Payment & merchant platforms
Merchant consoles, onboarding flows, card acceptance integrations and account dashboards, built and tested for correctness.
Fintech & Payments
Software development for fintech and payments
Money moves fast. The software behind it has to be right.
We have worked on engineering for Netevia, a US payments and banking platform for merchants. We bring that same care for correctness and security to platforms, risk models and automation for financial companies.
Built for teams where a bug has a price tag.
Financial products carry a higher bar than most software: every transaction must reconcile, every decision may be audited, and security is part of the product rather than an add-on. At the same time, customers expect the speed and ease of consumer apps.
We build fintech software with that balance in mind — clean, tested services for money movement, and machine learning where it earns its place: spotting unusual transactions, scoring risk, and reading the documents that onboarding and compliance depend on. Every model comes with the explanations and logs an auditor will ask for.
Fintech & Payments
What we build
Fraud & anomaly detection
Models that flag unusual transactions and behaviour early, with reasons your analysts can review.
Credit & risk scoring
Scoring models on your historical data, with explainability for credit decisions and regular monitoring for drift.
KYC & document processing
Extracting data from IDs, statements and company documents, with confidence checks and human review.
Support assistants
Assistants that answer account and product questions from your help content, and escalate anything sensitive.
Reporting & data platforms
Reliable pipelines and dashboards for finance, risk and compliance teams.
Who we work with
Payment providers
Merchant platforms, onboarding and transaction monitoring.
Banks & lenders
Risk scoring, document automation and customer assistants.
Insurance
Claims document processing and fraud signals.
Fintech startups
From MVP to a platform that passes due diligence.
Why MLMind
Why teams choose us
01Payments experience
Engineering work on a US payments and banking platform for merchants.
02Explainable models
Risk and fraud models that show why they flagged something, so decisions can be reviewed and defended.
03Security first
Least-privilege access, encryption, audit logs and code review as standard, not as extras.
04Testing that matches the stakes
Automated tests around every money-moving path, and reconciliation checks in production.
What changes for you
- 01Fraud caught earlierSuspicious activity flagged for review before it becomes a loss.
- 02Faster onboardingDocuments read and checked automatically, with people reviewing only the unclear cases.
- 03Decisions you can explainEvery automated score comes with the reasons behind it.
- 04Fewer support ticketsRoutine account questions answered instantly, sensitive ones routed to staff.
Frequently asked questions
How do you make ML models explainable for regulators?
We prefer models whose drivers can be shown per decision, add explanation methods where a more complex model is justified, and log inputs, outputs and versions so any decision can be reconstructed later.
Can you work within our security requirements?
Yes. We work in your cloud accounts and repositories under your access policies, follow least-privilege access, and sign an NDA and data processing agreement before any data is shared.
Do you build full platforms or only AI features?
Both. We build web and mobile platforms end to end, and add machine learning where it clearly improves a decision.
Next step
Tell us what you want to build.
A free 30-minute consultation with an engineer — no obligation, reply within one business day.
Contact us