I decided to test Google’s AI in a practical area that matters to everyone—tracking money—and found the results underwhelming. With access to purchase alerts in Gmail and transactional SMS in Google Messages, Gemini should be well-positioned to compile spending data, identify trends, and ease the burden of budgeting. Instead, it missed some transactions, double-counted others, and confused credits for debits. In a domain where accuracy is crucial, the bot felt more like a novelty than a dependable tool.
A Promising Idea, But Poor Execution
The test was straightforward. I asked Gemini in Gmail for my expenses this month. It successfully located emails from my bank, identified a series of transactions, and even recommended a total without prompting. Things looked promising—until I examined the details. Gemini failed to detect some card charges I clearly made, recorded a refund as a new expense, and worse, reported “no activity” for a month when transactions clearly occurred. It also mixed incoming transfers with expenses, inflating totals with funds that never left the account. When precision is essential, such discrepancies destroy trust.
The Core Issue: Reliability, Not Presentation
The problem isn’t how the information is displayed. If AI can’t consistently identify transactions in emails and SMS messages, it can’t provide meaningful budgeting insights or reliable month-to-month comparisons. Accuracy is non-negotiable in finance—almost right means wrong.
Why Managing Money Challenges AI
Bank notifications are notoriously complex: merchant names get truncated, currencies sneak in, holds expire, tips post later, and refunds or installments appear days after the original transaction. This demands more than natural language understanding; it requires a robust parsing engine to prevent conflicts between email and SMS data and logic to always distinguish debits from credits. Furthermore, proper categorization depends on merchant codes, location, and context (for example, whether an Uber ride is personal or work-related). Without a merchant knowledge base and lasting rules, AI tends to mislabel or lump transactions into vague categories like “Other.” According to the NIST AI Risk Management Framework, nondeterministic and inconsistent outputs are unacceptable for high-stakes uses. Finance may not be medical-grade accuracy, but its margin for error is similarly slim.
Privacy Is Essential, Not an Afterthought
Many third-party apps auto-track spending by reading SMS or linking bank accounts through aggregators. While some are effective, they often trade privacy for convenience—cloud processing, cross-app profiling, and frequent upselling of financial products based on data. After a popular budgeting app shut down last year, many users switched to trusted options like YNAB, Monarch Money, or simply spreadsheets, prioritizing trust over ease. Big tech must do better—with transparent data policies and on-device processing—to earn that trust. For Gemini to be a credible financial assistant, it needs transparency in data handling, strict minimization, and controls matching fintech security standards like SOC 2 and PCI DSS.
What a True Google Expense Tool Should Offer
- A genuine Google expense tracker would be a native tool, ideally integrated into Gmail and Messages, featuring:
- Deterministic parsers for bank emails and SMS templates, regularly updated
- A smart reconciliation engine that de-duplicates across channels, links refunds to original charges, and ignores
informational holds - Merchant intelligence leveraging global merchant category codes for accurate categorization and insights
- On-device data extraction with opt-in, consent-based cloud aggregation for trends, plus clear audit logs
- Core budgeting fundamentals such as envelopes, recurring bills, and savings goals, presented with explanations
linking every figure to underlying messages
Once the foundation is solid, AI can add significant value by predicting next-month spending, alerting users before subscription renewals, flagging unusual charges, or showing how small habits—like cutting back on food delivery—impact savings.
Current Verdict: Gemini Falls Short on Expense Tracking
Though Gemini’s demonstration appears polished, it fails at basic accuracy. For now, dedicated apps or even well-maintained spreadsheets outperform chatty AI assistants. If Google builds a privacy-conscious money tool with deterministic parsing and solid reconciliation, it could change the game. Until then, trusting Gemini to balance your books is a leap too far.
