OutSystems Launches AI Agents to Take the Paperwork Out of Bank Loan Applications
OutSystems is taking agentic AI deeper into banking with a new system designed to automate much of the work surrounding consumer loan applications, from collecting and checking documents to verifying customer identities and screening applicants before their files reach a bank’s existing lending platform.
The company has introduced Agentic Loan Applications, its first packaged Agentic Industry Solution for banking, as financial institutions look for ways to move artificial intelligence beyond isolated pilots and into heavily regulated, high-volume operations.
Rather than asking banks to replace their existing loan origination systems, OutSystems has designed the technology to sit on top of current infrastructure and connect AI agents with the bank’s own policies, data, systems and workflows.
That distinction is important. Lending is one of the areas where banks may see substantial potential for automation, but it is also an environment where AI decisions need to be explainable, auditable and subject to clearly defined controls.
OutSystems is betting that banks will be more willing to deploy AI agents if they can automate the work around lending decisions without surrendering control over the decisions themselves.
AI takes on the paperwork before the loan decision
The technology targets some of the most time-consuming stages at the front end of a loan application.
Applicants are guided through a digital journey in which AI agents can collect and verify documents, perform identity checks, run sanctions screening and assemble the information into a completed application.
Once that process is finished, the application can be passed into the bank’s existing loan origination system rather than requiring the institution to rebuild its core lending infrastructure.
The approach tackles a familiar problem in retail banking: customers are often required to complete lengthy forms, submit multiple documents and provide the same information at different stages, while bank employees spend considerable time checking and reconciling that information before an application can progress.
Agentic AI gives OutSystems a way to automate more of those steps while allowing different agents and deterministic workflows to handle specific parts of the process.
Documents and identity checks get their own agents
OutSystems has developed specialized banking agents that illustrate how the model works behind the customer-facing application.
Its Banking Document Intelligence Agent can examine documents submitted with a loan application, checking elements such as document validity and recency, identification expiry dates, inconsistencies between documents, arithmetic discrepancies and unusually large deposits.
A separate Banking Risk & Fraud Assessment Agent can support KYC and AML checks, test consistency across submitted documents and evaluate predefined fraud and credit-risk indicators.
The company makes an important distinction around those capabilities: the agents are designed to support existing banking processes rather than replace underwriting, fraud investigations, regulatory reporting or the institution’s own credit policies.
That leaves banks responsible for how the technology is configured, deployed and governed.
The bigger challenge is controlling the agents
Governance sits at the center of OutSystems’ pitch to banks.
The platform combines AI agents with conventional, deterministic workflows and includes controls around identity, access to data, policies, audit trails and human intervention.
OutSystems says agents are evaluated against dozens of criteria before production deployment, including accuracy, relevance and protection of personal information. Changes to models, prompts or tools can also trigger renewed testing to ensure agents continue operating within defined guardrails.
That becomes particularly important when AI moves from answering customer questions to handling information that contributes to lending decisions.
Banks need to know what information an agent accessed, what it did with that information and where human review is required — particularly when customer identity, financial data, fraud indicators and regulatory checks are involved.
AI without ripping out the core banking system
OutSystems is also addressing another obstacle that has slowed AI adoption across financial institutions: legacy technology.
Instead of requiring banks to replace existing core platforms, Agentic Loan Applications is intended to operate as an orchestration layer around them, combining mobile and web experiences, data models, workflows and specialized agents while connecting back to existing lending systems.
The company says the solution runs on AWS infrastructure, with Amazon Bedrock used for model orchestration and for routing tasks to AI models based on performance and cost requirements.
Individual agents and components can also be adopted separately, giving banks the option to begin with a narrower use case before deploying the wider lending solution.
OutSystems already works with financial institutions including KeyBank, Paragon Bank and Axos Bank, while other lenders have been experimenting with its agentic technology in specific lending processes.
Grihum Housing Finance, for example, has used OutSystems Agent Workbench to build an AI agent that reviews property reports against credit policies during mortgage origination and flags technical deviations for underwriting teams.
The launch of Agentic Loan Applications takes that idea considerably further.
Instead of deploying AI around one isolated task, OutSystems is attempting to connect agents across the loan application journey while keeping conventional workflows, human oversight and existing banking systems in the loop.
For banks, that may ultimately be the more realistic path toward agentic AI: not handing the lending decision to an autonomous machine, but allowing AI to remove much of the repetitive work that happens before humans and existing systems make it.