Financial Firms Deploy Generative AI to Speed Lending and Customer Service
Financial services companies are using generative AI to cut application processing times from minutes to seconds, reduce customer wait times, and free up staff to handle complex cases. Figure Lending, the largest nonbank home equity line of credit provider in the U.S., processes legal documents in under six seconds that previously took agents 30 minutes - with 99.5% accuracy.
Figure originated roughly 30,000 HELOCs totaling almost $2.5 billion in 2024. The company built a proprietary platform running more than 90 customized machine learning models, combining its own generative AI programs with tools from Google and OpenAI.
How Financial Services Are Using AI Today
At Figure, AI handles document processing, chatbots answer customer questions during applications, and voice AI automatically contacts borrowers who started but didn't complete the process. The company's marketing department uses the platform to target prospects with the right message at the right time.
Ruben Padron, Figure's Chief Data Officer, said the company chose third-party AI solutions partly because of regulatory requirements. The tools comply with Figure's zero data retention policy and integrate with existing security measures to prevent unauthorized access to customer information.
Other financial firms report similar results. Insurers GEICO and AXA deployed AI chatbots that locate customer documents, answer coverage questions, and adapt to customer needs. These systems reduce wait times and redirect human agents to more complex issues.
A 2025 Forrester survey of more than 900 companies found that IT leaders using AI for customer service cited enabling customer self-service as a top use case. Forty-three percent of IT leaders developing AI-enabled customer service solutions said this was their primary focus.
Converting Data Into Actionable Information
S&P Global Energy partnered with Microsoft to make its commodity market reports accessible through AI. The company produces over 1,000 news items and reports daily, but customers previously had to download files or build custom interfaces to extract relevant data.
S&P prepared its content for AI by categorizing text into chunks and storing them with metadata. Large language models then identify relationships between data points and generate summaries. Customers can access this through Microsoft 365, Google, Amazon Web Services, Snowflake, or other platforms.
A North American natural gas pipeline utility now uses S&P data combined with regulatory reports and internal metrics to compile daily indicators on gas prices, regional outages, and storage levels. Priyanka John, S&P's vice president of digital product management, said the goal is to help customers "get answers to their crucial questions as fast as possible so they can make confident decisions."
The Business Case for AI in Finance
Research from Metrigy shows generative AI improves customer satisfaction metrics while also generating revenue and cutting costs. When agents work more efficiently, companies may reduce hiring needs. As representatives solve problems faster, they gain more time for upselling.
Padron said Figure views AI as a productivity multiplier. "It lets us empower our loan officers and customer service agents to be much more effective and efficient at what they do," he said. The company was recognized for this work by Experian at its 2025 Vision Awards.
Financial services firms remain in early stages of AI deployment. Padron said his team is exploring how new models might address other business needs. "In terms of what's possible when we deploy AI responsibly, I think we're only starting to recognize the positive impact it can have on customers," he said.
Learn more about AI for Customer Support and AI for Finance.
Your membership also unlocks:
