Python · Streamlit · AI Project 02

US + SE Asia
M&A Screener

A cross-border M&A screening tool covering 38 companies across five markets — the US, Indonesia, Singapore, Malaysia, and Thailand — with live FX normalization and an AI-generated deal memo for any company that clears the filters.

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Type
Python App · M&A Tool
Markets covered
US, Indonesia, Singapore, Malaysia, Thailand
Date
July 2026
38
Companies screened across 5 markets
5
Screening factors (EV/EBITDA, growth, margin, leverage, market cap)
Live FX
USD normalization across all SE Asian currencies
AI
Claude API deal memo for every qualifying company

Why I Built This

Most screening tools stop at the US or treat Southeast Asia as an afterthought. I wanted something that covers both on equal footing — screening for companies with a financial profile common among acquisition candidates across five markets, with currency-adjusted comparisons so a $2B Indonesian company and a $2B US company are actually being compared in the same terms.

The tool started as a Google Colab prototype and was rebuilt into a modular three-file Streamlit app with FX normalization, CSV export, a Claude API integration for deal memo generation, and a public GitHub repo.

What It Does

The Tool in Action

M&A Screener screenshot 1 M&A Screener screenshot 2

The AKRA Deep-Dive

To validate the tool wasn't just a black box, I took one output — PT AKR Corporindo (AKRA.JK), an Indonesian energy distribution and logistics company — and built a full manual investment memo on top of it, sourced from the company's actual FY2025 annual report rather than relying on the AI-generated draft alone.

AKRA surfaced with 19% YoY revenue growth, a 7.4x EV/EBITDA multiple, and a net cash position. The process also exposed a real data-quality issue I caught and corrected: the data provider reported ~34x debt/equity against the actual ~1.3x from the annual report. The memo also flagged a practical deal constraint — AKR's ownership is concentrated with a controlling family stake, meaning any real transaction would require negotiated buy-in rather than an open-market approach.

Built With

Python Pandas Streamlit yFinance Claude API (Anthropic) Live FX Normalization CSV Export

What It Doesn't Do


Project Links

Access the live app and source code.

GitHub Repository
Source code · Python / Streamlit
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PDF
AKRA_Investment_Memo.pdf
PT AKR Corporindo — manual deep-dive memo
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