Banks, insurance companies, airlines, and other legacy industries are sitting on millions—sometimes billions—of lines of code written decades ago. These outdated systems are expensive to maintain, difficult to update, and risky to touch. Yet modernizing them has long been considered too complex and costly.
Enter AI-powered software modernization.
Recent advances in AI, particularly in code understanding, refactoring, and automated transformation, are making it not only feasible but practical to bring legacy software into the modern age. For banks and other heavily regulated industries, this presents a game-changing opportunity to reduce technical debt, enhance security, and dramatically cut costs.
The High Cost of Legacy Software in Banking
Legacy systems remain deeply embedded in core banking functions—from transaction processing to customer data management. But maintaining these systems is both expensive and risky:
- Up to 75% of IT budgets in banks are spent on maintaining legacy systems
- Developer productivity suffers, as few engineers are fluent in outdated languages like COBOL
- Security risks increase with aging, unpatched infrastructure
- Innovation slows, as old systems are hard to integrate with modern APIs and platforms
Modernizing these systems manually is time-consuming and prone to error. But with the help of AI, banks can now accelerate this transition at a fraction of the traditional cost.
How AI Is Powering Software Modernization
AI models trained on millions of codebases can now understand, refactor, and rewrite legacy code in modern languages. This includes:
- Code translation (e.g., COBOL to Java)
- Code pattern identification and standardization
- Automated testing and validation to ensure safe migration
- Risk-based prioritization of what code to modernize first
- End-to-end orchestration of modernization workflows
Instead of taking years and massive consulting teams to modernize a monolithic app, AI-powered solutions can assist developers in performing this work in weeks or months.
Case Study #1: Mechanical Orchard
Mechanical Orchard specializes in modernizing legacy applications using a unique blend of AI automation and expert engineering. They work with industries like finance and government to migrate mainframe systems to cloud-native architectures.
What they do:
- Automatically assess and map legacy systems
- Use AI to rewrite legacy code in modern languages like Java or Go
- Rebuild systems in microservices or modular cloud-native formats
- Offer long-term support and integration with CI/CD pipelines
Why it matters for banks:
- Drastically reduces maintenance costs
- Enables faster feature delivery and integration
- Improves developer experience and hiring (modern stacks attract talent)
- Enhances resilience and scalability with cloud-native design
Case Study #2: Moderne.AI
Moderne.AI focuses on large-scale code refactoring using automation. Its platform analyzes massive codebases to find and apply changes across thousands of repositories—at scale, and without breaking things.
What they do:
- Detect anti-patterns, security vulnerabilities, and outdated libraries
- Apply automatic code transformations safely and repeatedly
- Integrate with GitHub, GitLab, and CI tools for continuous upgrades
- Help teams migrate frameworks (e.g., Spring Boot upgrades)
Why it matters for financial services:
- Automates compliance-related code changes
- Keeps code up to date without manual effort
- Reduces bugs, security holes, and technical debt
- Saves developer time and frees up resources for innovation
Real Impact: Cost Savings & Risk Reduction
For large enterprises like banks, the impact of using AI for software modernization can be massive:
- 50–70% reduction in legacy maintenance costs
- Faster time to market for new digital products
- Improved security posture through up-to-date code and infrastructure
- Enhanced operational resilience, especially when moving from mainframes to cloud-native systems
Instead of spending millions every year maintaining brittle, outdated code, banks can reinvest that capital into innovation, customer experience, and competitive advantage.
Final Thoughts
AI is not just changing how we build software—it’s changing how we modernize it. For legacy industries like banking, AI-powered modernization platforms like Mechanical Orchard and Moderne.AI offer a path forward that’s faster, safer, and more cost-effective than ever before.
Organizations that embrace these tools will gain a significant edge in agility, security, and innovation.
To discover more trusted AI platforms for software development and enterprise modernization, visit TrustedBy.ai.