Building Financial Models with Claude AI

building-financial-modeling- with-claude-ai

Sumber: https://claude.com/claude-for-excel

Rate this post

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.

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.

Schedule 2026

22-23 January 2026
12-13 February 2026
12-13 March 2026
16-17 April 2026
18-19 May 2026
18-19 June 2026
16-17 July 2026
13-14 August 2026
14-15 September 2026
15-16 October 2026
12-13 November 2026
10-11 December 2026

Full Day Training: 09.00 – 17.00 wib

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 6,950,000/ Peserta

Jakarta: IDR 5,490,000/ 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.

Course Overview

Day 1 Agenda — Morning Session

Foundations, Capabilities & First Models
09:00 – 09:30
Prompt Engineering for Financial Modeling

SMART prompt guidelines for structured output
Prompt anatomy: context, role, constraints, format
Chain-of-thought for multi-step calculations
Course setup: Claude AI & Excel verification

09:30 – 10:30
Financial Models in Decision-Making

How models drive valuations, M&A, & credit decisions
Key types: DCF, LBO, 3-statement, budget models
Common modeling pitfalls & quality benchmarks
Case study: When models fail

Why Claude AI for Finance
10:30 – 10:45 Break (15 min)
10:45 – 12:00
Why Claude AI for Financial Modeling

AI landscape: Claude vs. Copilot vs. Shortcut
Claude’s strengths: reasoning, accuracy, context
Capabilities & limitations
Compliance, governance & review frameworks
Live demo: Claude building a financial calculation

Day 1 Agenda — Afternoon Session

Recap & Revenue Forecasting
13:00 – 14:00
Day 1 Recap & Afternoon Overview

Morning key takeaways review
Revenue drivers & assumption setting
Excel best practices for AI-assisted modeling

14:00 – 15:15
Workshop: Revenue Forecasting Models

Building a top-down revenue forecast with Claude AI
Prompt iteration: refining assumptions & growth drivers
Exporting structured output to Excel spreadsheets

DCF, Working Capital & Wrap-Up
15:15 – 15:30 Break (15 min)
15:30 – 16:45
Workshop: Basic DCF & Working Capital

Constructing a basic DCF template step by step
Working capital: receivables, payables, inventory
Validating AI formulas against manual calculations

16:45 – 17:00
Day 1 Wrap-Up & Q&A

Key takeaways recap & preview of Day 2
Homework: practice prompts for overnight preparation

Day 2 Agenda — Morning Session

Model Review & 3-Statement Models
09:00 – 09:15
Model Review & Revision

Systematic audit framework for AI-generated models
Formula integrity checks & compliance review
Day 1 key takeaways & Day 2 preview

09:15 – 10:30
Workshop: 3-Statement Integrated Models

Building a fully linked income statement with Claude AI
Balance sheet: assets, liabilities, equity
Cash flow: indirect method, working capital changes
Linking statements with circular reference handling
Testing model integrity: plug checks & balancing

Debt Schedules & Covenants
10:30 – 10:45 Break (15 min)
10:45 – 12:00
Workshop: Debt Schedules & Covenant Modeling

Debt structure: term loans, revolvers, mezzanine
Amortization schedules & repayment waterfalls
Interest rate calculations: fixed, floating, PIK
Covenant compliance: leverage, coverage, DSCR
Stress testing covenants under adverse scenarios

Day 2 Agenda — Afternoon Session

DCF Valuation & Sensitivity Analysis
13:00 – 13:45
Morning Recap & Afternoon Overview

Key learnings from morning workshops
Preview of advanced models & capstone project

13:45 – 14:45
Workshop: Full DCF Valuation Model

WACC calculation, unlevered FCF projections
Terminal value: Gordon growth vs. exit multiple

14:45 – 15:30
Sensitivity & Scenario Analysis

One-way & two-way data tables for key assumptions
Three-or-more-way data tables for key assumptions

Capstone & Course Wrap-up
15:30 – 15:45 Break (15 min)
15:45 – 16:45
Capstone: Complete End-to-End Model Build

Build a full financial model from assumptions to output
Peer review: exchange models for audit practice

16:45 – 17:00
Course Wrap-Up & Q&A Session

Wrap-up
Q&A Session

Course Objectives

Upon successful completion of this training, participants will be able to:

Understand Financial Models
Grasp the role of financial models in valuations, M&A, credit analysis, budgeting, and risk assessment
Apply Prompt Engineering
Master prompt techniques specifically designed for financial modeling, from simple queries to complex multi-step prompts
Build Core Financial Models
Create revenue forecasts, DCF templates, working capital models, and 3-statement integrated models with Claude AI
Construct Advanced Analyses
Build debt schedules, covenant models, DCF valuations, and sensitivity & scenario analyses
Review & Audit AI Models
Ensure compliance with best practices, verify formula integrity, and meet professional standards
Deliver End-to-End Models
Complete a capstone project demonstrating full AI-augmented financial modeling proficiency

Prerequisites & Who Should Attend

Prerequisites
✓ Excel Proficiency: Intermediate-level Microsoft Excel Skills (formulas, functions, data tables)
✓ Financial Literacy: Basic understanding of financial statement (income statement, balance sheet, cash flow)
✓ Accounting Fundamentals: Working knowledge of core accounting principles and concepts
✓ Claude AI Account: Active Claude AI Subscription (Pro or Team plan recommended)
✓ Laptop Required: Bring your own laptop with Microsoft Excel and internet access
✓ Growth Mindset: Willingness to learn AI tools and adapt workflows

Who Should Attend
→ Financial Analysts: Analysts building models for investment decisions, valuations, and reporting
→ FP&A Professionals: Planning and analysis teams seeking to accelerate budgeting and forecasting
→ Investment Bankers: IB professionals building deal models, pitch books, and transaction analysis
→ Corporate Finance Teams: Treasury, M&A, and strategic finance professionals
→ Consultants: management and financial consultants creating client-facing models
→ Finance Managers: Leader overseeing model development wanting to leverage AI tools