Built a fintech app with GPT Engineer?
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 GPT Engineer apps
Building a fintech app with GPT Engineer 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 GPT Engineer fintech app
Common GPT Engineer issues we fix
Beyond fintech app-specific issues, these are GPT Engineer patterns we commonly fix.
No authentication system
GPT Engineer generates functional UIs but typically skips authentication entirely. All routes and data are publicly accessible.
Direct database access from client
Some generated apps query databases directly from the frontend without an API layer, exposing database credentials and structure.
Incomplete feature implementations
Features that look complete in the UI but don't actually work end-to-end. Buttons that don't submit, forms that don't save, and links that go nowhere.
Missing error boundaries
A single component error crashes the entire application. No error boundaries or fallback UIs to gracefully handle failures.
Start with a self-serve audit
Get a professional review of your GPT Engineer 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 GPT Engineer?
GPT Engineer 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 GPT Engineer leave in fintech apps?
Common issues include: no authentication system, direct database access from client, incomplete feature implementations. For a fintech app specifically, these issues are compounded by the need for data encryption and storage.
How do I make my GPT Engineer fintech app production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most GPT Engineer-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 GPT Engineer-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 GPT Engineer fintech app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.