Introduction
Picture this: It's six weeks before a major product launch. Your team has been sprinting hard for months, feature velocity is high, and the demo looks great. Then legal drops a new requirement: the upcoming release also needs to satisfy a regulatory milestone that nobody flagged in sprint planning. Suddenly your roadmap is in pieces, engineers are context-switching into compliance work they were never set up to handle, and the launch date is at risk.
This is not a rare scenario. According to an Alloy survey of fintech compliance professionals, 93% of respondents said it is somewhat or very challenging to meet regulatory requirements, and the pressure is intensifying. According to Corlytics data reported by Fintech Global, regulatory bodies increased their fines in 2024 to reach $19.3 billion, a figure that signals how seriously enforcement is being taken across the financial sector.
For product managers and engineering managers in fintech and banking, regulatory compliance engineering is no longer a concern you can hand off to legal after the fact. The technical requirements embedded in frameworks like PCI DSS, GDPR, and DORA touch every layer of your stack, and every sprint.
This playbook is for the teams doing the actual work of building compliant systems. It covers what the major frameworks actually demand from your engineering team, how to restructure your delivery process so compliance deadlines do not blindside you, and where to bring in additional capacity when the scope exceeds what your core team can absorb. You will not find vague principles here. You will find a working structure you can start applying immediately.
What Is Regulatory Compliance Engineering in FinTech?
Regulatory compliance engineering is the practice of designing, building, and maintaining software systems so they satisfy the technical requirements of financial regulations. It is distinct from legal compliance or policy documentation. While your compliance team interprets regulations, your engineering team is responsible for implementing the controls those regulations require, embedding them into architecture, code, pipelines, and monitoring systems.
In fintech and banking, this covers a wide set of obligations. Platforms must comply with overlapping and sometimes conflicting regulations: GDPR, CCPA, PSD2, PCI DSS, and dozens of country-specific frameworks, while also contending with evolving fraud threats, accelerated innovation cycles, and heightened enforcement.
The distinction that matters for engineering teams is between compliance by retrofit and compliance by design. Retrofit compliance happens when legal or compliance teams review a nearly-finished system and find gaps that require rework. Compliance by design means regulatory controls are scoped and built alongside every feature, from the first sprint.
Good to know: The cost difference between these two approaches is real and large. Compliance gaps found post-build require rework across data models, authentication flows, and audit infrastructure, changes that ripple into components your engineers thought were finished. Catching the same gap during design takes a fraction of the time.
Cutting corners may save engineering cycles initially, but deferred compliance often manifests as product rewrites, urgent remediation projects, or blocked partnerships later on.
What Do the Major Regulations Actually Require From Your Engineering Team?
Most engineering teams are familiar with the names of major regulations. Fewer teams have a precise view of the technical obligations those regulations create. Here is what your engineers need to implement to satisfy the three frameworks most commonly affecting fintech and banking companies operating in 2025 and 2026.
PCI DSS v4.0 Technical Requirements
PCI DSS applies to any system that stores, processes, or transmits cardholder data. PCI DSS v4.0 introduced 51 new requirements that became mandatory on March 31, 2025, covering updates to password rules, expanded multi-factor authentication, and stronger protection of cardholder data.
For engineering teams, the headline obligations translate to concrete build work. Your team is responsible for configuring and maintaining network firewalls that isolate the cardholder data environment from all other systems. This includes reviewing firewall rules whenever new APIs or services are introduced. Multi-factor authentication and role-based access control are explicit requirements under PCI DSS, reducing the risk of unauthorized access to sensitive data.
Data encryption is non-negotiable for card data in transit and at rest, with proper key management forming part of the assessment. Your software development lifecycle must include code reviews, vulnerability scanning, and penetration testing, and any findings must be remediated promptly rather than deferred to a future sprint. PCI DSS Requirement 10 mandates centralized, tamper-proof logs for access, configuration changes, and sensitive user actions, which means logging infrastructure needs to be scoped into your architecture from the start, not added as an afterthought.
Important: According to a 2024 Verizon Payment Security Report cited by Metomic, only 43% of organizations maintain full PCI DSS compliance year-round. Compliance is not a state you achieve once at audit time. It is an ongoing operational posture that requires continuous monitoring and regular testing.
GDPR Technical Requirements
GDPR creates obligations that go well beyond privacy policy updates. For engineering teams building products used by EU residents, the regulation requires deliberate architectural decisions.
Data minimization under Article 5 means your data models should be scoped to collect only what you need for a clearly defined purpose. Any additional data collection requires a separate legal basis and must be documented. Consent flows need to be implemented in a way that is specific, informed, and freely given, which has direct implications for how your front-end and back-end capture and store user preferences.
The requirement with the sharpest engineering edge is breach notification. Under Article 33 GDPR, a controller must notify the supervisory authority without undue delay and, where feasible, not later than 72 hours after becoming aware of a personal data breach. This 72-hour window is not primarily a legal or PR challenge. It is an engineering challenge. Your monitoring, alerting, and incident response infrastructure must be capable of detecting a breach, scoping its impact, and generating the information needed for a regulatory notification, all within three days.
Enforcement reached EUR 1.2 billion in GDPR fines during 2025 alone, with regulators targeting operational failures, not just policy gaps. Engineering teams that build detection-to-notification workflows as a core capability, rather than improvising during incidents, are the ones who meet the window consistently.
Pro tip: Build your breach response runbook before you need it. Define clear roles, document what information regulators require under Article 33, and test the workflow in a tabletop exercise. The 72-hour clock starts when you become aware of a breach, not when you finish investigating it.
DORA Technical Requirements
The EU Digital Operational Resilience Act came into effect on January 17, 2025. DORA requires financial entities to build IT risk management, incident response, and third-party oversight into their operations. Even if you are not based in the EU, working with EU financial institutions could pull you into DORA's scope.
For engineering teams, DORA translates into several concrete build and operational requirements. ICT risk management frameworks must be formal and documented, covering how your team identifies, classifies, and responds to technical risks. Incident reporting obligations for major ICT incidents are structured similarly to GDPR's breach notification, requiring timely reports to competent authorities.
Third-party risk management under DORA has particularly significant engineering implications. Two key aspects of DORA are secure data transmission and managing third-party risks, including third-party connections and shadow APIs. Your engineering team is responsible for inventorying all third-party integrations, assessing each for criticality, and ensuring that your contracts and SLAs support your ability to audit or exit those vendors if needed.
Digital operational resilience testing is the other major engineering obligation. DORA requires threat-led penetration testing and regular resilience exercises for systems deemed critical, which means your testing cadence needs to align with regulatory requirements, not just internal risk appetite.
Why Compliance Deadlines Slip: The Four Root Causes
Understanding why compliance deadlines fail in engineering teams is the first step to preventing it. The same patterns appear across fintech and banking organizations, regardless of size.
Compliance scoped outside the sprint. When compliance requirements are managed separately from the engineering backlog, they inevitably compete with feature work rather than being integrated with it. The result is a deadline that feels sudden to the engineering team, even though the regulatory timeline was visible for months.
No compliance owner in the squad. Regulatory compliance engineering requires someone in each squad who understands both the technical implications and the regulatory context. Without that role, compliance tasks get deprioritized when sprint capacity is tight, and gaps accumulate silently.
Retrofit architecture. Systems built without compliance controls in their original design require the most disruptive remediation. Adding tamper-proof audit logging, data minimization constraints, or MFA flows to an existing system means touching infrastructure that other features depend on, creating scope that is hard to estimate and hard to schedule.
Third-party blindspots. Many fintech products rely heavily on external APIs and vendor integrations. Each new payment feature, lending model, or crypto integration can alter your licensing obligations, introduce extra AML and privacy regulations, and prompt oversight from sponsor banks, card schemes, and regulators in various jurisdictions. If your compliance scope does not account for every third-party integration, you will be surprised by gaps during audits.
How Should Engineering Teams Structure Compliance Work?
The most effective fintech teams treat regulatory requirements the same way they treat functional requirements: as items that flow through the backlog, carry acceptance criteria, and ship in sprints. This approach, commonly called shift-left compliance, moves regulatory considerations to the earliest stages of development rather than leaving them for pre-launch review.
Treat Compliance as User Stories
Integrating regulatory and control requirements into backlog grooming, design reviews, and release gates ensures that compliance is treated as a non-functional requirement rather than an afterthought. User stories can include explicit acceptance criteria tied to controls such as access management, encryption, or audit logging, enabling product owners and engineering teams to address regulatory expectations incrementally with every sprint.
This means your Definition of Done for any story touching the payment flow, user data, or authentication should include compliance acceptance criteria. A story is not done when it functions correctly. It is done when it functions correctly and satisfies the relevant control requirement.
Conduct Compliance Impact Assessments During Backlog Refinement
Rather than testing for compliance after features are built, agile fintech teams conduct compliance impact assessments during backlog refinement. This early identification of regulatory requirements prevents costly rework and ensures that compliance shapes design rather than constraining it after the fact.
During refinement, ask a simple set of questions for each story. Does this feature touch cardholder data? Does it collect, store, or transmit personal data covered by GDPR? Does it introduce a new third-party dependency that falls under DORA's third-party risk requirements? The answers determine whether compliance controls need to be built into the story or scoped as a linked story in the same sprint.
Embed a Compliance Champion in Each Squad
The engineering lead embeds controls in code, maintains immutable audit logs, and enforces least-privilege access. The product manager aligns release cycles with compliance milestones, allocates sprint time for control reviews, and gathers usage metrics for continuous improvement.
In practice, the most effective configuration is a compliance champion within the squad, a role that does not need to be a dedicated hire but does need to be an explicit responsibility. This person participates in refinement to flag compliance implications, reviews stories for control gaps before development begins, and owns the documentation that becomes your audit evidence.
Learn more: Scrums.com's Modern Banking Architecture blog covers the architectural patterns that make compliance controls easier to maintain at scale, including how to structure data environments, API layers, and access control into your core system design.
Automate Compliance Checks in Your Pipeline
Manual compliance validation is a bottleneck. Automated checks embedded in your CI/CD pipeline catch issues before they reach review, keeping velocity high without trading off compliance posture. Automation is one of the strongest ways to keep agile delivery fast, often referred to as Compliance-as-Code, similar to Infrastructure-as-Code.
For a fintech engineering team, this means SAST and DAST tools run on every commit, secrets scanning is standard, dependency vulnerability checks block merges on critical findings, and infrastructure configuration is verified against compliance baselines before deployment. The compliance review at the end of the sprint becomes a confirmation of what automation has already validated, rather than a first-pass discovery exercise.
Note: Automated scanning catches known vulnerability patterns and configuration drift. It does not replace the need for human review of architectural decisions, third-party integrations, or novel feature implementations where the compliance implications are not yet codified in tooling.
What Does a Compliance-Ready Engineering Roadmap Look Like?
A compliance-ready roadmap structures delivery so that regulatory milestones are treated with the same weight as feature launches. Here is a framework that works for teams working toward a defined deadline, whether that is a PCI DSS assessment, a GDPR audit, or a DORA resilience test.
Phase 1: Regulatory Scoping (Weeks 1-4)
Before writing a line of compliance-related code, your team needs a clear map of what applies and where. This phase covers cataloguing all systems that touch regulated data, identifying every third-party integration that creates compliance obligations, and producing a gap analysis against the relevant control framework.
The output is a compliance backlog: a set of stories and epics representing every gap between your current system and the regulatory requirement. This feeds directly into sprint planning, which means no surprise scope drops six weeks before a deadline.
Phase 2: Architecture and Controls Build (Weeks 5-12)
This is where the structural work happens. Data architecture changes, audit logging infrastructure, access control frameworks, encryption key management, and breach detection pipelines all need to be built and tested before feature-level compliance controls can be validated effectively.
The secure software development lifecycle must incorporate code reviews, vulnerability scanning, and penetration testing into the development pipeline, with findings remediated promptly. This phase is also where most teams discover their current capacity is not enough. The structural compliance build often runs in parallel with ongoing product development, and most teams do not have sufficient depth to absorb both without one suffering.
Phase 3: Control Validation and Documentation (Weeks 13-16)
As controls are built, validate them against the regulatory requirement they are meant to satisfy. This phase involves internal testing, penetration testing where required, and assembling the evidence package your compliance team will need for an external audit.
Documentation that emerges naturally from well-structured sprint work, commit histories, signed-off acceptance criteria, automated test results, is far easier to compile into an audit package than documentation created after the fact. This is another reason the sprint-level compliance approach saves time overall.
Phase 4: Ongoing Monitoring and Continuous Compliance
Compliance is not a state you maintain after passing an audit. Teams that monitor changes, test internal controls, and push code updates without long freezes preserve market access. Legal trackers, policy engines, and versioned compliance libraries help teams stay current.
Continuous compliance means your monitoring infrastructure flags drift in real time, your quarterly vulnerability scans are automated and acted on, and your incident response runbooks are tested rather than filed. The goal is to reach a state where the next audit is not a sprint-consuming preparation exercise because the evidence is always current.
When Does Your Team Need External Engineering Capacity?
There is a practical limit to what an existing engineering team can absorb alongside a normal product roadmap. Recognizing that limit early is the difference between a smooth compliance delivery and a miss that costs partnerships, market access, or significant fines.
These are the signals that your team needs additional compliance engineering support.
You have a hard deadline inside 90 days and an incomplete gap analysis. The gap between current state and compliance requirement is not yet fully understood, but the external deadline is fixed. This is the scenario where the cost of delay is highest, and where bringing in experienced compliance engineers immediately saves more time than the onboarding costs.
Your core team lacks domain expertise in a specific framework. PCI DSS has QSA-specific requirements. DORA has ICT risk management structures that are unfamiliar to teams that have not built under them before. GDPR's data architecture implications span multiple engineering disciplines. If nobody in your squad has built under the relevant framework before, you are likely to scope incorrectly, which creates rework.
Compliance work is competing with feature velocity. If compliance stories are being deprioritized sprint over sprint to protect feature work, the underlying issue is capacity, not prioritization. Adding dedicated compliance engineering capacity protects both the compliance deadline and the product roadmap.
Pro tip: The most effective model for compliance engineering augmentation is a dedicated team that integrates with your existing squads, rather than a separate compliance pod working independently. Integration means shared backlog visibility, shared sprint ceremonies, and natural knowledge transfer, so your core team builds internal capability as the engagement progresses.
For teams running dedicated engineering squads, adding compliance-specialized engineers to an existing structure is significantly faster than spinning up a new team from scratch. The collaboration patterns are already established; you are adding specialized capacity to an existing operating model.
How Do PCI DSS and GDPR Requirements Overlap?
Many fintech teams manage PCI DSS and GDPR in parallel, and there is meaningful overlap in the technical controls each requires. Understanding where they converge reduces duplicated effort and helps teams build shared infrastructure that satisfies both frameworks simultaneously.
The overlap is substantial. A team that builds the encryption, access control, and logging infrastructure to satisfy PCI DSS v4.0 has already completed most of the technical security work that GDPR requires. The areas where the frameworks diverge are data minimization and user rights (GDPR-specific) and cardholder data environment scoping (PCI DSS-specific).
Common Compliance Engineering Mistakes to Avoid
Even experienced engineering teams repeat the same set of mistakes when working under compliance pressure. These are the ones worth knowing before you start.
Scoping the cardholder data environment too broadly. Every system you include in your PCI DSS scope adds to your assessment burden. Using tokenization and third-party payment vaults to reduce the systems that touch raw cardholder data is not a shortcut. It is sound architecture that makes your compliance program smaller and more maintainable.
Building logging as an afterthought. Audit logging infrastructure is load-bearing. Adding tamper-proof, centralized logging to an existing system is expensive and disruptive. It needs to be in the initial architecture, scoped into early sprints, and validated before you build features that depend on it for compliance evidence.
Treating GDPR consent as a front-end problem. Consent capture is a front-end interaction, but consent management is a data and backend architecture problem. Your system needs to store consent with timestamps, propagate consent preferences to every data processing operation, and support withdrawal, including deletion or portability requests, in a way that is operationally feasible at scale.
Ignoring third-party compliance obligations. Your compliance boundary does not end at your own code. Automation stands as a pillar of fintech best practices, but automated compliance testing, automated security scanning, and automated deployment pipelines must extend to third-party dependency management to catch vulnerabilities in external libraries.
Warning: If a third-party vendor experiences a breach and you cannot notify the supervisory authority within 72 hours because you are waiting for the vendor to complete their investigation, you face regulatory exposure even though the breach was not in your systems. Build SLAs with all processors and sub-processors that require immediate breach notification to you.
Frequently Asked Questions
What is regulatory compliance engineering in fintech?
Regulatory compliance engineering is the practice of designing, building, and maintaining software systems to satisfy the technical requirements of financial regulations such as PCI DSS, GDPR, and DORA. It differs from legal compliance in that it focuses on implementing controls in code, architecture, pipelines, and monitoring systems, not just documenting policies.
What technical requirements does PCI DSS v4.0 impose on engineering teams?
PCI DSS v4.0, mandatory as of March 2025, requires engineering teams to implement network segmentation around cardholder data environments, multi-factor authentication for all administrative access, encryption for card data in transit and at rest, centralized tamper-proof audit logging, and secure software development lifecycle practices including code review, vulnerability scanning, and penetration testing.
How does GDPR affect software architecture in banking and fintech?
GDPR requires engineering teams to build data minimization into data models, implement granular consent management that can be withdrawn, maintain records of all data processing activities, support data subject access and deletion requests at scale, and build breach detection and incident response infrastructure capable of producing a regulatory notification within 72 hours of discovering a breach.
What is the 72-hour GDPR breach notification requirement for engineering teams?
Under Article 33 of GDPR, organizations must notify the relevant supervisory authority within 72 hours of becoming aware of a personal data breach. For engineering teams, this means building real-time monitoring and alerting that detects suspicious access or data exposure, a structured incident response workflow that scopes impact quickly, and documentation processes that produce the information regulators require, all before an incident occurs.
What does DORA require from fintech engineering teams?
DORA, which came into effect in January 2025, requires engineering teams to implement formal ICT risk management frameworks, build incident reporting workflows for major technical incidents, inventory and assess all third-party integrations for risk, manage third-party contracts to include audit rights and exit strategies, and conduct regular resilience testing including threat-led penetration testing for critical systems.
How should engineering teams integrate compliance work into agile sprints?
The most effective approach is shift-left compliance, where compliance impact assessments happen during backlog refinement rather than pre-launch review. User stories should carry compliance acceptance criteria as part of the Definition of Done. Automated compliance checks should run in the CI/CD pipeline, and at least one squad member should hold explicit responsibility for compliance in each team's ceremonies.
When should a fintech engineering team bring in external compliance engineering support?
External compliance engineering support is warranted when a hard regulatory deadline falls inside 90 days and the gap analysis is incomplete, when the team lacks prior experience with the specific framework, or when compliance stories are being consistently deprioritized to protect feature velocity. Adding specialized capacity protects both the compliance deadline and the product roadmap without forcing a tradeoff.
What is the difference between PCI DSS and GDPR technical requirements?
PCI DSS focuses specifically on protecting cardholder data environments through network controls, access management, encryption, and payment-system-specific vulnerability management. GDPR applies more broadly to all personal data, with specific obligations around consent management, data minimization, processing records, and breach notification. The two frameworks share significant overlap in encryption, access control, audit logging, and incident response, allowing teams to build shared infrastructure that satisfies both.
How can engineering teams reduce their PCI DSS compliance scope?
The most effective scope reduction strategy is tokenization. By routing payment processing through a third-party vault or payment gateway that handles raw card data, teams can remove most of their systems from the cardholder data environment. Fewer systems in scope means a smaller assessment surface, lower ongoing maintenance overhead, and reduced exposure to scope-expanding architectural changes.
What are the most common regulatory compliance engineering mistakes in fintech?
The most common mistakes are scoping the cardholder data environment too broadly, building audit logging as an afterthought rather than foundational infrastructure, treating GDPR consent as a front-end problem rather than a data architecture problem, not accounting for third-party vendor compliance obligations, and treating compliance as a pre-launch phase rather than an ongoing operational posture.
Conclusion
Regulatory compliance deadlines do not bend for product roadmaps. The teams that meet them without derailing velocity are not the ones with the most experienced compliance lawyers. They are the ones that have embedded compliance into how they build, from backlog refinement through deployment to monitoring.
The frameworks covered here, PCI DSS, GDPR, and DORA, are demanding. But they are also specific. Every requirement maps to a technical implementation, and every technical implementation can be scoped, estimated, and shipped like any other engineering work. The challenge is doing that work early enough, with enough capacity, and with enough cross-functional alignment so the deadline becomes an event you are ready for, not one you are scrambling to survive.
If your team is looking at a compliance deadline and the gap between current state and required state is wider than your current capacity can absorb, that is a solvable problem. Bringing in experienced fintech compliance engineering support is faster than retrofitting under pressure, and the knowledge transfer from a well-integrated engagement strengthens your team's internal capability for the next deadline.
Meet your regulatory deadlines by working with a software development company that understands both the technical depth and the delivery discipline fintech compliance requires. You can also explore our banking case studies to see how teams have navigated complex compliance builds without derailing their product roadmaps.
