Variance Explainer
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MIT · 2026
AI Financial Variance Analysis from SEC Filings

Ask why revenue, margin,
labor cost changed.

Get grounded answers with page-level citations from SEC 10-K and 10-Q filings in seconds. Stop searching PDFs. Start explaining variance.

Try a sample analysisView on GitHub ↗
Grounded in SEC filings
Every answer cited
Runs fully offline
7 companies
4 industries
02The problem

Why Financial Metrics Changed

Financial variance analysis often requires analysts to manually search SEC 10-K and 10-Q filings, read Management Discussion & Analysis (MD&A), and connect changes in financial metrics to the underlying business drivers. Slow, error-prone - and it doesn't scale across 7 companies and 4 industries.

4 hrs → 3 min
  • The manual crawlOpen the filing, search the filer, find the number, read the MD&A context.
  • The trust gapNo guarantee the paragraph you landed on is the one that moved the metric.
  • The scale wallDo this across a basket of companies and the process breaks down completely.
03Live demo
variance-explainer - demo
$ ask --question
“█”
CMG 10-Q, p. 12 · confidence 94%

█

07How it works

How AI Analyzes SEC Filings

variance-explainer - pipeline
> █
Understand the question
...
sections searched
Search the filings
...
possible matches
Rank by relevance
...
best match found
Write the answer
...
sourced answer
Sourced answer ready

Wage inflation and CA minimum wage increases, offset by sales leverage. Cited: CMG 10-K p.34, 10-Q p.12.

08Evidence

Accuracy on Real SEC Filings

Tested against 40 real questions with known correct answers, before and after adding a relevance-ranking step. The hardest cases went from being missed entirely to found first.

3 min
per variance question
down from ~4 hours
52%
right source found first try
top-5, up from 33%
74%
answers fully verified
restaurant filings
7
companies covered
4 industries
100%75%50%25%0%
18%
23%
Top 1
24%
45%
Top 3
33%
52%
Top 5
55%
70%
Top 10
Right source found on the first try
Before vs. after adding a relevance-ranking step
Before ranking step
After ranking step
0.52 → 0.66
search score (higher = right answer found sooner)
Chipotle overhead-cost question
was result #17→now #1
Cracker Barrel labor-cost question
was result #17→now #1
Questions it used to miss entirely
4 of 20→0 of 20
09Financial Variance Analysis Examples

Real questions, real answers.

Why did Chipotle's labor costs change?
Wage inflation, CA minimum wage, sales leverage
CMG 10-K/10-Q
What drove Walmart's e-commerce growth?
Omnichannel penetration, store-fulfilled pickup
WMT 10-K/10-Q
How did Target's gross margin rate change?
Merchandise mix, promotions, shrink impact
TGT 10-K/10-Q
How did Darden's Chuy's acquisition impact revenue?
Purchase price, sales contribution, segment profit
DRI 10-K/10-Q
How do WMT and TGT compare on inventory turnover?
Cross-retail inventory trends, shrink reduction
WMT + TGT
10Why Financial Analysts Use It
  • 01

    Explains financial variance

    Digs past the headline number to the drivers - price, volume, mix, wage inflation, FX - so you can explain why any metric moved.

  • 02

    Searches SEC filings

    Reads straight from 10-K and 10-Q filings across 7 companies - no more manual searching through PDFs.

  • 03

    Finds supporting evidence

    Retrieves the exact MD&A passage that backs each claim, ranked for relevance before anything is written.

  • 04

    Cites every answer

    Each claim points to the filing and page, so you can verify it before it goes in a report or a deck.

  • 05

    Works across industries

    Indexed on restaurant, retail, healthcare, and energy filings with no drop in retrieval accuracy between them.

05FAQ

Frequently Asked Questions

What is financial variance analysis?+
Financial variance analysis is the practice of comparing a reported financial metric - revenue, gross margin, labor cost, operating expense - against a prior period, a budget, or a forecast, then explaining what drove the difference. Instead of just noting that revenue rose, variance analysis identifies the business drivers behind the change, such as price, volume, mix, wage inflation, or foreign exchange.
How do analysts use SEC filings?+
Analysts use SEC filings such as the 10-K and 10-Q to find the disclosures, trends, and risks behind a company’s financial results. The Management Discussion and Analysis (MD&A) section is the primary place where management explains why a metric changed, which is why most financial research starts there.
What is MD&A?+
Management Discussion and Analysis (MD&A) is the section of a company’s 10-K, 10-Q, or annual report where management explains why financial performance changed between reporting periods. It connects the numbers on the income statement and balance sheet to the underlying business drivers - pricing, volumes, costs, acquisitions, and market conditions.
Can AI analyze 10-K filings?+
Yes. This tool indexes the full text of real 10-K filings - including the MD&A section - and retrieves the exact passages that explain a given metric. Answers are generated from those passages and cited to the specific filing and page, so you can verify every claim against the source.
Does this work on 10-Q reports?+
Yes. Quarterly 10-Q filings are indexed alongside annual 10-K filings, so you can ask about the latest quarter and compare it with the same period last year. Both filing types are covered by the same retrieval and citation pipeline.
Which companies are supported?+
The index currently covers 7 companies across 4 industries: Chipotle (CMG), Darden (DRI), Cracker Barrel (CBRL), Walmart (WMT), Target (TGT), Johnson & Johnson (JNJ), and ExxonMobil (XOM).
Does it run locally?+
Yes. The default setup runs fully on your own machine with a local language model and no API keys. Nothing leaves your computer, and there is no per-query cost.
11Quick start

Running in two minutes.

Want to run it yourself or see exactly how it works under the hood? Here's the full setup.

# Clone & setup
git clone https://github.com/redsandr/rag-variance-explainer
cd rag-variance-explainer
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env

# Build index & run
python src/build_index.py
streamlit run app.py
12Roadmap

What's next.

  • 01International filings, not just US-based companies
  • 02Follow-up questions in the same conversation, not just one-off queries
  • 03One-click setup, no command line required
  • 04A version tuned specifically on financial language for even higher accuracy
  • 05A public demo anyone can try without installing anything

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