Finance Desk

Private credit firms can still whiff if algorithms do the work, but the onus is on them.

Lenders are leaning on artificial intelligence to score borrowers, monitor portfolios, and automate workflows that once took analysts weeks. Momentum is only building: More than half of private credit portfolio managers—54%—plan to deploy AI in underwriting, according to a March PwC survey of 120 global firms.

But as AI takes on more of that analytical heavy lifting, firms face a tough question: When an algorithm makes a mistake, who bears the blame?

For credit risk expert Naeem Siddiqi, author of Intelligent Credit Scoring and senior risk advisor at SAS, the answer is clear: Don’t fault AI; it’s just a tool.

If the large language model, or LLM, miscalculates a number or uses a prohibited category like race or religion, “then the lender is liable,” he said in an email. The courts already tested that principle — that a company can’t hide behind its own algorithm. Guess what? The company lost.

‘An Emerging Discipline’

Take Moffatt v. Air Canada for example. One of the airline’s customers used its chatbot in 2022 to ask about bereavement fares following a death in his family. The chatbot told him he could book a full-fare ticket and apply for a refund within 90 days, advice that contradicted Air Canada’s actual policy requiring passengers to submit such requests before travel.

When the customer tried to collect, Montreal-based Air Canada argued it shouldn’t be held liable, effectively treating the chatbot as a separate entity responsible for its own statements.

The British Columbia Civil Resolution Tribunal rejected that defense, found Air Canada liable for the error and ordered the airline to pay $812.02 Canadian dollars, including CA$650.88 in damages plus interest and fees.

Siddiqi said the ruling set a precedent: “Companies can’t argue that the AI is a separate independent entity that frees the firm from liability.”

He pointed to a broader wave of AI-related litigation in the U.S. where legal exposure extends far beyond chatbots and the airline industry. Currently, there are copyright suits against LLM developers, including Anthropic. However, in other scenarios, the company wielding the tech bore the brunt of scrutiny.

Last year, facial-recognition company Clearview AI faced privacy litigation while software firm Intuit and HR tech firm HireVue received a discrimination complaint alleging their AI hiring tools disadvantaged a deaf, Indigenous job applicant.

“This is an emerging discipline,” Siddiqi said, “but it’s safe to assume the lender is liable for discriminatory decisions made on its behalf, whether by a human or an AI.”

Risk Sits With Lender

For private credit firms racing to deploy AI across underwriting and portfolio monitoring, the early case law sends a signal: The technology can do the work, but it doesn’t absorb the risk. That still sits with the lender.

“Legally and regulatory-wise, the buck stops entirely with the lender,” said Omar Abassi, founder of Newport Beach-based lending tech startup LoanFlo AI.

So far, regulators such as the Consumer Financial Protection Bureau, the Office of the Comptroller of the Currency and the U.S. Department of Housing and Urban Development have made it clear: You can’t delegate your compliance obligations to a software vendor, Abassi said.

If an AI algorithm introduces algorithmic bias, violates the Equal Credit Opportunity Act, or fails to provide legally compliant adverse action notices, regulators sue or fine the lender—not the AI company.

Because of this legal exposure, some lenders require vendor platforms to provide audit trails showing exactly what the AI read, and regular back-testing to prove the AI model does not inadvertently produce discriminatory outcomes.

Treating AI Like an Employee

That gap between high market interest and actual operational risk is top-of-mind for technology leaders building loan administration tools.

“There’s a general enthusiasm in the market around AI … and firms are very excited about diverse capabilities,” said David Yahalomi, chief operating officer and co-founder of Tel Aviv-based loan-management platform Hypercore. “But this technology is a statistical-based technology … it can make mistakes, and we’ve all seen that.”

Rather than viewing AI as a replacement for decision-makers, Yahalomi suggested lenders treat AI like a new hire who requires guidance and thorough review.

“We should treat it like it’s an employee,” Yahalomi said. “Even if you feel like you’ve trained your best agent … think about it like you gave a deal to your best person five minutes ago. Would it give you the correct answers, or does it need proper time to actually go and research?”

Ultimately, Yahalomi cautioned against granting agents final authority over deals: “We should not treat it as a person that makes calls … you shouldn’t treat it as an executive.”

What’s Next

The balance between strict regulatory oversight and day-to-day workflow is where human teams feel the pressure most. As LLMs become more ubiquitous, too few humans are taking on too much work and leaning heavily on AI-driven underwriting.

“Underwriters are definitely taking on too much work in traditional setups and being overworked in many cases, which leaves more room for human error,” Abassi said. But don’t expect AI to replace credit risk assessment; instead, it’s closing the gap so that fewer underwriters can underwrite many more loans and be less stressed as a result.

“Eventually, the AI will be so good that human underwriters won’t be able to keep up,” he added. “AI agents will be the ones reviewing the other AI’s work. We aren’t there yet, but ultimately it’s on its way.”

Anthony Noto covers corporate finance and private credit. Contact him at anoto@gfmag.com.

There’s a lot of cash, but fewer deals propelled global fintech to the best year since 2022.

When Global Payments completed its roughly $24.3 billion acquisition of London-based Worldpay in January, it would account for nearly a quarter of all global fintech investment in the five months that followed, according to Big Four auditor KPMG International’s latest Pulse of Fintech report released Monday.

That massive transaction captures the central paradox shaping current fintech funding: total capital is surging, yet it is concentrated in fewer hands.

KPMG crunched the numbers using data from PitchBook, which tracks M&A and venture capital activity. Overall fintech investment surged to $103.1 billion across the six-month period — up from $72.2 billion in the second half of last year — putting the sector on track for its strongest annual performance in four years. Overall deal count, however, dropped to a multi-year low.

Deal Volume Remains Soft

The shift reflects a strong preference for mature fintechs with proven track records over higher-risk, early-stage startups.

As a result, global deal volume dropped to just 2,100 transactions in the first half of the year. That’s down from 2,501 in the prior six-month period (the last six months of 2025). Instead of spreading capital across early-stage ventures, investors funneled funds into late-stage blockbuster deals.

Ten deals worth $1 billion or more closed during the period. In addition to buying WorldPay, Global Payments Inc. found itself on the sell side. The Atlanta-based company sold its issuer solutions business, Total System Services (TSYS), to Fidelity National Information Services Inc. for $13.5 billion — also in January.

Among the other megadeals of 2026, thus far, are the $8.4 billion buyout of Clearwater Analytics and the $6.4 billion take-private of OneStream. In Europe, Denmark’s Saxo Bank was acquired for $1.2 billion, and Belgium’s Kpler Holding landed a private equity growth equity investment of over $1 billion from global investment firm Sixth Street Partners in June.

Strategic liquidity and the latest technology are fueling digital transformation.

Modern treasury management is undergoing a profound digital transformation. As corporate finance teams navigate increasing geopolitical complexity, volatility, and the need for instantaneous decision-making, the role of their banking and technology partners has shifted. No longer just providers of standard transaction services, these institutions are becoming architects of sophisticated, data-driven ecosystems that prioritize real-time visibility, automated governance, and seamless liquidity orchestration. The global winners of Global Finance’s Best Treasury & Cash Management Providers 2026 awards demonstrate a clear commitment to this new paradigm, offering tools that do more than just process payments; they empower treasurers to treat liquidity as a strategic, actively managed asset.

METHODOLOGY

Global Finance editors select the winners of the Best Treasury & Cash Management Awards with input from industry analysts, corporate executives, and technology experts. The editors also use entries submitted by financial services providers, as well as independent research, to evaluate a series of objective and subjective factors. It is not necessary to enter to win, but experience shows that the additional information supplied in an entry can increase the chances of success. In many cases, entrants can present details and insights that may not be readily available to the editors of Global Finance.

This year’s ratings are based on the period from January 1, 2025, to December 31, 2025.

Global Finance uses a proprietary algorithm with criteria—including knowledge of local conditions and corporate customer needs, quality of product and service offerings, financial strength and safety, market standing, compliance, and excellent customer service—weighted for relative importance. The algorithm incorporates multiple ratings into a single numerical score, with 100 equivalent to perfection. In cases where more than one institution earns the same score, we favor local providers over global institutions and privately owned banks over government-owned ones.

The winners are those financial services providers that best meet the specialized needs of corporations engaged in global business. These top-notch financial institutions are not always the biggest, but rather the best—those with qualities that companies should look for when choosing a provider.

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MEET THE WINNERS