Evaluate AI with confidence

AI for IT Leaders

A practical guide for financial institutions

Understand AI agents. Assess vendor controls. Plan for responsible adoption.

Evaluating AI for a financial institution requires more than understanding what a model can generate.

IT leaders need clear answers about data access, permitted actions, human oversight, audit documentation, and the division of responsibility between the vendor and the institution. They also need to understand how value and performance will be measured after deployment, including capacity created, time to fund a loan, findings and outcomes, agent health, and more. This page is designed to help IT teams and other stakeholders work through that evaluation.

Move from AI interest to informed approval

Understand the technology

Know the difference between AI assistants, AI agents, and AI-powered solutions, and whether each fits a defined business problem or workflow.

Maintain control

Define what AI can access, what it can do, and which actions require approval or human review.

Ensure oversight

Make AI activity explainable, documented, monitored, and reviewable over time.

Plan for operating needs

Evaluate security, integration, implementation, support, and ongoing operating responsibilities before approving a solution.

Before approving the use of AI products or capabilities at your institution, ask for clear information on:

Data access, ownership, permitted use, retention, and deletion.
Model providers, integrations, and third-party dependencies.
Security, authentication, access controls, and auditability.
Pricing, licensing, implementation costs, support, ongoing maintenance, and how costs scale with use and integrations.

Human review, escalation, rollback, and reduced-autonomy processes.
Testing, monitoring, change control, and incident response.
Deployment, hosting, integration, implementation, support, and ongoing operating responsibilities.
Contractual responsibility, liability, and assurance documentation.

AI capabilities are not all the same

Abrigo’s AI portfolio includes various types of capabilities. Understanding these matters before any evaluation begins.

AI Agents

Reduce manual effort and create capacity for higher-value lending work by interpreting workflow context and coordinating multi-step tasks within institution-configured policies, permissions, and guardrails. Examples include gathering information, validating it, managing follow-ups, and routing exceptions for human review.
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AI Assistants

Complete focused tasks, such as extracting data, validating documents, generating credit narratives, analyzing credit risk and generating review narratives, or prioritizing AML alerts.
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AI-powered solutions

Incorporate AI directly into broader banking software to support activities such as fraud detection, allowance reporting, loan review, and banking intelligence.
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How Abrigo and your institution share responsibility

Governed AI depends on both platform controls and institutional oversight. Understand the details of both during any evaluation.

Abrigo operates

Abrigo provides and operates the platform control framework, including:

Platform/infrastructure

Orchestration

Governance framework

Guardrails

Tool access

Evaluations

Logging/observability

LLM model/provider integrations

Security controls around the service

Agent performance monitoring and recommendations

Your institution controls

The institution configures, approves, and monitors how AI is used within its risk appetite and policies, including:

Who can use it

What data/actions are authorized

Policies/instructions

Autonomy levels

Required human review

Approval/escalation

Whether/when agents are enabled

Why agentic AI requires a different assessment

Agentic AI requires evaluating more than what a model can generate. Look for evidence that an agent can interpret workflow context, complete multiple steps, validate information and documentation, and execute or route permitted actions. Below are common questions IT leaders are asking when assessing Abrigo's agentic platform.

What can the AI access?

Agents should operate within institution, user, and workflow permissions, using only the information required for the task. Abrigo APX operates within Abrigo lending workflows using institution-authorized data, source documents, workflow context, configured policies, and approved integrations. Customer data is not used to train the underlying AI models Abrigo uses.

What can the AI do?

Institutions should understand which actions are permitted, which require approval, and which are blocked. With Abrigo APX, agent behavior can be configured by workflow, action type, role, loan type, confidence threshold, and risk level.

What happens when the AI is uncertain?

Missing data, unsupported evidence, low confidence, permission issues, invalid configuration, or unavailable systems can trigger a controlled stop, escalation, or review. Actions can be deferred for human review or blocked when requirements are not met.

Can we explain what happened?

AI activity should be traceable to the information, policies, controls, and reviewers involved. Abrigo APX is designed to capture the context of agent actions, including supporting information, policy context, confidence information, governance decisions, reviewer activity, and final outcomes.

How is the AI secured and monitored?

Abrigo operates its underlying platform within an information security and compliance framework that includes access management, change management, system monitoring, vulnerability management, incident response, and audit logging. Abrigo maintains independent third-party assurance programs, including SOC 1 and SOC 2 examinations.

How does Abrigo APX fit into our existing technology environment?

Abrigo APX operates within Abrigo lending workflows, using institution-authorized data, configured policies, approved integrations, and existing permissions.

How does Abrigo APX help institutions measure performance and value?

The Abrigo APX Performance Center gives executives and administrators visibility into agentic operations, value, and reliability. It brings together a range of metrics and information, including estimated capacity created, Abrigo APX-enabled time to fund a loan, findings surfaced, and agent health and improvement, including identified issues and smart suggestions for lower-scoring agents. These insights help institutions support a fact-based view of ROI, focus human attention where it matters most, and improve performance over time.

How does Abrigo APX compare with building and operating a lending solution around a general-purpose LLM?

Building and operating a lending solution around a general-purpose LLM involves more than model access. It requires addressing workflow integration, data and permission boundaries, policies, human review, auditability, testing, monitoring, support, and ongoing maintenance. The cost, timeline, and operating effort of building around a general-purpose LLM depend on the scope and the institution’s existing capabilities, but the work can be lengthy and complex.

Abrigo APX helps simplify adoption and operation by bringing these capabilities into Abrigo lending workflows, operating within institution-configured policies and permissions while supporting human review, evidence presentation, audit logging, testing, and escalation paths. Abrigo operates the platform, while the institution configures, approves, and monitors its use.

Define a practical path to AI adoption at your institution

AI adoption does not need to begin with an institution-wide transformation. A practical approach is to identify a high-impact workflow, define the required controls, establish human oversight, and measure performance over time using metrics such as estimated capacity created, APX-enabled time to fund, findings surfaced, and agent health and improvement. Abrigo can help your institution evaluate where AI agents, assistants, and AI-powered solutions fit—and what is required to support responsible production use.

Talk with Abrigo