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Inference Wire

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Financial Services·AI Engineers On Demand·12 weeks

AI-Driven Loan Approval Transformation

Replacing 5-day loan reviews with instant AI decisions

A mid-market lending firm processed 800+ loan applications every month, each one taking 5 business days to review by hand. We built AI agents and an automated underwriting pipeline that scores, validates, and routes applications in under 90 seconds.

Under 90 Seconds

Approval Processing Time

7 in 8 Applications

Automated Decision Rate

25+ Per Week

Analyst Hours Recovered

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Responsive UI mockup of the LoanIQ AI loan origination dashboard on laptop and mobile screens, a fintech SaaS design case study by Hexaa.
“Delivered ahead of schedule and the system paid for itself within months.”
JF

Jane Fraser

Client Lead, AI-Driven Loan Approval Transformation

Before

5-day manual review cycles, fragmented data across legacy systems, no senior technical leadership

After

90-second automated approvals, unified real-time analytics layer, embedded fractional CTO driving strategy

Narrative

The full story.

The Challenge

The client's underwriting team reviewed every loan application manually, averaging 5 business days per decision across 800+ monthly submissions. On top of that, their senior technical leader had recently left, which stalled an in-progress team migration, opened compliance gaps, and exposed a data infrastructure that could not handle the volume.

What We Built

We embedded a fractional CTO who built the operational roadmap and directed the buildout of AI agents that evaluate creditworthiness using behavioral patterns, income signals, and repayment history. One agent consolidates fragmented data into a unified analytics layer, a second runs risk scoring models against each application, and a third routes edge cases to human reviewers while auto-approving qualified borrowers. End-to-end processing now completes in under 90 seconds per application.

Results

7 out of every 8 loan applications now receive a fully automated decision without a human touching them. Processing time dropped from 5 days to under 90 seconds for standard approvals. Compliance escalations fell by more than half, freeing up 25+ analyst hours every week. The engagement paid for itself within 3 months through recovered loan volume that the firm had been losing to applicant drop-off during long wait times.

Story gallery

Project snapshots.

Technical proof

How it was built.

Implementation details and the stack behind the delivery.

Implementation highlights

Key engineering decisions from this project.

Reduced loan processing from 5 business days to under 90 seconds for the vast majority of applications.
Delivered executive-level technical leadership at a fraction of a full-time hire, saving an estimated $180K annually.
Migrated legacy data systems to a unified analytics layer, consolidating 4 disconnected sources into one.
Achieved full production deployment in 12 weeks including regulatory compliance validation.

Stack snapshot

Tools and platforms used in the delivery.

TensorFlowSnowflakePostgreSQLAzureKubernetes

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