AI in finance is shifting from pilot projects to real production workloads. Banks, lenders, exchanges, and payment platforms are deploying machine learning to reduce fraud, automate underwriting, improve compliance, and speed up customer service. That matters for investors because financial institutions generate massive proprietary data sets and operate in highly regulated environments where even modest improvements in loss rates, decision quality, or labor efficiency can translate into meaningful economic value.
The opportunity spans several layers of the stack. Some companies sell AI directly into credit scoring, lending automation, fraud monitoring, anti-money-laundering workflows, and regulatory reporting. Others provide the workflow and decisioning software that helps banks operationalize AI across onboarding, servicing, and risk management. The most compelling businesses in this theme tend to have clearly monetized AI products, recurring software revenue, or transaction and platform fees tied directly to financial workflows rather than simply using AI internally.
This list focuses on investment quality within that broader AI-in-finance theme. The countdown runs from #7 to #1, so the names at the top are not necessarily the most speculative AI stories, but the companies that currently combine stronger business quality, financial performance, and strategic relevance to financial AI. That distinction matters in a market where narrative can move fast, but durable returns usually come from repeatable execution.
For this screen, we focused on U.S.-listed companies with market capitalizations above $500 million that have a direct connection to AI-enabled financial workflows, decisioning, fraud, lending, compliance, or market infrastructure. We then ranked the list primarily by investment quality, using our composite quality grade alongside profitability, growth, valuation context, and earnings execution. This is a countdown, so the strongest overall pick appears last at #1 rather than first.
What they do. The company develops enterprise AI application software, including its C3 agentic AI platform and a dedicated C3 AI Financial Services Suite. Its business model is built around selling AI applications and development environments to large organizations, with additional reach through partnerships with Microsoft Azure, AWS, Google Cloud, McKinsey, and others.
Why it fits. C3.ai makes this list because AI is the product, not just an internal tool, and financial services is one of its named verticals. That said, this ranking emphasizes investment quality, and C3.ai scores lower because the financial profile still looks weak relative to other AI-in-finance names with more established recurring economics.
Numbers that matter. Revenue was $307.4 million, but year-over-year revenue growth was negative 46.1%. Profitability remains deeply challenged, with a gross margin of 43.5%, operating margin of negative 263.63%, and net margin of negative 141.35%, while EBITDA was negative $453.1 million. Return on equity was negative 55.01% and return on assets was negative 29.88%, which helps explain the company’s C- composite quality grade.
Recent momentum. C3.ai has beaten earnings estimates in 5 of the last 7 reported quarters, but the most recent completed report on February 25, 2026 missed badly, with EPS of negative $0.40 versus a negative $0.29 estimate, a 37.9% miss. Analyst sentiment is cautious, with 1 Buy, 6 Hold, and 2 Sell ratings, and the average target of $8.82 sits below where the shares last closed. With earnings due June 3, this is the highest-risk name on the list.
Market cap: $1.9B · Quality grade: B · Analyst consensus: Hold (avg target $23.31)
What they do. The company is a software-as-a-service vendor focused on financial institutions, offering onboarding, account opening, lending, credit monitoring, portfolio analytics, and integration tools on the nCino Platform. Its products are built for banks, credit unions, challenger banks, and mortgage lenders, giving it direct exposure to recurring software revenue tied to core banking workflows.
Why it fits. nCino fits the AI-in-finance theme because its lending and small-business loan origination tools include automation and machine learning, while its consumer lending and onboarding products digitize decision-heavy processes inside banks. In other words, it sits in a practical part of the stack where AI can improve underwriting speed, customer acquisition, and operating efficiency.
Numbers that matter. Revenue reached $610.1 million, with year-over-year growth of 10.6%. Profitability is positive but still modest, with a 61.6% gross margin, 13.25% operating margin, and 2.17% net margin, while EBITDA was $71.6 million. Earnings growth was much stronger than revenue growth, up 147.6% year over year, and forward earnings expectations imply a notable step-up, with EPS estimated at 1.0261 next year versus trailing EPS of 0.12.
Recent momentum. Execution has improved lately. nCino beat estimates in its March 31, 2026 report with EPS of $0.37 versus $0.215 expected, a 72.1% surprise, and it also beat in December 2025 by 47.6%. Analysts remain constructive but not aggressive, with 5 Buy and 10 Hold ratings, and the average target stands at $23.31. The main reason it ranks only sixth is that the company still carries a high trailing P/E of 143.25 despite only modest current margins.
Market cap: $3.2B · Quality grade: C · Analyst consensus: Hold (avg target $40.20)
What they do. The company operates a cloud-based AI lending platform across personal loans, small-dollar loans, auto refinance, auto retail loans, auto secured personal loans, and home equity lines of credit. Unlike many software vendors adjacent to finance, Upstart monetizes AI directly through lending workflows, making its platform economics tightly linked to underwriting and credit decisioning activity.
Why it fits. Upstart is one of the purest AI-in-finance stories in the market because automated underwriting is central to the business model. If AI adoption in lending keeps expanding, Upstart has direct exposure to that trend through platform usage in personal and auto credit, but that also means its results can be more cyclical and credit-sensitive than those of software peers.
Numbers that matter. Revenue was $1.17 billion, and year-over-year revenue growth was a strong 44.6%. Profitability has turned positive, but it is still thin, with an 82.7% gross margin, 0.9% operating margin, and 4.21% net margin, while EBITDA was $98.9 million. Earnings growth was 209.1% year over year, and analysts expect EPS to rise to 3.4367 next year from trailing EPS of 0.41, but the stock still trades at 81.98 times trailing earnings and 36.50 times forward earnings.
Recent momentum. Upstart has beaten earnings estimates in 6 of the last 7 quarters, including a 750.0% surprise in February 2025 and a 76.5% surprise in May 2025. The one recent blemish was the May 5, 2026 report, when EPS of $0.30 missed the $0.43 estimate by 30.2%. Analyst positioning is mixed, with 2 Buy, 7 Hold, and 1 Sell ratings, which fits a stock that has improving fundamentals but still carries meaningful execution and credit-cycle risk.
Get AI research on any stock
Instant reports, daily intelligence, and an AI analyst in your pocket.
What they do. The company provides banking, payments, capital markets, fraud, risk management, compliance, and treasury technology to financial institutions and businesses worldwide. FIS is not a narrow AI pure play, but it owns critical financial infrastructure and monetizes software and services embedded in day-to-day banking and transaction processing.
Why it fits.FIS fits because AI in finance increasingly rides on large transaction, fraud, compliance, and banking data sets, and those are exactly the workflows where FIS already operates. Its exposure to fraud, risk management, compliance, lending, and capital markets gives it multiple paths to embed AI into products that financial institutions already depend on.
Numbers that matter. Revenue was $11.44 billion, with year-over-year growth of 30.1%. Profitability is solid for a scaled financial technology provider, with a 36.3% gross margin, 16.39% operating margin, and 23.35% net margin, while EBITDA reached $3.31 billion. The valuation is also relatively undemanding, at 8.24 times trailing earnings and 6.95 times forward earnings, which is one reason it scores an A on our composite quality grade.
Recent momentum.FIS has beaten estimates in 5 of the last 7 quarters, including a 5.4% beat in the May 8, 2026 report when EPS came in at $1.36 versus $1.29 expected. Results have been steady rather than explosive, with two quarters merely matching estimates. Analysts lean positive, with 4 Buy, 9 Hold, and 1 Sell ratings, and the average target is $58.76. For investors who want AI-in-finance exposure through established infrastructure, FIS offers a more balanced risk profile than the pure-play names.
What they do. Nasdaq operates exchanges, market services, listing platforms, data products, and a broad financial technology portfolio. Its offerings include Verafin for money-laundering and financial fraud detection, AxiomSL for risk data management and regulatory reporting, surveillance tools, and Calypso for trading, treasury, risk, and collateral management.
Why it fits. Nasdaq is one of the clearest examples of AI in finance moving into production because it already sells technology into financial crime detection, compliance, market surveillance, and trading infrastructure. Verafin is especially relevant to this theme because transaction monitoring and anti-money-laundering are high-value AI use cases with recurring demand from banks and other financial institutions.
Numbers that matter. Revenue was $5.42 billion, with year-over-year growth of 13.7%. Profitability is excellent, with a reported gross margin of 100.0%, operating margin of 48.4%, and net margin of 35.28%, while EBITDA totaled $3.22 billion. Earnings growth was 33.8% year over year, and EPS is projected to rise to 4.4288 next year from trailing EPS of 3.32, although the valuation is fuller than FIS at 26.48 times trailing earnings and 25.77 times forward earnings.
Recent momentum. Nasdaq has one of the cleanest execution records on this list, beating estimates in 7 of the last 7 quarters. The April 23, 2026 report delivered EPS of $0.96 versus a $0.93 estimate, a 3.2% beat, following a 4.3% beat in January. Analysts are constructive, with 6 Buy and 3 Hold ratings and no Sell ratings reported, while the average target is $106.47. That consistency is a major reason it ranks in the top three.
Pick #2Subscribers only
Subscribers see this pick's full breakdown — investment thesis, key financial metrics, recent earnings execution, and analyst consensus.
Subscribers get the complete breakdown — pick rationale, financial metrics, and recent earnings detail.
This monthly screen focused on U.S.-listed stocks with market capitalizations above $500 million and a direct business connection to AI in financial services, including credit scoring, lending automation, fraud and AML monitoring, compliance, workflow orchestration, and market infrastructure. We ranked candidates primarily by investment quality, using our composite quality grade as the starting point and then weighing profitability, revenue and earnings growth, valuation context, analyst sentiment, and recent earnings execution. The article is presented in countdown order from #7 to #1, so the final company listed is our top overall pick for this month’s refresh.
▌The Daily Briefing · Free
A new stock idea, every evening.
One stock worth watching each weekday, plus the analysis behind it. Free, in your inbox.
