FORUM Credit Union achieves 70% increase in loan processing capacity with agentic AI document automation

FORUM Credit Union's back-office operations were increasingly strained by manual document handling across loan applications spanning multiple formats — pay stubs, tax returns, bank statements, and title documents. Underwriters spent the majority of their time on repetitive classification and data extraction tasks rather than credit analysis, creating a bottleneck that constrained how many members the institution could serve. For a mid-market credit union competing against larger banks with greater operational resources, this manual throughput ceiling directly limited loan volume and member experience without a path to scale headcount proportionally.

FORUM CU deployed Multimodal's AgentFlow platform to automate end-to-end document workflows in its lending operation. AgentFlow uses agentic AI to handle multi-step processes autonomously: ingesting documents in various formats, classifying them, extracting structured data, and routing files through underwriting decision steps — escalating exceptions for human review rather than requiring staff intervention at every stage. The deployment targeted the highest-friction segment of the loan pipeline first, integrating with existing back-office systems to avoid wholesale infrastructure replacement. COO Andy Mattingly positioned the rollout internally as an amplifier for staff, not a displacement, which was central to securing team buy-in before go-live.

Loan processing capacity increased by 70% following the AgentFlow deployment — the primary headline metric. Turnaround times fell meaningfully, allowing FORUM CU to serve more members within the same staffing footprint. Key outcomes include:

• 70% increase in loan processing capacity without adding underwriting headcount
• Faster underwriting decisions, reducing member wait times on loan applications
• Staff redeployed from manual data entry toward higher-value, member-facing work
• Exception-based review model reduced friction while maintaining human oversight on edge cases

The results reflect a structural change in throughput rather than incremental efficiency gains.

• Agentic AI delivers measurable ROI in lending operations by removing the document-handling bottleneck, not by replacing underwriters — capacity gains come from eliminating non-judgment work.
• Staff communication is a prerequisite, not an afterthought: FORUM CU's COO framed AI as a back-office efficiency tool that releases time for member value, which drove adoption rather than resistance.
• Starting with document-heavy, rules-bound workflows (classification, extraction, routing) produces fast, verifiable wins before expanding to more complex decisioning steps.
• Exception-based escalation — where AI handles standard cases and flags outliers — is the deployment pattern that balances automation scale with regulatory and credit-quality oversight.