to do the same. At Deloitte he and his financial modelling team developed best-practice financial models for his clients in various industries for various purposes and delivered monthly financial modelling and Power BI training courses for the public, clients, and Deloitte’s internal staff in Indonesia, Singapore, Malaysia, Thailand, and Cambodia.

After spending 10 years working for Deloitte, he returned to his own financial modelling business and is now working as a financial modelling subcontractor for BDO and Deloitte as well as an independent private financial modelling consultant and trainer.

Baca Juga: Data Analysis & Visualization with Power BI

Schedule 2026

  • 28 January 2026
  • 18 February 2026
  • 9 March 2026
  • 22 April 2026
  • 20 May 2026
  • 17 June 2026
  • 15 July 2026
  • 19 August 2026
  • 16 September 2026
  • 14 October 2026
  • 18 November 2026
  • 16 December 2026

Full Day Training: 09.00 – 17.00 wib

Baca Juga: Prompt Engineering for Financial Modeling using Claude AI

Venue Training

Yogyakarta:

  • NEO Hotel Malioboro Yogyakarta
  • Royal Malioboro by ASTON Yogyakarta
  • Novotel Suites Yogyakarta Malioboro

Jakarta:

  • Swiss-Belinn Simatupang, Jakarta Selatan
  • Swiss-Belhotel Pondok Indah, Jakarta Selatan
  • Ibis Styles Simatupang, Cilandak, Jakarta Selatan

(Kepastian venue akan dikonfirmasikan H-4 sebelum event)

Investment Fee

Yogyakarta: IDR 4,950,000/ Peserta

Jakarta: IDR 3,490,000/ Peserta

  • Harga sudah termasuk Training Material, Sertifikat, Lunch & Coffee Break, Souvenir, Door Prize.
  • Discount 10% bagi peserta yang mendaftar lebih dari 1 participants dan pembayaran dilakukan sebelum event berlangsung.
  • In-House Training: minimal 4 Peserta.

Baca Juga: Financial Statement Spreading and Analysis with Claude AI

Course Takeaways – What You’ll Walk Away With

Five career-ready competencies that you can deploy immediately on any financial modelling engagement – from analyst-level model builds to CFO-level scenario presentations.

  1. Efficient Prompting Mastery
    • Confidence writing high-precision prompts for financial modelling – the new essential skill for the AI era of finance.
  2. MIRROR Method
    • A repeatable system to deconstruct any prompt, extract optimal instructions, and rebuild it using the MIRROR framework.
  3. 3-Tier 10-Technique Toolkit
    • 5 principles, 6 best practices, and 10 battle-tested prompt techniques with exercises – ready to deploy on any finance task.
  4. Complete Business Planning Model
    • A fully functional BPM covering all module sheets, financial statements, DuPont ratios, DSCR, capital structure, sensitivity, and scenario analysis.
  5. Scenario & Validation Skills
    • Ability to stress-test any model with AI-driven scenario analysis, sensitivity tables, assumption audits, and model error checks.

What You Will Learn

Six core competencies – spanning prompting fundamentals, reverse engineering, advanced frameworks, and full model construction – built progressively across one day of intensive hands-on training.

  1. Master Efficient Prompting
    • Recognize prompt engineering as the essential new skill for finance professionals in the AI era – and immediately apply it to modelling tasks.
  2. Apply Reverse Prompt Engineering
    • Deconstruct and reconstruct prompts using the MIRROR Method to extract optimal model-building instructions from any financial output.
  3. Leverage the 3-Tier Framework
    • Apply 5 principles, 6 best practices, and 10 techniques – with exercises – for precise financial model prompts on any task.
  4. Build the Core Business Planning Model
    • Build a complete Business Planning Model – from projection assumptions through supporting modules to income statement, balance sheet, and cash flow statements.
  5. Produce Financial Ratios and Sensitivity & Scenario Analysis
    • Generate financial ratios for profitability, efficiency, liquidity, leverage, DSCR, capital structure, as well as sensitivity and scenario analysis, and model error checks.
  6. Validate & Stress-Test Models
    • Run AI-driven scenario analysis, sensitivity testing, and assumption audits to deliver defensible, boardroom-ready models.

Course Prerequisites

Required

  • Intermediate to advanced Excel proficiency (formulas, financial functions, data manipulation)
  • Foundational knowledge of corporate finance and accounting concepts (P&L, Balance Sheet, Cash Flow)
  • Familiarity with financial modeling concepts (DCF, valuation multiples, 3-statement linkages)
  • Access to a computer with internet connection and a Claude AI account (free or paid; Pro recommended for heavy use)

Recommended

  • Prior experience building at least one financial model from scratch
  • Basic understanding of AI / large language models (no coding required)
  • Exposure to investment banking, equity research, or FP&A workflows

Baca Juga: Financial Modelling Fundamental using Excel

Course Outline

Efficient Prompting: The New Core Skill for Finance Professionals

Session 1 – Why Prompt Engineering Is the New Finance Skill

  1. The AI shift in finance: how LLMs are redefining analyst, FP&A, and IB workflows
  2. Why mastery of prompt engineering is now as essential as Excel and financial modelling
  3. The cost of vague prompts: garbage-in, garbage-out in financial models

Session 2 – Efficient Prompts for Financial Modelling: Live Practice

  1. Anatomy of an efficient financial model prompt: precision, scope, and output format
  2. Side-by-side comparison: weak vs. efficient prompts across modelling tasks
  3. Hands-on exercise: rewrite 5 weak finance prompts into high- precision, model-ready prompts

Reverse Prompt Engineering & the MIRROR Method

Session 3 – Reverse Prompt Engineering: Concepts & Anatomy

  1. What reverse prompt engineering is and why it matters in financial modeling
  2. Deconstructing model outputs to reverse-engineer the optimal prompt
  3. Prompt anatomy: goal, role, context, constraints, format & output specification

Session 4 – The MIRROR Method & Hands-On Exercises

  1. MIRROR Method walkthrough: Map, Instruct, Refine, Review, Output, Repeat
  2. Applying MIRROR to a live financial modelling scenario step by step
  3. Exercise: reverse-engineer a BPM prompt, then rebuild it using the MIRROR framework

The 3-Tier Prompt Framework

Session 5 – Foundations: 5 Principles, 6 Best Practices & Techniques 1-5

  1. 5 core principles of effective prompting for financial modelling
  2. 6 best practices: clarity, context, constraints, format, iteration & validation
  3. Techniques 1–5 with exercises: role assignment, structured output, chain-of-thought, few-shot examples, constraint framing

Session 6 – Advanced Techniques 6-10 & Applied Exercises

  1. Techniques 6–10: iterative refinement, persona layering, negative prompting, multi-step decomposition, self-critique loops
  2. Paired exercise for each technique applied to a finance/modelling scenario
  3. Capstone drill: combine all 10 techniques in a single business planning model prompt sequence

Building the Business Planning Model

Session 7 – Model Architecture: Inputs & Supporting Module Sheets

  1. Table of contents with hyperlinks; Inputs: projection assumptions sheet
  2. Module sheets: Revenue, Costs & Expenses, Working Capital, Capex & Depreciation
  3. Borrowings module and Income Tax module

Session 8 – Outputs: Financial Statements, Ratios & Analysis

  1. Income statement, balance sheet, cash flow statement (3-way integration)
  2. DuPont ratios (ROE, ROS, ATO, ALEV), profitability, efficiency, liquidity & leverage ratios
  3. EBITDA & debt service cover, capital structure, sensitivity & scenario analysis, model error checks

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