TL;DR
Fraud-resistant software is the product of deliberate team design. Most fintech breaches originate in vulnerabilities that were already present in the code long before production. This blog breaks down the process and cultural changes that engineering managers and product managers need to turn security from a compliance task into a genuine engineering capability. It covers secure development lifecycle practices, DevSecOps culture, team ownership structures, and what separates teams that catch problems early from those that don't.
Why Most Engineering Teams Have a Security Problem They Don't Know About
Ask any engineering manager whether their team cares about security. They'll say yes. Ask whether security review happens before or after code ships. The answer, in most fintech organizations, is after.
That gap is where fraud lives.
According to IBM's Cost of a Data Breach 2024 report, the average data breach cost for financial firms reached $6.08 million, which is 22% above the global cross-industry average. The same research found that breaches involving stolen credentials took an average of 292 days to identify and contain. Nearly ten months. Long enough for a vulnerability to quietly sit in production, be discovered, and be exploited across thousands of customer accounts before anyone on the engineering team knows anything is wrong.
Alloy's 2025 State of Fraud research found that 60% of financial organizations reported an increase in fraudulent activity over the prior twelve months. Consumer fraud losses totalled more than $12.5 billion in 2024. These numbers represent real pressure on engineering teams to build systems that actually hold.
The honest question is not whether your team cares about security. The question is whether the processes and culture you've built make it possible to catch problems before they reach production rather than after.
How Security Fails at the Team Level
Before looking at what fraud-resistant engineering teams do well, it's worth being specific about where most teams go wrong.
Security treated as a handoff. The most common failure mode is treating security as something that happens at the end of the development process. Development builds. QA tests functionality. A security team runs a scan or penetration test in the final days before release. Any findings go back to the development team as a list that then competes with the next sprint's feature work for attention.
This creates exactly the wrong incentives. Security findings become a release blocker rather than a feedback signal. Developers learn that security review is something that happens to them, not something they participate in. And because findings appear late, they're expensive to fix.
Ownership is unclear. In teams without a defined security ownership model, everyone assumes someone else is responsible. The developer assumes the security team will catch issues in review. The security team assumes developers were following secure coding standards. Product assumes compliance is handled by engineering. Nobody is exactly wrong. But nobody is right either.
Training is infrequent and generic. Annual security awareness training that covers phishing and password hygiene does not create secure software. It creates teams that can pass a compliance checkbox. Developers who haven't been trained on the OWASP Top 10 vulnerabilities specific to financial applications will keep writing code with those vulnerabilities present, because they don't know what they're looking for.
External team security is an afterthought. When distributed or external development teams are involved, organizations often apply less rigorous security vetting than for internal hires. That reasoning gets it backwards. Third-party and contractor access is one of the highest-risk exposure surfaces in fintech. IBM's research found compromised credentials were the most common initial attack vector, accounting for 16% of all breaches and the hardest to contain once active.
The Process Foundation: Security in the Development Lifecycle
Building fraud-resistant software starts with how the development process is structured, not which security tools you purchase.
Shift Security Left
The OWASP DevSecOps Guideline frames shift-left security as embedding security measures from the inception steps of application design rather than treating security as a gate at the end. The principle is straightforward: a vulnerability found at design costs almost nothing to fix. The same vulnerability found after deployment can cost millions.
In practice, shifting left means requiring threat modeling before development begins on any feature that touches financial data or authentication flows. It means code review standards that include security criteria alongside functionality and performance. And it means automated security scanning in the CI/CD pipeline that runs on every commit, not on a weekly schedule.
For fintech teams, OWASP's Secure Software Development guidance is the most practical starting point. The OWASP Developer Guide on secure development is explicit on one key point: the secure SDLC should never be a separate lifecycle from the existing software development process. Security actions built as a parallel track get deprioritized by busy teams. Security built into the existing pipeline gets applied consistently.
Make Security Checks Automatic
Manual security review doesn't scale. When a team ships on a two-week sprint cycle, adding a manual security checkpoint for every code change creates a bottleneck that developers will route around under deadline pressure.
Automated tools integrated into your CI/CD pipeline solve this by making security feedback immediate. Static Application Security Testing (SAST) scans source code for vulnerability patterns before tests run. Dependency scanning flags known vulnerabilities in third-party libraries before they reach production. Secret detection prevents credentials and API keys from being committed to version control.
These tools are not perfect. They generate false positives and won't catch every class of vulnerability. But they create a baseline that catches the most common issues at the point where they're cheapest to fix, without requiring developers to change their core workflows substantially.
Define Access Controls from Day One
One of the most preventable classes of fintech fraud involves overprivileged access. Developers with production database access they no longer need. Service accounts with permissions broader than required. Former employees or contractors whose access wasn't revoked at offboarding.
IBM's breach data is clear that compromised credentials represent the longest-running and most expensive class of breach. The mitigation is well understood: least-privilege access by default, access reviews on a defined schedule, automated revocation at offboarding, and MFA for everything that touches production or financial data.
For engineering managers, this is partly a tooling problem and partly a process problem. Tooling automates enforcement. Process defines what access each role actually needs and creates accountability for reviewing it regularly.
The Culture Foundation: Making Security Everyone's Responsibility
Process changes are necessary but not sufficient. The teams that build genuinely fraud-resistant software have also made security a cultural norm, not just a procedural requirement.
Security Champions Create Distributed Ownership
A security champion program plants security knowledge throughout the engineering organization rather than concentrating it in a specialist team. Each squad or product team nominates one developer as a security champion. That person gets deeper security training, participates in security reviews for their team's work, and serves as the first point of escalation when developers on their team have security questions.
This model addresses the ownership problem directly. Security champions know their codebase, their team's patterns, and the specific risk profile of the features their team builds. A centralized security team reviewing dozens of teams' work simultaneously can't have that context.
The OWASP DevSecOps Maturity Model describes security champion programs as a defining characteristic of mature DevSecOps culture, the point where security moves from a specialist function to a distributed organizational capability.
Psychological Safety Around Security Issues
This one is counterintuitive but important. Teams where engineers are afraid to raise security concerns create worse outcomes than teams where those conversations happen freely.
Fear of blame when a vulnerability is found causes engineers to underreport issues they're uncertain about, delay raising problems hoping they'll resolve on their own, and avoid writing honest post-incident documentation. All of these behaviors allow vulnerabilities to persist longer and become more expensive to fix.
Engineering managers building fraud-resistant teams need to create conditions where raising a security concern is treated as professional responsibility, not as evidence of poor work. The Creating a High-Performance Engineering Culture guide covers this dynamic in depth, and the security dimension is one of the clearest examples where culture directly determines outcomes. Teams that punish the messenger don't stop vulnerabilities from existing. They just stop hearing about them.
Regular Training That Connects to Real Work
Annual compliance training doesn't change engineering behavior. Regular, role-specific training that connects to the actual code your team writes does.
For developers building payment processing features, relevant training covers PCI-DSS requirements, common injection vulnerabilities in payment flows, and the OWASP categories most likely to appear in their specific stack. For developers building authentication systems, it covers credential management, session handling, and the OAuth implementation patterns that fail in predictable, well-documented ways.
The difference between training that sticks and training that doesn't is specificity and frequency. Short, regular sessions tied to current work embed security thinking in active contexts. Once-a-year mandatory sessions teach people how to pass a quiz.
Security as a Product Concern, Not a Tax
Product managers play a role in fraud-resistant teams that's often underestimated. PM prioritization decisions shape what gets built and when. If security work competes with feature development on equal footing in the backlog, it loses. Security work rarely has a visible user benefit that anyone would point to in a demo.
PMs in fintech who have internalized security as a product concern rather than an engineering cost push for threat modeling during discovery, include security acceptance criteria in stories, and treat security debt with the same urgency as technical debt.
The framing that tends to work with stakeholders is customer trust. Fraud incidents don't just cost money to remediate. Alloy's fraud research shows that 87% of financial institutions report fraud prevention efforts save more money than they cost. But the reputational damage from a breach often outlasts the financial impact. When a customer's payment data is exposed, the relationship damage tends to be permanent.
Team Structure for Secure Fintech Development
The right team structure reinforces both the process and cultural foundations above.
Embed Security in Sprint Rituals
Security doesn't need its own meeting if it's integrated into rituals that already exist. Sprint planning that includes a quick threat review for new features touching sensitive data. Code review standards that include a security checklist alongside functional review criteria. Sprint retrospectives that surface security findings from the previous sprint and track resolution against the backlog.
None of these are significant time commitments. A five-minute threat review in planning prevents hours of remediation post-deployment. A security item in the code review checklist catches vulnerability classes that automated scanning misses.
Vetting and Onboarding External Developers
Fintech development frequently involves distributed teams, external contractors, or dedicated development partners. Each of these introduces access control and knowledge transfer challenges that internal-only teams don't face.
Fraud-resistant teams treat external developer onboarding with the same security rigor as internal onboarding: background verification appropriate to data access levels, role-specific access provisioned rather than broad credentials, security briefing covering the regulatory and data handling requirements of the engagement, and clear offboarding processes that revoke access immediately at engagement end.
For teams considering bringing in a dedicated development team to scale fintech engineering capacity, the security practices of that partner matter as much as their technical capability. A partner without mature access control practices introduces risk that internal process improvements can't fully offset.
Accountability Structures That Actually Work
Security accountability in engineering teams tends to fail in one of two ways. Either it sits entirely with a specialist security team that developers treat as external to their work, or it's distributed so broadly that no individual feels responsible for specific outcomes.
Effective accountability structures name specific owners for specific security outcomes. The security champion for each squad owns the security findings backlog for their team's codebase. The engineering manager owns the access review cycle for their team's production access. The product manager owns security acceptance criteria in the features they ship. When a finding surfaces, there's a clear owner rather than a committee.
Regulatory Compliance and Security Are Not the Same Thing
A common mistake in fintech is treating regulatory compliance as the ceiling for security investment. Build what's required for PCI-DSS, GDPR, or the relevant local regulations, and consider the security problem solved.
Compliance is a floor, not a ceiling. The requirements in financial services regulations represent the minimum defensible standard. Actual fraud vectors evolve faster than regulatory update cycles.
Our Regulatory Deadline Playbook for engineering teams covers how to meet compliance deadlines without compromising delivery, but the underlying principle is that compliance work and security work should reinforce each other rather than compete. Teams that use compliance deadlines as a forcing function for better security foundations end up stronger than teams that do the minimum to pass an audit.
The practical gap shows up clearly in vulnerability timing. Compliance audits happen periodically. Fraud doesn't wait for audit cycles. Teams whose security posture is driven by audit preparation rather than operational discipline accumulate vulnerability debt between audits that becomes expensive and risky to clear.
What Fraud-Resistant Engineering Teams Look Like in Practice
The engineering teams that build consistently fraud-resistant fintech software share several characteristics.
They have defined security ownership at the team level through a champion model. They run automated security scanning on every commit and treat findings as immediate work, not future backlog items. They conduct threat modeling as a standard part of feature discovery. They apply least-privilege access by default and review it on a schedule. They train developers on the specific vulnerability categories relevant to their codebase and stack rather than running generic annual sessions.
And critically, their leadership treats security investment as a product decision, not a cost center. Engineering managers who fight for security work in sprint planning. Product managers who include security acceptance criteria in stories. CTOs who measure security posture alongside release frequency and defect rate.
IBM's research found that organizations using AI and automation in security prevention workflows saved an average of $2.2 million per breach compared to those that didn't. The gap between teams with mature security practices and those without is measurable, and in fintech, it's significant.
Building that capability starts with an honest assessment of where your current process and culture fall short, and deliberate investment in closing those gaps, before a breach forces the conversation.
If you're scaling a fintech engineering team and want partners who have these practices built in, the Scrums.ai dedicated teams model is designed for fintech delivery environments where security and speed both matter. If you'd like to work through where your current team's security posture stands, a consultation is the right first step.
Frequently Asked Questions
What is a fraud-resistant engineering team?
A fraud-resistant engineering team has security practices embedded across its development process and culture, rather than treated as a late-stage checkpoint. This includes automated scanning in CI/CD pipelines, threat modeling during feature design, clear ownership through security champion programs, and least-privilege access controls. The goal is catching vulnerabilities before production rather than after they've been exploited.
What does secure software development mean in fintech?
Secure software development in fintech means building applications where security is integrated at every phase of the development lifecycle, from design through deployment. In practice this includes threat modeling, secure coding standards aligned with OWASP guidelines, automated vulnerability scanning, access control enforcement, and regular developer training. Fintech has specific requirements around financial data handling, PCI-DSS, and fraud prevention that shape what secure development looks like.
What is shift-left security and why does it matter for fintech teams?
Shift-left security means embedding security checks earlier in the development process rather than running them as a final gate before release. Vulnerabilities found at the design or development stage cost a fraction of what they cost to remediate post-production. In fintech, where a single breach can cost over $6 million on average, finding problems early is financially material, not just operationally convenient.
How do you build a security culture in an engineering team?
Building a security culture requires structural changes alongside training. Security champion programs distribute ownership so every squad has someone with deeper security knowledge embedded in their work. Psychological safety around raising concerns prevents underreporting. Regular, role-specific training connects security to actual developer work rather than generic awareness sessions. Leadership that treats security as a product metric, not a compliance cost, reinforces all of it.
What is a security champion program?
A security champion program selects or nominates one developer per squad to receive deeper security training and serve as the team's first point of contact for security questions and reviews. Champions participate in security reviews for their team's work, maintain the team's security findings backlog, and help propagate secure coding standards within the squad. The model distributes security knowledge throughout the organization rather than concentrating it in a specialist team that lacks codebase context.
How should fintech teams vet external or distributed developers for security?
External developers should go through security onboarding with the same rigor as internal hires, scaled to their data access level. This includes role-specific access provisioning rather than broad credentials, a security briefing covering the regulatory and data handling requirements of the engagement, background verification appropriate to data sensitivity, and a clear offboarding process that revokes access promptly at engagement end. Compromised or overprivileged external access is one of the most common breach vectors in financial services.
What is the difference between compliance and security in fintech engineering?
Compliance defines the minimum requirements your software must meet to satisfy regulatory obligations. Security is the operational capability to protect customer data and financial systems from real fraud and attack vectors. Compliance requirements are point-in-time standards updated on regulatory cycles. Actual attack methods evolve continuously. Teams that build to the compliance floor and stop accumulate vulnerability debt between audit cycles that fraud actors can exploit.
How does DevSecOps apply to fintech development?
DevSecOps integrates security into every phase of the software development pipeline, from design through deployment and monitoring. In fintech, this means security scanning runs automatically on every code commit, threat models are created during feature discovery, access controls are defined and enforced in infrastructure code, and post-deployment monitoring includes security anomaly detection. The OWASP DevSecOps Guideline and NIST Secure Software Development Framework both provide frameworks specifically designed for implementing these practices in production engineering environments.
