Connect with us

Fintech

BofA’s CashPro Platform Uses Gen AI to Put Treasurers in Control | PYMNTS.com

Published

on

Bank of America’s CashPro platform is undergoing a transformation, fueled by artificial intelligence (AI), real-time data and digital capabilities.

This has contributed to CashPro netting more than 40,000 corporate and commercial clients around the world. The global treasury management platform now supports everything from mobile-based biometric logins to self-service forecasting using machine learning. “Clients … are looking for more productivity and efficiency out of tools that help them manage cash, payments and receivables,” said Tom Durkin, global product head of CashPro in Global Payments Solutions at Bank of America. According to Durkin, the cash flow managed by BofA’s corporate clients sits on top of a treasure trove of data for all the different systems that run through the bank. Globally, he told PYMNTS, exchanging information from trade, supply chains and foreign exchange provides unique visibility into a company’s treasury operations.

Durkin said CashPro now delivers “predictive, more personalized recommendations to clients to help drive the right treasury decisions [via a secure platform],” citing CashPro Forecasting, CashPro Chat and QR Sign-In as examples.

The Internal Stack

Bank of America has embedded AI not only in its client-facing products but throughout its internal technology stack.

“We’re leveraging AI … to help [develop] software,” said Andrew McKibben, head of International Technology and CIO for Global Corporate and Investment Banking at BofA. “It improves the productivity of a software engineer — helps them write code, helps them write test cases [and] improve time to market. It improves quality as well.”

McKibben said that innovation is decentralized by design. “We [believe] that all employees can innovate or be forward-thinking, regardless of their role,” he said. “We showcase it and we celebrate it.”

That approach has yielded more than 7,800 patents from nearly 8,000 employees, with 1,400 of those patents in AI and machine learning.

The bank’s “Great Wall of Patents” in the Chicago office, with members of the CashPro team. From left: Adam Jalali, Trish Gillis (patent holder), Scott Mumma (patent holder) and Alyssa Salloum. Credit: Bank of America

In generative AI, the bank’s efforts include content classification, summarization, and generation, which enables Bank of America to support clients more efficiently and effectively.

“You can prompt and ask questions of all of our research reports in a library and generate content that might be useful [for someone internally, or in discussions with] a client, McKibben said.

Forecasting Efficiency

On the treasury side, Durkin pointed to CashPro Forecasting as one of the clearest examples of AI-driven efficiency. It learns from a client’s historical cash flows, automatically selecting the most accurate balance for each account and using it to forecast future cash positions. At the end of each day, the models are retrained based on the new cash flows from that day, allowing them to continuously learn and adjust for changes in seasonality and other operational impacts specific to each company.

“There’s nothing more important to the treasurer than preserving and understanding where their cash is, Durkin said, adding that people traditionally have used a spreadsheet to forecast, and that could take up to a week to complete. By the time it’s done, the data is out of date. However, with CashPro Forecasting, the modeling is done within minutes.

CashPro Forecasting also supports scenario-based modeling. “If I create certain models and events, how will the model scenario work? How will that work within this unit — if I have a subsidiary operating in the EU versus a subsidiary that’s operating out of Brazil? Durkin said. Clients can develop forecasts up to a year into the future.

In addition to forecasting, clients are increasingly using self-service features like account verification letters to do things like substantiate account information for a beneficiary. Bank of America said adoption has soared by 21% in the first quarter of 2025 from the fourth quarter of 2024.

Durkin said their clients no longer have to call the service center — they can generate the letters themselves. Clients are now asking the bank to offer the feature outside of the U.S. as well.

CashPro Chat is another artificial intelligence tool built on the same platform as Erica, the bank’s consumer-facing virtual assistant. CashPro Chat helps treasurers and other financial professionals to quickly view transactions, find information about their accounts and navigate CashPro functionality.  According to Durkin, 40% of queries are self-serviced through this tool.

The evolution of the CashPro App is another core part of the bank’s strategy. “The app itself really started as … a transactional tool, Durkin said. “But we see more opportunity for [it] to be a personalized tool [once] you’ve told it what you like, what you don’t like, and what you want to tap into. A key demonstration of the app’s popularity is how it’s used to approve payments. Last year, the volume of payment approvals exceeded $1T. The bank believes the figure underscores the trust that treasurers have in the app to conduct strategic business decisions.

Saving Grace

Daylon Bailey, treasury operations manager at Highgate Hotels, said the CashPro App has been “our saving grace. Primary administrators like myself, a lot of times, we’re generally going into CashPro App to make decisions, so it’s nice to have front and center that information that we need right then and there — whether I need to approve a user change, I need to approve a wire or look at positive pay. It’s very intuitive. It’s like having the web-based platform in the palm of your hand.”

McKibben highlighted security as a key trend. The bank is adding additional security layers for protection, including stronger authentication through QR sign-in and push notifications before signing in. Push code notifications were added in May while adoption of QR sign-in is growing rapidly, increasing 60% from 2023 to 2024.  

Bank of America

CashPro Insights is another capability that delivers value as it helps corporate clients make smarter treasury decisions by analyzing their transactional data. It provides tailored recommendations, such as encouraging shifts from paper checks to digital payments and highlighting opportunities to enhance account security. CashPro Insights is designed to “drive efficiency and help clients better understand “what they should be doing, not just what they are doing today, Durkin said.

Angela Brown, assistant treasurer of Continental, said, “the amount of data we can now tap into using CashPro Insights is jaw-dropping. We had been creating these KPIs internally and it took us many steps to get to these same valuable data points. Now they are right at our fingertips.”

Clients are responding to the improvements. “Some customers will say, ‘CashPro knows more about my business than some of my team does,’” Durkin said. “Because it sees all that.”

On the subject of agentic AI, McKibben said the bank is being deliberately strategic. “We’re interested in building that, but we also want to make sure we have the right controls around its use, he said. “We’re deep into evaluating it.”

CashPro also offers flexibility, which is also a key differentiator.

“CashPro can meet the clients wherever they are, whether through the mobile app, online platform, or an API rail, Durkin said. “Some clients may pull real-time data through the CashPro API, use the online experience for CashPro Chat, and rely on the mobile app to review and approve payments.”

Looking ahead, Durkin said more automation and intelligence are coming. “We’re going to continue to drive that out in areas where clients gain better access to information and more efficient delivery.”

McKibben said the broader trend is toward real-time treasury capabilities. “[Traditionally the data available to treasurers was based on what is already available but increasingly, data is becoming more ‘real-time’]. You want customers to get really valuable insights into the data and their cash flow to make more dynamic … decisions… That’s a continued focus area for us.”

Durkin closed with a reflection on CashPro’s future: “I think it’s already pretty smart, but as with any human, you’re never done learning.”

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

Fintech

Experian Unveils New AI Tool for Managing Credit and Risk Models | PYMNTS.com

Published

on

Experian Assistant for Model Risk Management is designed to help financial institutions better manage the complex credit and risk models they use to decide who gets a loan or how much credit someone should receive. The tool validates models faster and improves their auditability and transparency, according to a Thursday (July 31) press release.

The tool helps speed up the review process by using automation to create documents, check for errors and monitor model performance, helping organizations reduce mistakes and avoid regulatory fines. It can cut internal approval times by up to 70% by streamlining model documentation, the release said.

It is the latest tool to be integrated into Experian’s Ascend platform, which unifies data, analytics and decision tools in one place. Ascend combines Experian’s data with clients’ data to deliver AI-powered insights across the credit lifecycle to do things like fraud detection.

Last month, Experian added Mastercard’s identity verification and fraud prevention technology to the Ascend platform to bolster identity verification services for more than 1,800 Experian customers using Ascend to help them prevent fraud and cybercrime.

The tool is also Experian’s latest AI initiative after it launched its AI assistant in October. The assistant provides a deeper understanding of credit and fraud data at an accelerated pace while optimizing analytical models. It can reduce months of work into days, and in some cases, hours.

Experian said in the Thursday press release that the model risk management tool may help reduce regulatory risks since it will help companies comply with regulations in the United States and the United Kingdom, a process that normally requires a lot of internal paperwork, testing and reviews.

As financial institutions embrace generative AI, the risk management of their credit and risk models must meet regulatory guidelines such as SR 11-7 in the U.S. and SS1/23 in the U.K., the release said. Both aim to ensure models are accurate, well-documented and used responsibly.

SR 11-7 is guidance from the Federal Reserve that outlines expectations for how banks should manage the risks of using models in decision making, including model development, validation and oversight.

Similarly, SS1/23 is the U.K. Prudential Regulation Authority’s supervisory statement that sets out expectations for how U.K. banks and insurers should govern and manage model risk, especially in light of increasing use of AI and machine learning.

Experian’s model risk management tool offers customizable, pre-defined templates, centralized model repositories and transparent internal workflow approvals to help financial institutions meet regulatory requirements, per the release.

“Manual documentation, siloed validations and limited performance model monitoring can increase risk and slow down model deployment,” Vijay Mehta, executive vice president of global solutions and analytics at Experian, said in the release. With this new tool, companies can “create, review and validate documentation quickly and at scale,” giving them a strategic advantage.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Read more:

Experian and Plaid Partner on Cash Flow Data for Lenders

Experian Targets ‘Credit Invisible’ Borrowers With Cashflow Score

CFPB Sues Experian, Alleging Improper Investigations of Consumer Complaints

Continue Reading

Fintech

Anthropologie Elevates Maeve in Rare Retail Brand Launch | PYMNTS.com

Published

on

Anthropologie is spinning off its Maeve product line as a standalone brand, a rare move in a retail sector where brand extensions have become less common.

The decision reflects shifting strategies among specialty retailers as they work to adapt to changes in women’s fast-fashion and evolving consumer behavior.

Maeve, known for its blend of classic silhouettes and modern flourishes, will now operate independently with dedicated storefronts and separate digital channels, including new social media accounts and editorial content platforms, according to a Monday (Aug. 4) press release. The brand is inclusive, spanning plus, petite, tall and adaptive options, which broaden its reach as the industry contends with demands for representation.

Maeve has nearly 2 million customers and was the most-searched brand on the Anthropologie website over the past year, the release said. It is also a driver of TikTok engagement. Several of the company’s most “hearted” items online are already from the Maeve label.

“Maeve has emerged as a true driver of growth within Anthropologie’s portfolio,” Anu Narayanan, president of women’s and home at Anthropologie Group, said in the release. “Its consistent performance, combined with our customers’ emotional connection to the brand, made this the right moment to evolve Maeve into a standalone identity.”

While many retailers have retreated from new brand creation, opting instead to consolidate or focus on core labels, Anthropologie’s move suggests confidence in cultivating sizable, engaged consumer communities around sub-brands.

Anthropologie is backing Maeve’s standalone debut with a comprehensive marketing campaign, including influencer-driven content, a new Substack, a launch event in New York, and a charitable partnership, per the release. The first Maeve brick-and-mortar store is set to open in Raleigh, North Carolina, in the fall.

The move comes as the apparel sector in the United States sees shoppers valuing not just price and selection, but brand story, inclusivity and digital experience. While the outcome remains to be seen, Anthropologie’s gamble on Maeve reflects a belief that consumers remain eager to embrace distinctive, thoughtfully curated fashion.

Continue Reading

Fintech

Meta Faces Scrutiny Over AI Prompt Disclosure | PYMNTS.com

Published

on

Meta’s artificial intelligence assistant may publicly share user prompts, and its apps may have exploited a technical loophole to track Android users without their knowledge, CPO Magazine reported.

Meta’s AI app introduced a pop-up warning that content entered by users — including personal or sensitive information — may be publicly shared, per a June 20 report. It seems these prompts can be published in the “Discover” feed. The feature, which launched earlier this year, showcases AI-generated content and occasionally displays user-submitted prompts, some of which have included private data such as legal documents, personal identifiers and even apparently audio of minors.

Although users can opt out, the setting is enabled by default, and users must manually disable it, the report said. Privacy advocates argue that no other major chatbot service offers a comparable mechanism that proactively republishes private inputs.

Consumers already have privacy concerns around generative AI. The PYMNTS Intelligence report “Generation AI: Why Gen Z Bets Big and Boomers Hold Back” found that 36% of generative AI users are nervous about these platforms sharing or misusing their personal information, and 33% of non-users are kept from adopting the technology because of the same hesitations.

Separately, Meta may have taken advantage of an Android system vulnerability known as “Local Mess” to harvest web browsing data, per a June 17 CPO Magazine report. The loophole, involving the mobile operating system’s localhost address, potentially allowed Meta and Russian tech company Yandex to listen in on users and correlate their behavior across apps and websites. The tech giants may have been able to do this even when users were browsing in incognito mode or using other privacy protections. This data could be linked to a user’s Meta account or Android Advertising ID.

Meta has since halted sending data to localhost, characterizing the issue as a miscommunication with Google’s policy framework. Privacy watchdogs and experts say both cases could trigger regulatory action in the European Union and other jurisdictions.

Meta is already facing legal action over its privacy practices in an $8 billion lawsuit concerning alleged data misuse.

Google, for its part, is scheduled to appear in court later this month for allegedly violating the privacy of both Android and non-Android mobile phone service users.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Continue Reading

Trending