Equipment financiers continue to identify areas best suited for AI integration while recognizing its long-term potential.  

The global market for AI in finance is projected to hit $73.9 billion in 2033, a more than fourfold increase from $17.7 billion in 2025, according to research and consulting firm Market.us.

AI is reshaping equipment finance by accelerating “high-volume and repeatable” tasks on the front end while humans remain accountable for credit decisions, Mark French, president of Atlanta-based Crest Capital, told FinAi News‘ sister publication Equipment Finance News. These tasks include:  

• Extracting key data from financial statements; 

• Verifying insurance and vendor documents; 

• Drafting credit summaries; and  

• Flagging exceptions for underwriter review. 

Fraud detection is another strong use case, French said, noting that AI “can spot synthetic identity signals, document tampering and pattern anomalies, then route suspicious files to tighter human review.” 

Strengthening sales ops 

AI is also streamlining sales processes, Riley Thompson, vice president and head of direct sales at North American equipment financier Mitsubishi HC Capital America, told EFN.  

Thompson “and my whole sales team use [Microsoft] Copilot for analysis of financial statements,” he said. “We use it to create credit memos based on any deals that we’re looking at to bridge the gap with credit.” 

AI-driven automation is effective for tasks such as lead generation and asset management because it allows employees to focus on more substantial revenue-generating tasks, Thompson said. 

“If you have a platform to run those through, now we can focus on reselling equipment, which is where we make our money,” he said. 

“The less time that we spend on all of this monotonous, repetitive stuff that isn’t true intelligence, that is where the money comes in.” — Riley Thompson, vice president and head of direct sales at North American equipment financier Mitsubishi HC Capital America

The agentic advantage  

Meanwhile, the benefits of AI should increase as lenders capitalize on agentic solutions, Thompson said. 

“When you talk agentic, that’s exactly what we’re hoping for,” he said. “We want to see our sales people not only use AI but understand it to the point that they’re able to develop their own widgets” that are not necessarily “tied to the Mitsubishi ecosystem.”

Lenders can think beyond automation using agentic, Thompson said. AI voice agents are one example.

“When I get on a phone with a customer, [the agent] is going to be a compendium of all the information out there, but actually sounds and operates like a human being,” he said.

Crest Capital’s French also said that AI agents present opportunities to cut cycle time for document review, data extraction, exception handling and reducing “rework without changing core credit standards.”