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Agentic AI is moving out of the pilot phase in banking. OutSystems announced its first end-to-end agentic solution for Loan Origination, with ready-to-use agents for document processing and policy verification, connections to core systems like Jack Henry and Fiserv, and a fully auditable workflow. According to OutSystems, Axos Bank, a customer for several years, already reports a 60% productivity gain in core banking workflows using similar agentic capabilities.
Until recently, agentic AI in banking lived mostly in proofs of concept. That is changing: banks are starting to put autonomous agents into production for regulated tasks such as KYC, fraud detection and document processing, precisely the areas where mistakes are costly and human oversight isn't optional.
OutSystems' new Banking Solution isn't a demo prototype. It comes with agents ready to process documentation and check credit policies, connects to core systems already installed at most banks, and keeps an auditable record of every decision, a non-negotiable requirement at any regulated institution. The bank's team is free to customize only what truly differentiates its business, instead of building intake agents and compliance workflows from scratch.
This confirms something we already see with financial services clients: the barrier to agentic AI adoption in banking is rarely the technology itself, it's governance. A bank can't adopt an agent that "usually" works well; it needs an agent whose decisions it can explain to a regulator. That's why solutions built on a platform with native auditability, data control and traceability, like OutSystems, move faster than generic AI tools bolted onto legacy systems.
For financial institutions in Portugal, the realistic path isn't to "implement agentic AI" as a standalone project. It's to pick a well-defined, auditable use case first, such as loan origination or document processing, and expand from measured results. This is the kind of support, from strategy to implementation.
Is agentic AI already in production in banking, or is it still a pilot? It's already in production for specific use cases. KYC, fraud detection and loan origination are the most advanced, with banks like Axos Bank reporting measurable productivity gains (60% in some core workflows, according to OutSystems).
What guarantees should a financial institution require before adopting AI agents? At minimum: an auditable workflow, decision traceability, control over where data is processed, and native integration with existing core systems, not just the ability to generate answers.
Exploring agentic AI for your bank? Talk to our team or see how we approach Financial Services.
Sources - OutSystems, "How OutSystems is evolving to give enterprises leverage and digital sovereignty in the AI era" - OutSystems, "Axos Bank pioneers agentic AI strategy with OutSystems Agent Workbench" - OutSystems Forge, Banking and Financial Services Agent Kit