How lender, dealer insights shape AI tools

Technology providers are examining equipment lender and dealer perspectives to fully unlock the potential of AI and establish long-term partnerships.  

Nearly 70% of financial services firms reported AI-driven revenue growth in 2024, with most seeing at least 5% to 10% increases, according to market research firm Statista. AI investments in financial services reached approximately $45 billion in 2024, up 28.6% from 2023.  

As AI reshapes equipment finance, fintechs are recognizing that comprehensive lender insights are crucial to maximizing new tech, Shivi Sharma, co-founder and president of San Francisco-based Kaaj.ai, told Equipment Finance News. Kaaj uses AI agents — designed to execute complex tasks independently — to automate and accelerate small-business lending processes for equipment financiers, credit unions and other financial services firms.  

“We get a lot of lender perspectives on what their challenges are, what the bottlenecks are that they are facing in their operations,” Sharma said. “And then we build the products to address those challenges.” 

The fintech meets with hundreds of lenders every year for “rich conversations” about the workflows and processes they want to improve, Sharma said. 

Small-business lenders have been struggling to handle higher volumes of applications and maximize data-driven decisions, she said. Knowing this prompted Kaaj to develop a credit intelligence platform geared toward end-to-end automation, processing unstructured data and increasing profitability relative to the growing number of applications. 

The offerings are especially important for small-business lenders because “most of the time they’re working on thin margins,” Sharma said. 

“That’s what we wanted to focus on,” she said. “How do we build the right technology, right solution that really helps them analyze the data and provide intelligence so the burden on their teams reduces?” 

Dealer pain points 

Equipment dealer perspectives are similarly shaping AI tools that bridge the gap between lenders and end-users.  

For example, loan automation software provider Northteq in October launched Aurora IDP, which automates the extraction and verification of data from applications, invoices and other documents.  

Aurora IDP got its start after a survey Northteq conducted at the 2025 Associated Equipment Distributors conference found that “time to decision” is the biggest challenge in dealer finance operations, Chief Executive Kristian Dolan told EFN. 

“That’s the main driver of why [dealers] would choose one lender over another,” he said. “So, if you start with what the vendors and dealers want, and then you work backwards from there, you’re like, ‘Well, those are the bottlenecks.’” 

Many dealers said that manual document processing was a major hindrance to financing decisions, Nolan said. 

“Dealers want to be able to get financing easily,” he said. “They’re creating order forms. They’re creating invoices. So, if you can simply send over an invoice to a finance company, and the finance company can take that, extrapolate the equipment data, customer data and everything they need to get the credit application going, it just removes work for the vendor, makes their life easier.” 

Evaluating the need for tech 

It is crucial for fintechs to evaluate lenders’ needs when gathering their perspectives. 

In the short term, lenders often want to “continue using their systems rather than rip and replace everything,” Kaaj’s Sharma said. 

“If they’re using Salesforce, what will the integration into Salesforce look like?” she said. “What kind of fields should be mapped? How do we address any concerns around maybe creating duplicates?  

“A lot of effort goes into understanding what will help their teams adopt the solution with minimum disruption and minimum retraining, because one of the biggest challenges of using any new technology is retraining staff.” 

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