Built a fintech app with Databutton?
We'll make it production-ready.
Financial apps handle the most sensitive data there is — bank accounts, transactions, and personal financial information. A single security flaw can mean stolen funds, regulatory penalties, or permanent loss of user trust. AI tools can prototype a budgeting dashboard or invoicing system quickly, but the compliance, encryption, and audit requirements for financial software are far beyond what any AI tool generates out of the box.
Fintech App challenges in Databutton apps
Building a fintech app with Databutton is a great start — but these challenges need attention before launch.
Data encryption and storage
Financial data must be encrypted at rest and in transit. Account numbers, transaction histories, and personally identifiable financial information need field-level encryption, not just HTTPS. AI tools store financial data in plain text in the database, which is a compliance violation waiting to happen.
Transaction integrity
Financial transactions must be atomic — money debited from one account must be credited to another, with no in-between state where it disappears. AI-generated code doesn't use database transactions, meaning a server crash mid-operation can leave accounts in an inconsistent state.
Audit trail and compliance
Every financial action needs an immutable log — who initiated it, when, what changed, and what the balances were before and after. Regulators require this. AI tools don't generate audit logging, and retrofitting it into an existing codebase is tedious but essential.
Third-party financial API integration
Connecting to Plaid, Stripe, or banking APIs requires handling OAuth flows, webhook verification, idempotency keys, and retry logic for failed calls. AI tools generate the initial API call but miss the error handling and reliability patterns these services require.
Authentication and fraud prevention
Financial apps need multi-factor authentication, session timeout policies, device fingerprinting, and suspicious activity detection. Basic email/password auth from AI tools is nowhere near sufficient for an app that touches people's money.
Number precision and currency handling
JavaScript floating-point math causes rounding errors with money — $0.1 + $0.2 !== $0.3. AI tools use standard floats for currency calculations, which leads to penny discrepancies that compound over time and break reconciliation.
Regulatory awareness
Depending on what your app does, you may need to comply with PCI DSS, SOC 2, KYC/AML requirements, or state money transmitter regulations. AI tools have no awareness of these requirements, and non-compliance can result in fines or forced shutdowns.
What we check in your Databutton fintech app
Common Databutton issues we fix
Beyond fintech app-specific issues, these are Databutton patterns we commonly fix.
SQL injection in AI-generated query strings
Databutton's generated FastAPI endpoints sometimes build SQL queries using f-strings or string concatenation with user-supplied parameters, bypassing parameterized query protections entirely.
No authentication on data API endpoints
Data pipeline endpoints are frequently generated without authentication middleware, exposing raw database access and sensitive business metrics to anyone who discovers the API URL.
Unhandled data type mismatches crashing pipelines
Generated data processing code assumes clean input schemas. When upstream data contains nulls, type changes, or unexpected formats, pipelines throw unhandled exceptions and fail silently.
Missing pagination on large dataset queries
Data queries load entire tables into memory without limit or offset clauses. With more than a few thousand rows, responses time out and memory usage spikes.
Start with a self-serve audit
Get a professional review of your Databutton fintech app at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a fintech app with Databutton?
Databutton is a great starting point for a fintech app. It handles the initial scaffolding well, but fintech apps have specific requirements — data encryption and storage and transaction integrity — that need professional attention before launch.
What issues does Databutton leave in fintech apps?
Common issues include: sql injection in ai-generated query strings, no authentication on data api endpoints, unhandled data type mismatches crashing pipelines. For a fintech app specifically, these issues are compounded by the need for data encryption and storage.
How do I make my Databutton fintech app production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Databutton-built fintech apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a Databutton-built fintech app?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger fintech app projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your Databutton fintech app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.