How We Applied Fintech Security Best Practices Without Slowing Software Releases

Quick Summary

Introduction

Our release date was meant to be a simple one. All the requirements for the feature had been met, the client had been waiting for it for weeks, and the sprint board was finally clear again. Yet at the last moment on a Friday, the security check found three major problems, which led to a delayed release for a whole week. This was not the first such occurrence, making us conclude that security was still considered a final step and not an integral part of development.

The client was a digital lending service dealing with highly sensitive data; security could never be something to be considered in the end. Every new sprint brought not only new functionality but also potential risks of any kind if the security checks were postponed till the end.

This article shares our fintech security best practices, why we chose them, and how they helped us build a faster, more secure development workflow.

Why Our Existing Release Process Needed to Change

When we took over the project, a security review happened right before deployment. A senior engineer or an external auditor would look at the release candidate, and if something was wrong, it went back to the queue.

This worked fine when we shipped once a month. It stopped working when we moved to weekly releases. A few problems showed up quickly:

• Developers only found out about security issues after the code was already considered “done.”
• The security team became a queue, not a partner, since every release waited on their availability.
• Fixes made late in the cycle were more expensive and more rushed than fixes made during development.
• Compliance documentation was recreated manually for every release instead of being generated as part of the process.

None of this was anyone’s fault. The process was built for a slower release cadence, and it simply had not been updated as the team scaled.

Moving Security Earlier With Shift-Left Security

We started reading about DevSecOps, and the idea of shift-left security kept coming up. Instead of treating security as a final gate, shift-left security means building security checks into the development process itself, starting from the first commit.

For us, that meant three concrete changes:

• Moved security scanning into the CI/CD pipeline instead of running it manually before release.
• Gave developers direct visibility into security findings inside their pull requests, not in a separate report.
• Involved our security engineer in sprint planning, so risky features got a security review of the design before a single line of code was written.

Shift-left security did not remove the need for expert review. It just moved that expertise earlier, where it was cheaper and faster to act on.

8 Fintech Security Best Practices We Built Into the Pipeline

Fintech security best practices only matter when they’re part of everyday development, not something revisited before an audit or a release. These are the practices we integrated into our workflow, the challenges they addressed, and the impact they had over time.

1. Automated Security Testing in CI/CD

One of our biggest gaps was relying on manual security checks just before deployment. By the time vulnerabilities were discovered, they had often been sitting in the codebase for weeks.

What we changed

• Added Static Application Security Testing (SAST) to every pipeline.
• Included automated dependency vulnerability scanning.
• Blocked pull requests whenever critical security checks failed.

Result
Security became part of development rather than a final checkpoint. Issues were caught within minutes of being introduced, and every build followed the same security standard.

2. Secure Secrets Management

Keeping API keys or database credentials inside repositories creates unnecessary risk. Even limited repository access can expose production systems if secrets aren’t managed correctly.

What we implemented

We moved all sensitive credentials into a dedicated secrets management platform and replaced long-lived credentials with short-lived access tokens.

Business impact

Instead of becoming a major security incident, an exposed credential simply expired before it could be misused, dramatically reducing long-term risk.

3. Role-Based Access Control (RBAC)

As the engineering team expanded, permissions became broader than necessary. Developers often had access to systems unrelated to their responsibilities.

Key improvements

• Defined access based on job responsibilities.
• Applied least-privilege permissions across internal systems.
• Logged and reviewed all privileged access requests.

The biggest advantage wasn’t just tighter security—it also limited the impact if an account was ever compromised.

4. Encryption for Data in Transit and at Rest

Most cloud platforms encrypt stored data by default, but internal service-to-service communication is often overlooked. Instead of assuming our private network was secure, we treated data security as an end-to-end requirement and encrypted customer data at every stage.

Our approach included:

• Encryption for stored customer information.
• TLS encryption between internal services.
• Quarterly reviews of certificates and encryption configurations.

This ensured that even if part of the internal network was compromised, sensitive financial data remained protected.

5. Multi-Factor Authentication (MFA)

Initially, MFA protected production environments but not internal dashboards or staging systems. After reviewing our environment, we expanded MFA everywhere customer data could be accessed.

Outcome

• Protected internal administration tools.
• Secured staging and testing environments.
• Reduced the risk of compromised passwords leading to unauthorized access.

6. API Security

Financial applications depend heavily on APIs, making them one of the most common attack surfaces. Rather than treating every endpoint differently, we established a consistent security baseline.

Security controls added

• Rate limiting at 100 requests per minute per API key on transaction endpoints
• Strict input validation
• Token-based authentication
• Automated security tests for every endpoint

As a result, every API followed the same minimum security standard instead of depending on individual developer implementation.

7. Third-Party Security Assessments

Internal reviews are valuable, but they rarely provide the level of assurance regulators or enterprise clients expect. We scheduled periodic penetration testing with independent security specialists who evaluated the platform from an external perspective.

Why it mattered

• Added credibility during client security reviews
• Improved audit readiness
• Identified weaknesses our internal team had overlooked

8. Automated Compliance Checks

Preparing for audits used to mean gathering logs, screenshots, approvals, and documentation at the last minute. For a lending platform handling cardholder and account data, PCI DSS compliance evidence was the heaviest lift. Instead of treating compliance as a separate activity, we integrated it directly into our development pipeline.

What changed

• Compliance evidence was generated automatically
• Logs and approvals were captured continuously
• Audit artifacts were always available when needed

The result was a much smoother audit process, allowing engineering teams to focus on releases rather than scrambling to assemble documentation.

How We Balanced Security With Release Speed

Not every security issue deserved the same response, and treating them all the same was part of why our old process was slow.

We split findings into two categories. Critical issues, like an exposed secret or an unauthenticated endpoint, blocked the deployment automatically. Lower-severity issues, like an outdated dependency with no known active exploit, generated a warning and a ticket instead of stopping the release.

One example stands out. We had a manual security engineering review where security engineers manually reviewed all releases for hardcoded credentials. This was then substituted with automated scanning for secrets within the pipeline. The manual process would take anywhere between a few hours and up to a day based on the availability of the engineers. However, the automated process takes less than two minutes to complete.

This is the part of fintech security best practices that often gets missed. It is not only about which controls you add. It is about deciding which controls need a human gate and which ones can run automatically without slowing the team down.

Building Collaboration Between Security and Engineering

The biggest shift was not technical. It was cultural.

Security used to be the team that said no at the end of the process. We changed that by including our security engineer in sprint planning and design discussions from the start. Developers started asking security questions before writing code instead of after.

This is a habit we’ve carried across our fintech software development company at Bacancy Technology, treating security as a shared responsibility from day one, not a final gate. We also started sharing security findings openly in the same dashboards developers already used, instead of a separate report only the security team could see. That single change made security feel like part of engineering, not a separate department checking engineering’s work.

Results

After several months of running this process, the numbers spoke for themselves:

• Release cycles got faster, since security no longer sat at the end of the pipeline as a bottleneck.
• Vulnerabilities were caught during development instead of during a final review, which meant fewer late-stage surprises.
• Compliance readiness improved, since audit evidence was already generated by our automated checks.
• Production security issues dropped, because problems were caught before code ever reached production.

Third-party risk is worth watching closely here too. Across the industry, breaches involving third parties doubled to 30% of incidents in 2025, according to Verizon’s Data Breach Investigations Report, which is exactly why we treated vendor and dependency scanning as a first-class part of our pipeline rather than an occasional check.

Conclusion

Frequently Asked Questions (FAQs)

Does adding fintech security best practices always slow down releases?

Not if the checks run earlier in the pipeline. Manual, end-of-cycle reviews cause delays. Automated checks built into CI/CD generally do not.

What is the first step for a team wanting to shift security left?

Start by adding automated security scanning to your CI/CD pipeline and giving developers visibility into findings inside their existing workflow, rather than a separate report.

Do smaller fintech teams need all eight fintech security best practices at once?

No. Start with secrets management, RBAC, and automated CI/CD scanning, since these fintech security best practices give the fastest risk reduction for the least setup effort.

How often should third-party security assessments happen?

Most teams benefit from at least an annual external penetration test, with more frequent internal reviews for high-risk releases or major architecture changes.