FinAi Podcast

Loan servicing and software provider Sagent named Sridhar Sharmachief executive in September.  

Sharma joined Sagent as president in February from loan servicing provider Mr. Cooper, he tells FinAi News on this episode of “FinAi Podcast.” Mr. Cooper was acquired by Rocket Companies in 2025. 

Sharma brings experience in product, technology and AI leadership to Sagent, he says.  

At Mr. Cooper, Sharma spent over a decade as executive vice president and chief information officer and later chief innovation and digital officer. 

He solved complex problems, built and scaled technology and learned to prioritize innovation that was relevant to the business, he says.  

He will continue to solve fragmentation and friction at Sagent. 

His priorities as CEO include: 

• Overseeing implementations of its end-to-end real-time mortgage servicing platform Dara; 
• Keeping up with evolving technology; and 
• Building out Sagent’s partner ecosystem with payment, title, insurance and tax providers. 

Listen to Sharma discuss his experience in mortgage servicing and how he is using AI to solve complex problems.

AI-powered commercial and agriculture lending platform Vine Financial innovates around customer feedback, including the June launch of its Reporting Dashboard. 

The Reporting Dashboard is an AI-driven tool that allows financial institutions to tap key portfolio metrics hidden inside their core banking data, Justin O'Brien, chief product officer at Vine, tells FinAi News on this episode of the "FinAi Podcast." 

"Cores do a great job of storing information," O'Brien says. However, community banks and credit unions don't always have teams big enough to build custom reports based on that data.  

The Reporting Dashboard offers real-time insights based on FI-specific data to view deposit relationships, liquidity trends, outstanding decisions and more, O'Brien says. This gives community banks and credit unions access to data that they weren't easily tapping before. 

Vine clients include Primeway Federal Credit Union, Crest Savings Bank and Ipava State Bank, according to the company.  

Listen as O'Brien discusses addressing gaps in the market and innovating around client feedback. 

Mortgage lender Newrez has received a positive response to its customer-facing AI tool, signaling a shift in how people buy homes.  

Newrez launched Rezi Mortgage Assistant, its customized ChatGPT tool, in May, and has seen “plenty of usage,” Chief Information Officer Brian Woodring tells FinAi News on the latest episode of the “FinAi Podcast.” 

“That trend of the more sophisticated and informed consumer is going to accelerate,” Woodring says.  

Newrez originated $63.3 billion in mortgage loans in 2025, up 7% year over year, according to parent company Rithm Capital.  

“Millions of our customers are on ChatGPT, and that's only going to increase over time,” he says. “We're going out there into an environment where we have inherently a little bit less control, but we wanted to meet our customers where they were, even though it doesn't give us that same visibility and control that hosting it ourselves does.” 

The AI tool, designed to address common queries about the mortgage process based on Newrez’s guidelines, is also boosting internal efficiencies because customers are more educated when speaking with loan officers, Woodring says.  

“We're seeing that it's actually helping our customers be better informed, which for them obviously makes the process a lot less scary and stressful, but it's a big win for us too because we don't go back and forth as much,” he said.  

Tools such as Rezi Mortgage Assistant mark an inflection point for the industry as more prospective homebuyers become comfortable using AI for mortgage advice, he says.  

Over the next year, Woodring says he expects more customers “to have an AI agent working with them to help them figure out what they want and how to get it.” 

“You're going to see that creating a more competitive landscape, which I think is good for everyone,” he said. 

Listen as Woodring discusses Newrez’s approach to customer-facing AI and other AI initiatives.  

AI is changing the fraud landscape on both ends of the spectrum: Fraudsters can use AI to increase the intricacy and polish of their exploits and FIs can use AI to identify scammers in near real-time.

But AI progress marches on and FIs must continually reevaluate and refine their methods for combating fraud, Jennifer Pitt, senior analyst of fraud and security at Javelin Strategy & Research, tells FinAi News on this episode of the “FinAi Podcast.”

"A lot of organizations that I speak to on a daily basis [are] only looking at the fraud that we're seeing right now, and I think that's the problem that we need to address," she says. "We can't only look at the fraud that we're seeing right now. We have to be able to try to anticipate what fraud might be occurring."

FIs need to be able to "think like a criminal," Pitt says, to anticipate the next uses of AI for fraud, especially as models such as Anthropic's Mythos 5 and OpenAI's GPT-5.6-Sol expand capabilities. 

"We need to look at all the fraud that's actually happening — not only within each ecosystem, but the whole fraud landscape," she says. 

That means implementing the latest technologies, including AI, Pitt says. Concerns about implementation costs and preserving consumer trust may cause some FIs to hesitate before implementing new tech. However, FIs will pay a great deal more in both of those metrics if they do not implement AI and other modern tools to fight fraud, she says.

"You are going to pay either way," Pitt says. "You pay on the front end for the technology and tools, or you pay on the back end for the financial loss or customer attrition."

Listen as Pitt discusses how fraud has changed in the age of AI, what FIs and consumers can do to protect themselves and the critical need for institutions to share knowledge.

Nearly a year after launching Agent Pay, Mastercard is focused on developing trust to drive adoption. 

“The first thing is the consumer needs to know that they can trust the interaction,” Mastercard Chief Digital Officer Pablo Fourez tells FinAi News on this episode of the “FinAi Podcast.”  

“They need to know that if ‘I shop with this agent and something goes wrong, I am protected.’” 

Agent Pay, announced in April 2025, has now rolled out across Mastercard’s global operations, enabling the company's network of issuing banks to participate in agentic commerce, Fourez says. 

Central to Mastercard's approach to agentic payments is "Verifiable Intent," a specification the company co-developed with Google and open-sourced through standards bodies including the FIDO Alliance, he says.  

Verifiable Intent is an open, standards-based trust layer for agentic commerce that creates a tamper-resistant record of what users authorized when an AI agent acts on their behalf, according to a March Mastercard release. 

Verifiable Intent “helps basically a merchant understand that this is actually an agent that they can trust," Fourez says. 

Looking ahead, he says next year will bring more autonomous use cases and growth in machine-to-machine payments, including agent-to-agent transactions tied to business-to-business commerce. 

Listen as Fourez discusses how Mastercard aims to develop and drive adoption of agentic payments. 

J.P. Morgan Payments is looking to AI to remove friction from workflows — freeing up employees from repetitive and manual tasks. 

"The workflow surrounding the payment has traditionally been very manual," Michelle Conklin, head of receivables and public sector product and operations for J.P. Morgan Payments, tells FinAi News on this episode of the "FinAi Podcast."  

It's "a manually intensive process that has multiple steps throughout," from physically receiving the mail, opening envelopes, extracting documents, capturing documents, entering data and resolving exceptions, she says. 

That's where AI is transforming the paper process into a digital effort.  

J.P. Morgan Payments has deployed a mail automation robot within its lockbox sites, tapping robots to open envelopes, remove and unfold the contents, scan documents and extract data, she says. 

Removing manual steps of check processing and data capture is a big help considering the bank processed more than 130 million checks in 2025, she says. 

"When you operate at the scale that we do, even the smallest inefficiencies become significant," she says. "We are transforming a highly intensive paper process into a more digital, efficient and scalable experience for both our clients, but also equally for our employees." 

Now employees can use their time and resources for exceptions, problem solving, client support and oversight. 

Listen as Conklin discusses how J.P. Morgan Payments is using AI to digitalize historically manual processes. 

Small businesses are increasingly looking to AI to improve operations – and banks must be able to meet the needs of those clients. 

According to the 2026 TD Financial Preparedness Survey, released in April, 69% of business owners already use AI to reduce expenses, up from 39% in the 2025 survey. The survey polled 1,000 U.S. business owners with 100 or fewer employees. 

“That was a dramatic increase,” Chris Ward, head of small business banking at TD Bank U.S., tells FinAi News on this episode of the “FinAi Podcast.” 

In the survey, small business owners identified the top benefits of AI for their businesses: 

• Customer service; 
• Fraud and cybersecurity; and 
• Sales and marketing. 

AI in SMB banking

While small businesses deploy AI internally, they are also looking to their financial services provider for advice and insights. 

“Operating a small business is really complex nowadays,” Ward says. “It’s tough to be a small business owner, so we found that giving tools to our business customers to help them manage their cash flow is more important than ever.” 

That’s where the bank’s Small Business Dashboard, or cash flow management tool, comes into play, he says. It offers insights, forecasts future cash flow needs and allows for benchmarking across other businesses in the same industry. 

“They’re looking for information and they’re looking for somebody who can help them manage their cash flow more intelligently,” Ward says. 

Listen as Ward discusses how SMBs use AI and how TD is keeping up with the demand for intelligent small business banking solutions. 

Tax season adds stress to banking systems with a surge in transactions, fraud threats, data complexity and necessary risk controls. 

This added stress, including to AI systems, can expose gaps in data quality, Mark Blake, financial services industry practice lead at data management solution provider Stibo Systems, tells FinAi News on this episode of “The Buzz” podcast. 

Those gaps to watch for in AI systems include: 

• Mismatched data; 
• Missing data; 
• Lineage issues; and 
• Auditability issues. 

Financial institutions must ensure “they’re meeting and satisfying the regulators, and they need to be confident that their AI models also stand up to that pressure,” Blake says. 

Listen as Blake discusses AI readiness at financial institutions this tax season.

Financial institutions have established cloud partners and now those cloud providers are being tapped for agentic AI, Ravi Khokhar, executive vice president and head of cloud at Capgemini, tells FinAi News on this episode of “The Buzz” podcast. 

"The role of cloud has now become an enabler for AI across financial services,” Khokar says.  

For example, banks are tapping their cloud providers to host agents, creating processes that are “a little bit more intentional for managing risk, compliance, explainability,” he says. 

Netherlands-based bank ABN AMRO tapped Microsoft and Capgemini to migrate its existing chatbot to the cloud, according to Capgemini’s ” “World Report Series 2026: Cloud in Financial Services.” The bank migrated its chatbot infrastructure to Microsoft Copilot Studio to create an agent that integrates generative AI features and scalability. 

Before moving it to the cloud, the chatbot had high customer drop-off rates, limited capabilities and high operating costs, according to the report. Now, the agent’s language processing accuracy in Dutch has increased by 7% and overall drop-off rates fell. 

Listen as Khokhar discusses agentic readiness, multicloud and multiagent ecosystems and the importance of governance, trust and training when deploying agentic AI. 

Bank of America invests about $4 billion annually in AI and other technologies to keep up with the needs of its clients.  

“AI at the bank … touches everything we do,” Nikki Katz, head of digital at Bank of America, tells FinAi News on this episode of “The Buzz” podcast. 

Katz leads a team of designers, data scientists, product managers and others who meet the needs of the 59 million clients accessing the bank through its digital channels — its website, mobile app, and its AI-driven assistant Erica. 

“We make over a thousand different enhancements to [the digital experience] every year,” she says, noting, “We’re constantly tuning Erica.” 

Erica adoption continues to grow as it is continuously iterated. The latest stats: 

• About 50 million clients have used the AI assistant; 
• Clients have engaged with Erica for almost 19 million hours; and  
• Erica has had over 3 billion interactions. 

Listen as Katz discusses how her team approaches emerging technology and the application of AI across digital channels at the bank.