Financial institutions today are under pressure to deliver software solutions faster. But they can’t afford to let security or compliance slip. Unfortunately, traditional methods of managing security are no longer enough, especially when trading algorithms and sensitive data are at stake. DevSecOps (“development, security, and operations”) is the logical next step.
“DevSecOps builds on DevOps with security testing and compliance checks [throughout the software development cycle], without reducing agility or speed,” says Gartner. “This is desirable in highly regulated industries that are under pressure to mitigate risk as they seek the value of DevOps.”
This guide shows how AI-driven DevSecOps can help investment firms fix security weaknesses quickly. This allows them to release new features without falling behind on regulations. By using smart security automation at every step of the development process, financial organizations can protect their most valuable assets and stay ahead of strict compliance demands.
The Financial Services DevSecOps Imperative
Across all industries, the financial services sector has the second-highest average cost per breach: The average cost in 2023 reached $5.9 million per incident, IBM reports, and increased by 3% in 2024. Many of these attacks target vulnerabilities during software development cycles. Investment firms may struggle to protect both client and proprietary data while delivering on clients’ software needs. Maintaining compliance in their heavily-regulated industry while developing new software solutions is also a challenge.
Traditional security models that rely on end-of-cycle reviews create bottlenecks, causing more modern software deployment cycles to take months instead of days. Meanwhile, threats have become more sophisticated, targeting related vulnerabilities.
Now, AI-powered attacks are becoming more common. For example, bad actors “can use advanced AI-based tools… to discover vulnerabilities and identify weaknesses in an institution’s IT network and application security measures,” the U.S. Department of the Treasury describes. The integration of DevSecOps practices has become essential for maintaining operational security in this environment.
Regulatory and Compliance Pressures
Financial institutions operate under stringent regulatory frameworks, including SEC, FINRA, SOX, and PCI-DSS requirements that demand continuous compliance monitoring. The challenge is compounded by the global nature of many investment firms, which must navigate multiple jurisdictional requirements simultaneously. Traditional compliance approaches that rely on periodic audits and manual reviews cannot keep pace with the velocity of modern software development.
Investment firms must demonstrate not only that they meet current requirements but also that their systems can adapt to future regulatory changes without significant architectural overhauls. This means compliance must be integrated directly into the software development process rather than regarded as a separate activity.
The Speed vs. Security Dilemma
Modern investment firms need deployment capabilities that can respond to market opportunities within hours, not weeks. High-frequency trading algorithms, risk management systems, and client-facing applications must be updated rapidly to maintain competitive advantages. However, the traditional approach of adding security reviews at the end of the development cycle creates delays that can cost millions in missed opportunities. This approach doesn’t naturally evolve with changes to development cycles, either.
The solution lies in shifting security “left” into the development process, embedding automated security checks throughout a continuous integration and continuous delivery (CI/CD) pipeline. This approach allows for ongoing security validation without slowing down development, allowing firms to deploy secure code as fast as business demands. In one study, organizations implementing DevSecOps practices “reduced model risk incidents and decreased model deployment time substantially.”
The AI Advantage in DevSecOps
AI-powered security tools can analyze code repositories, infrastructure configurations, and deployment patterns in real-time, identifying potential vulnerabilities before they reach production environments. Machine learning algorithms trained on financial services-specific threat patterns can detect anomalies that traditional rule-based systems miss, reducing false positives as well. This precision enables security teams to focus on genuine threats rather than investigating benign activities.
Automated vulnerability scanning powered by AI can process millions of lines of code in minutes, identifying security flaws, compliance violations, and potential attack vectors. These systems continuously learn from new threat intelligence, ensuring that security measures evolve alongside the threat landscape.
Predictive Risk Assessment
Advanced analytics platforms can predict security risks by analyzing patterns in code commits, infrastructure changes, and deployment frequency. This predictive capability supports proactive risk mitigation, allowing security teams to address potential issues before they manifest as actual vulnerabilities. Machine learning models trained on historical incident data can even forecast the likelihood of security events.
Meanwhile, behavioral analytics systems monitor application and user behavior patterns, automatically flagging deviations that may indicate security breaches or compliance violations. These systems are particularly valuable for protecting trading algorithms and client data, as they can detect unauthorized access attempts or data exfiltration in real-time. The integration of AI-powered monitoring reduces mean time to detection from hours to minutes.
Automated Compliance Monitoring
Critically, AI-driven compliance systems can automatically verify adherence to regulatory requirements throughout the development lifecycle. Natural language processing algorithms can interpret regulatory documents and translate requirements into automated compliance checks, ensuring that new regulations are quickly incorporated into existing processes. This capability is essential for investment firms operating across multiple jurisdictions with varying regulatory frameworks.
Additionally, intelligent audit trail generation can ensure all development activities are properly documented and traceable, meeting regulatory requirements for transparency and accountability. These systems can also provide early warning of potential compliance violations, enabling corrective action before regulatory issues arise.
Five Pillars for AI-Driven DevSecOps in Financial Applications
Adopting an AI-driven DevSecOps approach calls for new principles in financial application development.
As Boston Consulting Group notes, Firms must “consider various approaches to transform legacy core systems to modern technology architecture-based core systems.”
Here we’ve identified five steps—“pillars” in successful DevSecOps cycles—for you to consider as you move forward:
- Integrate security from the start. Build security directly into every step of your development process. Use automated security gates that assess risk and apply controls before code moves forward. Adjust security policies based on the sensitivity of your applications—give your trading systems extra protection, for example, and streamline for less critical tools. Make risk-based decisions so low-risk changes move quickly, while you closely scrutinize high-impact changes.
- Automate compliance enforcement. Enforce regulatory requirements automatically, in real time, for every code change. Use policy-as-code to turn complex regulations into rules your CI/CD pipeline can check and enforce. Generate audit trails automatically, so you’re always ready for regulatory review—no manual work required.
- Adopt risk-based development workflows. Use dynamic risk assessment tools to evaluate the security impact of every code change. Route high-risk changes through enhanced reviews and fast-track low-risk updates. Prioritize your security team’s efforts on the most critical vulnerabilities and adapt controls to fit each application’s needs.
- Continuously monitor and respond. Set up real-time monitoring for all applications and infrastructure. Use behavioral analytics to spot unusual activity as soon as it happens. Automate your incident response so threats are contained within minutes, not hours.
- Continuously learn and improve. Use machine learning to analyze what’s working and what’s not in your security controls. Build feedback loops so lessons from incidents are immediately used to strengthen your defenses. Apply predictive analytics to stay ahead of new threats—don’t just react, anticipate.
Technology Stack and Architecture Considerations
Deciding the right technology stack will be essential to successful DevSecOps, and will differ between firms. Consider these options as you build out you own.
- Choose your cloud-native security infrastructure. Build your DevSecOps program on a cloud-native foundation using microservices and containers. For example, you can use Kubernetes for orchestration, add a service mesh for secure microservice communication and real-time monitoring, and set up API gateways to centralize security controls and manage access. This approach ensures your systems can scale quickly and securely to handle high-volume financial operations.
- Integrate AI and machine learning for security. Deploy AI and machine learning for real-time threat detection, behavioral analysis, and predictive security. Use natural language processing to automate log and compliance reviews, and train your models on financial data for better accuracy. Leverage edge computing for fast, local processing and federated learning to share threat intelligence securely—always back your AI with strong governance for transparency and control.
- Ensure seamless integration with financial systems. Connect your DevSecOps platform directly to trading, risk, and compliance systems for seamless, real-time monitoring. Use event-driven architectures to instantly share and respond to security events, integrate alternative data sources for richer risk insights, and use blockchain for tamper-proof audit trails. Keep business unit data isolated to reduce risk and prevent cross-contamination.
Compliance and Regulatory Automation
As discussed, you must keep up with changing regulations while maintaining speed and security. Use these strategies to automate compliance and stay ahead of regulatory demands.
- Automate regulatory mapping. Deploy AI-powered tools to automatically map regulatory requirements to your controls and processes, ensuring nothing is missed, even across multiple jurisdictions. Use natural language processing to turn complex regulations into machine-executable policies, and set up systems that detect regulatory changes and update your compliance processes instantly. Prioritize updates with intelligent impact assessment, and rely on automated compliance testing to make sure every change stays within the rules.
- Enable real-time compliance monitoring. Implement continuous compliance monitoring throughout your development and deployment pipeline. Enforce policies in real time so non-compliant code never reaches production, and generate audit-ready documentation automatically. Use intelligent audit trails to track every action, and predictive analytics to spot potential violations before they become problems, cutting compliance costs and improving audit outcomes.
- Simplify cross-border regulatory coordination. Use AI to identify and resolve conflicts between overlapping or conflicting regulations in different countries. Automate data localization to keep sensitive information in the right geographic regions, and standardize your approach with international compliance frameworks. Intelligent data classification ensures the right controls are always applied, helping you stay efficient and compliant as you grow globally.
DevSecOps Maturity Assessment Framework
As you take your first steps with DevSecOps, gauging your maturity level as you go will help you determine the extent to which you will apply your learnings at each stage of the process.
Maturity Level 1: Initial/Ad-hoc
If your security is mostly manual, inconsistent, and added late in the development cycle, you’re at the starting line. Move quickly to automate basic vulnerability scanning, set up version control, and standardize your security procedures—as suggested, focus first on your most critical applications and aim for consistent security baselines.
Maturity Level 2: Managed
At this stage, you have some automation and defined processes, and your security and development teams are starting to collaborate. Expand automated testing, add security gates to your CI/CD pipelines, and set clear security metrics—standardize tools and processes across all teams to build a solid foundation.
Maturity Level 3: Defined
Here, security is fully integrated and standardized across the organization, with proactive measures and data-driven improvements. Deploy advanced threat detection, automate compliance with policy-as-code, and implement continuous monitoring—optimize and fine-tune processes as you go.
Maturity Level 4: Optimized
At this top level, AI, predictive analytics, and continuous learning power your security, with minimal manual intervention. Focus on AI-driven threat detection, automated incident response, and self-improving security systems to stay ahead of threats and set the industry standard.
You might also consider the popular, industry-agnostic OWASP DevSecOps Maturity Model as an alternative reference.
Take Steps Now for DevSecOps Success
The future of financial services depends on the ability to innovate rapidly while maintaining absolute security and compliance. Organizations that embrace AI-driven DevSecOps today will establish competitive advantages that compound over time.
Don’t be discouraged if many of the DevSecOps principles and techniques are out of reach for your firm today. The framework and implementation guidance provided here offer investment firms the tools necessary to achieve this critical balance between security and speed well into the future.
Start Your Journey with Option One Technologies
Option One Technologies can guide cloud-based and cybersecurity solutions in your AI-driven DevSecOps journey. Learn more and contact one of our experts today.
