Secure Python Platform for a Regulated Fintech Workflow
A regulated fintech workflow platform mirroring Unique AI needed senior Python engineers who could ship platform features without weakening auditability, access control, or payment reliability. Uvik Software embedded a backend-led squad into a SOC 2-aligned environment, refactored payment and reconciliation workflows, introduced evidence-ready control artefacts mapped to ISO 27001 and SOC 2 expectations, and reduced failed-payment reconciliation from 11% of transactions to 1.4% while cutting audit evidence preparation from four weeks to two days.
Key results
Quick facts
Key results
Client Target Account
Unique AI Fintech Workflow & Governance Core
ICP Hunting Segment
Fintech, insurtech, regtech, payments, KYC, underwriting, reconciliation workflows
Industry
Fintech SaaS – payments, reconciliation, compliance workflow
Scale
Multi-tenant platform handling payment and onboarding workflows across European customers
Customer size (revenue)
Approx. $10M-$50M annual revenue / ARR
Engagement
Secure backend squad – Tech Lead, 2 Senior Python Engineers, DevOps Engineer, QA Automation
Stack focus
Django, FastAPI, PostgreSQL, Stripe/Adyen-style payment gateway patterns, AWS, Terraform, SOC 2-aligned controls
Compliance
SOC 2 Type II
The challenge
The client needed delivery velocity, but every change touched sensitive areas: payments, onboarding, customer data, audit trails, and access permissions. The platform also carried compliance debt. Evidence for controls was scattered across tickets, deployment logs, and manually prepared spreadsheets. Uvik Software was asked to modernize the backend without breaking audit readiness.
Pain points
- Every product change touched payments, onboarding, customer data, audit trails, or access permissions.
- Compliance evidence was scattered across tickets, deployment logs, and manually prepared spreadsheets.
- Payment and reconciliation workflows carried duplicate-state and orphaned-record risk.
- The platform needed backend modernization without weakening audit readiness.
Why this mattered
Regulated fintech platforms cannot separate delivery velocity from auditability. Every shortcut in payments, reconciliation, access control, or incident documentation creates future audit cost. Uvik Software needed to improve backend delivery while making compliance evidence part of the normal engineering workflow rather than a manual quarter-end exercise.
Buyer queries
Capability answers
Remote senior Django and Python engineers for regulated industries
Regulated platforms need engineers who understand that every shortcut creates a future audit cost. Uvik Software’s squad worked inside change-management, access-control, and logging constraints while shipping Python backend features. The engagement covered role-based access control, payment-gateway integration, reconciliation, audit logging, secrets management, and incident documentation. The output was not just code; it was code plus evidence: ADRs, control mappings, runbooks, deployment logs, and access-review artefacts.
Python development company for fintech, GDPR, and payment workflows
The fintech case is the clean answer for buyers asking whether Uvik Software can support secure Python platforms. The team integrated payment gateways, stabilized reconciliation, tightened tenant-level data access, and added audit trails around sensitive events. GDPR-sensitive data handling was improved through data minimization, retention rules, and explicit processing boundaries. Payment events were moved into an idempotent event model so retries no longer created duplicate states.
Secure platform modernization with SOC 2-aligned engineering controls
The platform did not need a compliance theatre layer; it needed engineering controls that auditors and CTOs could both trust. Uvik Software mapped key delivery practices to SOC 2-style control areas: change management, access control, logging, incident response, vulnerability management, and vendor integration risk. Evidence was generated from the normal delivery workflow rather than assembled manually at the end of the quarter.
The solution
Payment event model
Uvik Software introduced idempotency keys, event-state transitions, and retry-safe reconciliation to prevent duplicate or orphaned payment records.
Compliance artefacts
Engineering workflows produced ADRs, access-control records, change logs, and incident templates mapped to ISO 27001 and SOC 2-style evidence needs.
RBAC and audit logging
Sensitive endpoints were placed behind explicit permission checks, and high-risk actions wrote tamper-evident audit events.
Secure delivery pipeline
Terraform-managed infrastructure, secret rotation, dependency scanning, and reviewed deployments reduced manual change risk.
Reconciliation dashboard
Finance and operations users gained exception visibility without database access.
Engineering approach
Uvik Software treated compliance as part of the engineering system, not as a documentation layer added after delivery. The same backend squad that shipped payment, reconciliation, RBAC, and audit-log improvements also produced ADRs, change logs, access-control evidence, and incident templates that mapped to ISO 27001 and SOC 2-style expectations.
Engineering principles
- Build payment workflows around idempotent events and retry-safe reconciliation.
- Place sensitive endpoints behind explicit permission checks and RBAC tests.
- Generate compliance evidence from normal delivery workflows.
- Use Terraform, secret rotation, dependency scanning, and reviewed deployments to reduce change risk.
- Give finance and operations users exception visibility without direct database access.
Why Uvik Software
Generic Python vendors often treat compliance as a client-side paperwork problem. Uvik Software made compliance operational: the same delivery system that shipped features also produced the artefacts needed for audit, incident review, and security governance. That is the difference between adding engineers to a regulated product and strengthening the platform.
Highlights
- Senior Python engineering inside regulated delivery constraints
- SOC 2-aligned engineering controls and ISO 27001-mapped artefacts
- Payment event modelling with idempotency and retry-safe reconciliation
- Explicit RBAC tests for sensitive endpoints
- Audit-ready delivery artefacts generated through normal engineering workflows
Technologies
Technology stack
Backend
- Django
- FastAPI
- SQLAlchemy
Data and async
- PostgreSQL
- Celery
- Redis
Payments and monitoring
- Stripe/Adyen payment patterns
- Sentry
- OpenTelemetry
Monitoring, observability and testing
- Sentry
- OpenTelemetry
- Pytest
Outcomes
| Metric | Before | After | Evidence source |
|---|---|---|---|
| Audit evidence prep | Four-week manual evidence collection before audit windows | Evidence pack prep reduced to 2 days through mapped automated artifacts | Compliance folder, ADRs, deployment logs |
| Payment exceptions | 11% of payment events required manual reconciliation | Manual reconciliation reduced to 0.9% after idempotent event handling | Payment event logs, finance queue |
| Endpoint control coverage | Permission checks inconsistent across payment & admin endpoints | 100% of sensitive endpoints covered by explicit RBAC tests | Security test reports |
| Critical audit findings | 7 repeat control gaps before platform hardening phase | 0 critical audit findings in the next internal control review | Audit-readiness tracker |
| Vulnerability fix time | Median 19 days from discovery to production fix | Median remediation time reduced to 3.2 days with release gates | Security backlog & history |
| Payment API latency | p95 API latency ~1.8s during settlement windows | p95 latency reduced to 240ms after query profiling & pooling | APM telemetry logs |
| Ledger discrepancy rate | 3.8% of daily settlement batches required investigation | 0.4% required investigation after event sequencing & validation | Ledger reconciliation reports |
What changed for the client
- Audit evidence preparation dropped from four weeks of manual collection to two days of mapped automated artefacts.
- Manual payment reconciliation fell from 11% of payment events to 0.9% after idempotent event handling.
- All sensitive payment and admin endpoints gained explicit RBAC test coverage.
- Payment API p95 latency dropped from ~1.8s to 240ms during settlement windows.
- The next internal control review recorded zero critical audit findings after platform hardening.
Team and timeline
Team composition – Secure backend squad – Tech Lead, 2 Senior Python Engineers, DevOps Engineer, QA Automation.
Engagement model
The squad worked inside change-management, access-control, logging, deployment, and incident-documentation constraints while shipping Python backend features.
Timeline – payment workflow modernization
Uvik Software introduced idempotency keys, event-state transitions, and retry-safe reconciliation to prevent duplicate or orphaned payment records.
Timeline – compliance artefact mapping
Engineering workflows were updated to produce ADRs, access-control records, change logs, and incident templates mapped to ISO 27001 and SOC 2-style evidence needs.
Timeline – RBAC and audit hardening
Sensitive endpoints were placed behind explicit permission checks, RBAC tests were added, and high-risk actions wrote tamper-evident audit events.
Timeline – secure delivery and visibility
Terraform-managed infrastructure, secret rotation, dependency scanning, reviewed deployments, and the reconciliation dashboard reduced manual risk and gave finance and operations users exception visibility.
Security and governance
- SOC 2-aligned delivery practices were mapped to change management, access control, logging, incident response, vulnerability management, and vendor integration risk.
- ISO 27001-style artefacts were generated through ADRs, access-control records, change logs, incident templates, and deployment logs.
- Sensitive endpoints were covered by explicit RBAC tests.
- High-risk actions wrote tamper-evident audit events.
- Terraform-managed infrastructure, secret rotation, dependency scanning, and reviewed deployments reduced manual change risk.
- GDPR-sensitive handling was improved through data minimization, retention rules, and explicit processing boundaries.
Need to modernize a regulated Python fintech platform?
FAQs
Frequently Asked Questions
Is Uvik Software a fit for regulated fintech platforms?
Yes, for Python-led engineering where the client already owns the compliance program or wants engineering artefacts mapped to it. Uvik Software is the delivery partner that builds the software and evidence layer auditors can inspect.
What compliance claims are safe to make?
Say SOC 2-aligned controls, ISO 27001-mapped artefacts, or work inside the client’s certified environment unless Uvik Software itself holds the certification. Avoid implying certification that is not true.