The M&A Blind Spot: Why Software Due Diligence Matters More Than Ever
- Avalia
- 2 days ago
- 3 min read
Given the complexity of M&A transactions, dealmakers have traditionally obsessed over financials. EBITDA, revenue multiples, and customer churn were the kings of the data room. But in 2024 and 2025, a new reality has set in: buying a company without deeply auditing its code and technical infrastructure is like buying a house without checking the foundation.
Recent data reveals a stark truth: while financial books might look clean, the technical "books" often hide liabilities worth millions—or even billions.
Why Tech Matters Now
Historically, "technical due diligence" was a checkbox exercise—a quick look to ensure the servers were running. Today, it is a primary driver of deal failure.
According to 2024 industry reports, 50-70% of post-merger integrations fail due to technical misalignment, and technical debt (the implied cost of fixing poor code) consumes nearly 33% of developer time in acquired companies.
"Buying a company without deeply auditing its code is like buying a house without checking the foundation."
Here are the three massive "blind spots" that are currently killing deals or destroying value post-close.
Blind Spot 1
The hottest trend in M&A is acquiring AI capabilities. But this gold rush has created a dangerous new risk: "Dirty Data."
In 2024 and 2025, we’ve seen that an AI model is only as legal as the data it was trained on.
The Risk: If a target company trained its AI on copyrighted books, artwork, or private user data without permission, that "asset" is actually a massive legal liability.
Real-World Lesson: The Bartz v. Anthropic case highlighted a potential $1.5 billion exposure for using pirated materials in training. For an acquirer, this means the shiny AI tool you just bought might have to be deleted entirely, rendering the acquisition worthless overnight.
The Fix: Modern due diligence must include a "Data Lineage Audit." Ask: Where did every single piece of training data come from, and do we have the license to use it?
Blind Spot 2
Financial statements show how much money a company made last year, but they don't show how hard it was to make it.
The Risk: "Technical Debt." This occurs when a startup builds software quickly to grow, ignoring best practices. The code works, but it's fragile. When a big company acquires them and tries to scale, the system collapses.
Real-World Lesson: TD Bank’s $3 billion fine in 2024 serves as a grim warning. While not a direct M&A failure, it was a failure of "static" and "outdated" monitoring systems that couldn't keep up with compliance. In an M&A context, buying a fintech company with similar "spaghetti code" means you aren't just buying their revenue—you are inheriting their regulatory fines.
The Fix: Don’t just look at the product demo. Run automated code quality scans to quantify how much it will cost to fix the codebase. If it costs $10 million to rewrite the software, that should come directly off the purchase price.
Blind Spot 3
Modern software is built using "open source" blocks of code (free, public code). But some of these come with "viral" licenses (like GPL) that legally force you to make your own proprietary software free to the public if you use them.
The Risk: A target company uses a tiny piece of restricted open-source code in their core product. If you acquire them, your entire proprietary software suite could legally become "infected," forcing you to release your trade secrets.
The Fix: Use "Software Composition Analysis" (SCA) tools during due diligence. These tools create a "Bill of Materials" for the software, listing every ingredient and its legal license.
Valuable Lessons for Dealmakers (2025 Edition)
If you are looking to buy or sell a technology-driven company today, we suggest three "Golden Rules":
Quantify the Code: Treat technical debt like financial debt. If a target has $5M in "code debt" (fixes needed to scale), deduct it from the valuation just as you would a bank loan.
Audit the "AI Supply Chain": Never assume an AI model is safe. Demand proof of ownership for the data inside the model, not just the code that runs it.
Cybersecurity is Valuation: A 2025 IBM report noted the average cost of a data breach is nearly $4.88 million. A target with weak security is a ticking time bomb.
The Bottom Line: In 2025, software due diligence is no longer just for the CTO. It is a financial imperative. The deals that succeed will be the ones that look past the balance sheet and into the codebase.
Sources & Further Reading:
