Accelerating Application Modernization in Banking: Overcoming Legacy Barriers with GenAI

In the rapidly evolving world of financial services, banks face mounting pressure to modernize legacy applications, enhance agility, and deliver the seamless digital experiences customers now expect. Yet, entrenched legacy systems, regulatory complexity, and siloed data continue to impede progress. Generative AI (GenAI) is emerging as a transformative force, offering banks a practical path to overcome these barriers and accelerate their journey to a modern, agile, and secure technology landscape.

The Legacy Challenge in Banking

Legacy applications are a double-edged sword for banks. While they underpin critical operations and compliance, they also:

• Deliver poor user experiences due to outdated interfaces and sluggish performance.
• Drive up maintenance costs as specialized skills become scarce and expensive.
• Create integration headaches by lacking modern APIs, making it difficult to connect with new digital services.
• Expose banks to security and compliance risks as unpatched vulnerabilities and outdated controls become targets for cyber threats.
• Slow innovation by consuming resources that could otherwise be invested in new products and services.

According to Publicis Sapient’s Global Banking Benchmark Study, regulatory challenges, lack of operational agility, and legacy technology are the top barriers to digital transformation in banking. Nearly a third of banking executives cite budget constraints as a major obstacle, while only 11% of banks are considered digital Transformation Leaders—down from 22% just two years ago. The need for a new approach is clear.

GenAI: A Catalyst for Modernization

Generative AI is redefining what’s possible in application modernization. Unlike traditional automation, GenAI leverages large language models (LLMs) to understand, refactor, and generate code, automate testing, and create documentation—all with human-like reasoning and adaptability. For banks, this means:

• Automated code transformation: GenAI can analyze legacy codebases, suggest improvements, and generate modern code snippets, dramatically reducing manual effort and error rates.
• Accelerated testing and quality engineering: AI-driven tools generate comprehensive test cases, automate unit and regression testing, and identify defects early, ensuring higher quality and compliance.
• Continuous documentation: GenAI can produce and update technical documentation in real time, supporting knowledge transfer and regulatory audits.
• Security and compliance by design: AI models can proactively detect vulnerabilities, enforce secure coding practices, and automate compliance checks, reducing risk and supporting regulatory requirements.

Banks that embrace GenAI are seeing measurable results: modernization costs reduced by over 50%, defect rates halved, and migration speeds increased by up to 70%. These gains are not theoretical—they are being realized in real-world banking engagements.

Addressing Sector-Specific Barriers

Regulatory Compliance

Banks operate in one of the most regulated environments. GenAI, when deployed with robust governance, can automate compliance validation, generate audit trails, and ensure that modernization efforts align with evolving regulatory standards. Leading banks are investing in custom AI tools, rather than relying solely on third-party solutions, to maintain control over data privacy and compliance.

Data Silos and Integration

Siloed data is a persistent challenge. GenAI-powered modernization platforms can analyze and map data flows across legacy and modern systems, facilitating seamless integration and enabling a 360° view of the customer. This is critical for delivering personalized experiences and meeting regulatory expectations for data transparency.

Security and Risk Management

With cyber threats on the rise, security cannot be an afterthought. GenAI tools embedded in the software development lifecycle (SDLC) can identify vulnerabilities, recommend secure coding patterns, and automate remediation. Banks are also leveraging AI to monitor for anomalous behavior and ensure that new applications meet stringent security standards from day one.

The Power of Human-AI Collaboration

While GenAI accelerates modernization, human expertise remains essential. The most successful banks blend AI-driven automation with skilled developers, architects, and compliance specialists who provide domain context, validate AI outputs, and ensure alignment with business goals. This human-in-the-loop approach is especially important in regulated environments, where explainability and accountability are paramount.

Real-World Impact: Banking Modernization in Action

Publicis Sapient’s work with leading banks demonstrates the tangible benefits of GenAI-powered modernization:

• A major global bank partnered with Publicis Sapient and Google Cloud to modernize its infrastructure and software development lifecycle, targeting up to 40% efficiency gains while meeting complex regulatory requirements.
• A leading benefits provider used private LLMs to deconstruct legacy mainframe applications, achieving 3x faster migration, improved traceability, and easier maintenance in a modern tech stack.
• Deutsche Bank built a core AI and machine learning platform to augment code development, support compliance, and scale GenAI solutions across the business, laying the foundation for future innovation.

Enabling Modernization with the Right Platforms

Publicis Sapient’s proprietary platforms, such as Sapient Slingshot and Bodhi, are designed to accelerate every stage of the modernization journey:

• Sapient Slingshot automates code migration, documentation, and testing, leveraging an enterprise code library and agentic AI to deliver high-impact solutions.
• Bodhi provides a secure, cloud-agnostic environment for deploying and scaling AI solutions, with built-in data security and compliance features.
• Google Cloud’s Vertex AI and Gemini Code Assist offer scalable, secure AI infrastructure, enabling banks to build, test, and deploy modern applications with confidence.

Best Practices for Banks Embarking on GenAI Modernization

1. Start with a clear business case: Align modernization efforts with strategic goals—whether it’s improving customer experience, reducing costs, or enabling new products.
2. Invest in data readiness: Break down silos and ensure data quality to maximize the value of AI-driven modernization.
3. Adopt a human-in-the-loop model: Combine GenAI automation with expert oversight to ensure quality, compliance, and explainability.
4. Prioritize security and compliance: Embed AI-driven security and regulatory checks throughout the SDLC.
5. Measure and iterate: Track outcomes, learn from each phase, and continuously optimize your modernization approach.

The Road Ahead: From Legacy to Leadership

The next wave of digital transformation in banking will be defined by those who can modernize at speed, scale, and with confidence. GenAI is not a silver bullet, but when combined with the right strategy, platforms, and expertise, it is a powerful accelerator. Banks that move decisively—investing in both technology and talent—will be best positioned to deliver the agility, security, and customer-centricity that define the future of financial services.

Ready to accelerate your bank’s modernization journey? Publicis Sapient’s deep banking expertise, proven AI platforms, and strategic partnerships with Google Cloud and AWS make us the partner of choice for banks seeking to overcome legacy barriers and lead in the GenAI era.