GUEST POST: Zac Amos (ReHack)

The Fintech landscape is constantly growing, but with that progress comes more responsibility.

As financial apps handle increasingly sensitive user information and facilitate billions of transactions, the stakes become higher.

Cyberattacks keep increasing in frequency and sophistication, so Fintech app developers must prioritize security to keep threat actors from exploiting their users.

Here’s a 5-step guide in building & deploying best-in-class applications:

1. Implement Zero Trust Architecture From the Start

With the rise of cloud-native environments, third-party integrations and remote access, the traditional “trust but verify” model leaves too many gaps.

Instead, zero trust architecture employs the concept of never trust, always verify, treating every access request as potentially hostile until proven otherwise.

This framework is quickly becoming the new standard for every industry. In fact, Gartner found that 56% of organizations prioritizing zero trust cite it as a best practice, recognizing its ability to reduce the risk of lateral movement during a breach.

For Fintech developers, implementing zero trust means:

Micro-segmentation of app services and infrastructure.
Strict identity and device verification through continuous authentication.
Granular access controls based on user roles, context and risk level.

Take the example of Plaid — a FinTech API company. This provider partnered with Skyflow — a data privacy vault brand — to enable developers to build faster while securely isolating and tokenizing sensitive data like PII and PCI information.

This collaboration enables internal data access restrictions through fine-grained access policies and randomized tokens. For teams building Fintech platforms, adopting privacy-centric data infrastructure like Skyflow’s can enforce zero trust principles while meeting compliance demands.

2. Conduct Regular Updates and Software Patches

Outdated software is a prime target for cybercriminals, as they often exploit known vulnerabilities in libraries, frameworks or software development kits.

In a sector that handles such sensitive financial information and operates under heavy restrictions, overlooking these updates is a liability.

Regularly releasing security patches and updates is critical to maintaining a strong defense posture. Yet, in practice, delaying patching is common due to concerns about service disruption. The longer the patch becomes postponed, the greater the attack window becomes.

For example, suppose an app uses a third-party encryption library with a disclosed vulnerability involving potential memory leaks. If the team delays patching while waiting for a major version upgrade, attackers scanning for unpatched versions could exploit the flaw and expose user data.

To minimize these risks:

Implement automated vulnerability scanning tools in the CI/CD pipeline.
Establish a clear patch management schedule tied to sprint cycles.
Use feature flagging or phased rollouts to deploy updates without disrupting service.

3. Use End-to-End Encryption

End-to-end encryption (E2EE) ensures sensitive data is hidden on the sender’s device and only decrypted on the receiving end, preventing even the service provider from accessing it.

When an app handles payment details, personal identifiers or authentication credentials, this level of protection is necessary.

However, many apps mistakenly assume HTTPS alone is enough. While Transport Layer Security (TLS) protects data in transit, it lacks safeguards against vulnerabilities on the client or server side, where unencrypted data may briefly exist. With full E2EE, Fintech enterprises ensure data is inaccessible throughout its journey.

Various ways to strengthen an encryption strategy include:

Using TLS 1.3 for all communications, with strict cipher suites and certificate pinning to prevent man-in-the-middle attacks.
Using strong symmetric encryption algorithms like AES-256 to encrypt data at rest.
Protecting private keys using hardware security modules or cloud key management services.

Additionally, developers should avoid building their own encryption algorithms. Leveraging trusted cryptographic libraries and regularly updating them is key.

4. Adopt Secure Coding Standards

Fintech apps operate in a high-risk environment where a single overlooked vulnerability in the codebase can lead to financial fraud or data breaches.

That is why secure coding should be a core pillar of responsible development.

Secure coding standards help development teams avoid common pitfalls like injection flaws and broken authentication. Frameworks like the OWASP Application Security Verification Standard provide a checklist of security requirements for everything from architecture to deployment. Meanwhile, adhering to language-specific guidelines ensures consistent, defensible practices across the codebase.

Following standards provides a good basis for secure development, but code reviews and automated testing are equally critical. Doing a thorough peer review or security-focused test is important to prevent unauthorized access.

To build a secure pipeline:

Enforce peer code reviews with a checklist that includes input validation, proper handling and authentication flow checks.
Integrate static application security testing tools into the CI/CD pipeline to catch vulnerabilities early.
Apply good input where possible, especially for fields like dates, IDs and numerical inputs.

5. Build Real-Time Fraud Detection Systems

Static rule-based systems are insufficient for how fraud-based threats are moving in today’s Fintech applications.

To keep up, developers must design real-time fraud detection systems powered by adaptive intelligence and behavior analytics.

AI and machine learning are becoming increasingly integrated into the financial sector. These systems work around the clock to flag anomalies the moment they occur. Because of their powerful capabilities, there is a massive investment in AI, and market projections predict it will exceed $64 billion by 2030 in the banking market.

Institutions are increasingly relying on automation because machine learning models (MLMs) can detect fraud, automate risk scoring and personalize security responses. This innovation offers a proactive approach to security, allowing platforms to intervene when suspicious activity occurs.

Implementing real-time fraud detection requires the following steps:

Use MLMs trained on historical and real-time behavioral data to identify anomalies.
Deploy a rules engine for predictable fraud patterns.
Integrate with data pipeline tools for stream processing.
Store logs and flagged activities in a centralized security information and event management system for forensic analysis and regulatory compliance.

Making Security the Foundation of Fintech App Development

Building a secure Fintech app means treating security as a continuous commitment.

By prioritizing privacy and proactive defense at every stage of development, businesses can earn user trust and stay ahead of today’s threats.

About the Author: Zac Amos (Features Editor at ReHack Magazine) is a tech writer who specializes in fintech, AI, and cybersecurity, and he has bylines on publications such as Forbes, VentureBeat, and Advisorpedia. For more of his work, check out his portfolio site or follow him on LinkedIn or X (Twitter).

5 Tips for Secure Fintech App Development