A product vision for turning fragmented bank data into beautiful, shareable financial reports — without the compliance burden of handling client data.
Your clients live across borders. Their finances are scattered across countries, currencies, and institutions. No tool gives them a consolidated picture without demanding daily effort — or their bank credentials.
2–4 bank accounts across countries. Income in one currency, rent in another, savings in a third. No single dashboard shows the whole picture.
Cloud aggregators require bank credentials (compliance risk). Budgeting apps demand daily input (low adoption). Spreadsheets work once, then go stale.
"The ability to take someone's real financial data and generate personalized output without a heavy compliance burden is exactly what we've been looking for."
Three capabilities that didn't exist two years ago converge to make this product viable.
LLMs can now read a PDF bank statement — any format, any country, scanned or digital — and extract every transaction into structured data. This used to require building a custom parser per bank. Now one model handles them all.
The same model that reads documents can hold a nuanced conversation: "KVBW Wohnen is a German housing association" or "round-number ATM withdrawals usually mean cash payments to household staff." It knows the world well enough to categorize your client's financial life through dialogue.
Tools like Claude Code run directly on a user's computer, reading local files and executing tasks without uploading data to a cloud service. The AI orchestrates locally — your client's data doesn't need to live in someone else's database.
Many of your clients are already using ChatGPT, Claude, or Gemini for work and personal tasks. The interaction model — asking questions in natural language, uploading documents, iterating on results — is familiar. This product meets them where they already are, applied to a problem they can't solve with a general-purpose chatbot alone.
The window is now. AI-powered financial tools are emerging fast. The cross-border space is underserved by both traditional fintech and generic AI products. There's an opportunity to define what "AI-powered financial clarity" means for expats — with your credibility and domain expertise behind it.
We built a working prototype for a real household — 3 accounts, 2 currencies, 3,800+ transactions, 12 months of data. Here's what we learned.
The core insight: The user described their life. The AI mapped the money. 7 rounds of conversation replaced weeks of manual categorization.
The demo you saw was an anonymized version of this real analysis — same structure, same interactivity, synthetic data.
Four steps from bank exports to a shareable, branded report.
First report: under 1 hour for single-currency, under 3 hours for multi-currency. Monthly refresh: under 5 minutes — the agent remembers prior rules.
Two phases with different privacy profiles. We're transparent about both.
Every AI interaction is logged locally — both extraction calls (full documents) and conversation calls (anonymized). Reviewable by client, advisor, or compliance counsel at any time.
Anthropic API: No training on data. 30-day retention for safety (or Zero Data Retention for enterprise — content processed but never stored). Exposure decreases over time as local parsers improve for known bank formats.
Educational tier. Spend analysis as a coaching tool. Findings framed as observations. Lower price point. Broader audience.
Full advisory tier. Deeper analysis, forward projections, advisor review mode. Findings framed for planning conversations. Premium positioning.
A desktop app with a single, always-present input bar. The client talks to the AI the same way they'd talk to you — in plain language.
Bank CSVs, Amazon PDFs, Apple receipts — drag and drop onto any screen. The app routes them automatically.
"Geraldine is our babysitter, €20/hr in cash." The AI derives categorization rules from lifestyle context, not transaction-level tagging.
While viewing the report, circle something that looks wrong, type what's off. The AI gets the screenshot, annotation, and data context together.
Charts, drilldowns, findings, methodology. Self-contained HTML — works on phone, desktop, offline. Your brand, your colors.
Client sets a passcode, gets a URL. No login required for you to view it. Open the link, enter the code, review the report.
New quarter? Drop in fresh exports. The agent remembers all prior rules — only asks about genuinely new merchants.
Three phases from pilot to scale. We start with your first clients.
There are several ways to bring this to market. The right model depends on how you want to position it relative to your practice and your clients. Let's explore the options.
The report becomes part of your advisory service. Clients get it as part of working with you — it's a differentiator, not a separate product.
Two tiers matching your two brands. Passport To Wealth gets an education-framed version (spend analysis as coaching). Connected FP gets the full advisory version with planning tools.
A new product brand — an AI-powered financial clarity tool for cross-border individuals. You're a co-founder, not just a customer. Sold directly to consumers or through advisor networks.
These aren't mutually exclusive. You could start with Option A (bundled, pilot with your clients), learn what works, and evolve into B or C as the product matures. The architecture supports all three — branding, compliance framing, and report depth are all configurable.
The bigger question: Is this a tool that makes your practice better — or is this a new kind of product in the cross-border space? LLM-powered financial tools are emerging fast. There may be a window to define what "AI financial clarity" looks like for expats, with your credibility behind it.
Let's start with your clients and build from there.
Select 3 clients with multi-currency, multi-account situations. We run the full journey together — data to report — and learn what works.
Your compliance counsel reviews the report format, findings language, and the Agent Bridge audit log. We establish the "data tool vs. financial advice" boundary together.
Pilot learnings become the product. Desktop app, self-service onboarding, your branding, your clients. Phase 2 by the end of the year.