What AI Agents Mean for Core Banking Modernization
AI agents in banking are autonomous or semi-autonomous software systems that plan, write, and execute tasks such as code changes or financial analysis, enabling faster core banking modernization by automating repetitive work, coordinating across complex systems, and delivering insights or features with minimal human intervention. In core infrastructure, these agents act as tireless teammates that work inside existing development and operations pipelines. They reduce manual coding, testing, and reporting effort, which historically slowed financial software upgrades. For banks under pressure to compress release cycles, AI agents banking strategies promise shorter time-to-market for new products and security updates. The combination of autonomous software engineer agents and domain-focused assistants is starting to redraw digital transformation timelines, shifting modernization from multi-year programs toward more iterative, continuous change that better matches customer expectations for always-on, flexible digital services.
Fiserv and Devin: An Autonomous Software Engineer for the Core
Fiserv’s partnership with Cognition’s Devin AI shows how autonomous software engineer agents are moving from concept to production in banking infrastructure. Devin can autonomously plan, write, test, and deploy code across complex codebases, working inside Fiserv’s core platform and other engineering initiatives. According to Fiserv Co‑President Dhivya Suryadevara, “With Devin, we can accelerate modernization of the platforms our clients run their business on, ship new capabilities faster, and free our teams to focus on the work that matters most.” For financial institutions running on Fiserv, this should mean quicker delivery of new features, tighter security improvements, and more frequent core banking modernization releases. Rather than replacing development teams, Devin extends engineering capacity by taking on repetitive tasks, so human engineers can focus on architecture, quality reviews, and resilience, which remain critical in regulated financial environments.
Shorter Development Cycles and Faster Financial Software Upgrades
Core modernization projects have long been expensive, resource-heavy, and slow, often stretching across many release cycles before meaningful benefits reach customers. AI agents banking deployments promise to change that rhythm. By automating test creation, regression checks, and routine code changes, tools like Devin can accelerate financial software upgrades while preserving quality controls. Fiserv expects shorter release cycles and more consistent rollouts of integrations and security updates for thousands of institutional clients. Cognition Co‑Founder Russell Kaplan noted that Fiserv’s scale and ambitious engineering roadmap make it “exactly the kind of organization where Devin creates compounding value.” For banks, the business impact is faster response to market shifts, quicker launch of digital products, and a move toward continuous modernization instead of disruptive, infrequent core replacements that strain budgets and technology teams.
Efimis and Eve: Parallel Progress in Self‑Serve Financial Insights
While Devin transforms engineering workflows, Efimis displays a parallel trend on the insight side with Eve, its embedded in‑app AI assistant for legal finance. Eve sits inside the Efimis financial management platform, allowing law firms to self‑serve financial information and operational insights through natural language queries instead of manual reporting. Users can ask about fees and performance, debtors, matter balance activity, or wider financial analysis and receive instant, actionable answers. This reduces time spent compiling reports or answering internal queries, and frees teams to focus on higher-value advisory work. Product Manager Tom Spedding explains that the focus of AI in Efimis is on “delivering meaningful and practical functionality that improves the day-to-day experience for firms.” Eve’s planned expansions, including email-based time recording and bill drafting, show how AI agents can streamline back-office processes across the broader financial ecosystem.
What AI Agents Mean for Banking Timelines and Talent
Together, Devin and Eve show how AI agents can change both the pace and shape of financial transformation. On the infrastructure side, an autonomous software engineer can compress development cycles for core banking modernization, reducing time-to-market for upgrades and giving providers like Fiserv a competitive edge with faster, more flexible platforms. On the insight side, domain assistants like Eve turn complex financial data into self-serve answers, cutting the lag between question and decision. For banks and firms, this points toward smaller, more continuous upgrade steps instead of infrequent large migrations. It also reshapes talent strategies: engineers and finance teams move away from routine coding or reporting toward design, oversight, and exception handling. As these agents improve, governance, security, and clear role boundaries will decide which institutions translate speed into reliable, trusted services.