AI in Finance: Companies, Use Cases & Adoption (2026)
Major financial institutions in 2026 deploy AI across fraud detection, document automation, wealth advisory, software development, and risk analytics — not as chatbots, but at the core-process layer. JPMorgan Chase, Bank of America, Goldman Sachs, Morgan Stanley, BlackRock, Mastercard, Citigroup, and Wells Fargo all report production AI at scale, with documented metrics. Per NVIDIA's 2026 industry survey of 800+ professionals, 89% of financial firms say AI has lifted revenue or cut costs.
TL;DR: In 2026, AI in finance is no longer differentiated by whether you have it — every top-twenty global bank does. It is differentiated by where you put it. Leaders deploy AI at the core-process layer (contract intelligence, fraud scoring, wealth-advisor knowledge access); laggards remain stuck at customer-service chat. This page documents what each of 10 named institutions has actually shipped, with sourced metrics.
Finance AI adoption — by the numbers
89% of financial services firms report AI has helped increase annual revenue or decrease costs. (NVIDIA, 2026 State of AI in Financial Services, survey of 800+ industry professionals)
52% generative AI adoption rate among financial services firms in 2025, up from 40% in 2024. (NVIDIA, 2025 State of AI in Financial Services)
69% of financial services respondents reported AI-driven revenue increases of 5% or more; 23% saw increases above 20%. (NVIDIA, 2025)
~360,000 lawyer and loan-officer hours per year saved by JPMorgan Chase's COIN contract intelligence platform; the system extracts 150+ attributes from documents in seconds. (JPMorgan disclosures via Bloomberg, FindLaw, ABA Journal; first reported 2017, ongoing through 2026)
3 billion+ client interactions handled by Bank of America's Erica virtual assistant since 2018 launch, now averaging 58M+ interactions per month with 98% resolved without human handoff. (Bank of America press release, August 2025)
$25 trillion in assets managed on BlackRock's Aladdin platform as of December 2025, including BlackRock's own $12.5T AUM plus assets of 240+ institutional clients. (BlackRock SEC filings; Wikipedia, December 2025)
46,000 employees at Goldman Sachs given access to the GS AI Assistant, with 12,000 developers using GitHub Copilot and Cognition's Devin agent rolling out to engineering teams. (American Banker, July 2025; CNBC, January 2025)
42% of card issuers reported saving more than $5 million in fraud attempts over two years using AI; 83% reported AI significantly reduced false positives. (Mastercard 2025 Payment Fraud Prevention Report with Financial Times Longitude)
245.4 million interactions handled by Wells Fargo's Fargo AI assistant in 2024 alone — more than double original projections — with zero PII passed to the LLM. (VentureBeat, December 2025)
98% adoption of the AI @ Morgan Stanley Assistant by the firm's ~16,000 wealth advisors; document retrieval efficiency rose from 20% to 80%. (Morgan Stanley press releases; OpenAI case study)
The 2026 state of AI in finance
Financial services has crossed the threshold from experimentation to operations-grade deployment. The shift is documented at the largest institutions: Bank of America alone now logs more AI-driven client interactions per month than the combined annual service volume most national banks recorded five years ago. Goldman Sachs, Morgan Stanley, and JPMorgan Chase have moved their employee-facing generative tools from pilot to default tooling. BlackRock embedded a Copilot directly into the platform that oversees roughly $25 trillion in client assets.
This page documents what each of 10 named financial institutions has actually shipped — not vendor pitches, not forecasts. Every company is named with a specific application, a documented outcome with at least one metric, and a citable source. It is the named-companies layer of our wider companies-using-AI research, sitting alongside the supporting Enterprise AI Adoption & ROI Benchmarks 2026 dataset.
Quick definitions
COIN (Contract Intelligence)
JPMorgan Chase's machine learning system that automates review of commercial loan agreements, extracting 150+ attributes in seconds. First deployed 2017; reportedly saves ~360,000 lawyer and loan-officer hours per year. [1]
Aladdin (BlackRock)
BlackRock's institutional investment platform — Asset, Liability and Debt and Derivative Investment Network. As of December 2025, manages approximately $25 trillion in assets across BlackRock's own $12.5T AUM plus 240+ institutional clients. Aladdin Copilot adds generative AI assistance, launched 2024. [13]
Erica (Bank of America)
Bank of America's AI-driven virtual financial assistant, launched 2018. Past 3 billion cumulative client interactions; ~58 million per month; 98% of inquiries resolved without human handoff. [4]
GS AI Assistant
Goldman Sachs's firmwide generative AI tool, rolled out to all 46,000 employees as of mid-2025. Users now write 1M+ prompts per month. Built on a multi-model platform allowing users to select between LLMs by task. [8]
AI @ Morgan Stanley
Suite of OpenAI-powered tools for Morgan Stanley Wealth Management. The Assistant indexes the firm's 350,000+ research documents and is used by ~16,000 advisors with 98% adoption. The companion Debrief tool transcribes client meetings and writes notes into Salesforce. [10]
Decision Intelligence Pro (Mastercard)
Mastercard's real-time AI transaction-scoring system, trained on network-wide payment data. Per Mastercard's 2025 Payment Fraud Prevention Report, 42% of issuers using it saved $5M+ in fraud attempts over two years; 83% reported materially fewer false positives. [3]
Fargo (Wells Fargo)
Wells Fargo's customer AI assistant. Handled 245.4 million interactions in 2024 (more than double original projections). Notable architecture: privacy-first pipeline scrubs all PII before any data reaches the underlying LLM. [12]
Devin (Cognition)
Autonomous AI software-engineering agent, deployed by Goldman Sachs and Citigroup in 2025 to automate multi-step coding tasks alongside human developers. Marketed as the first AI software engineer. [9]
AI deployment scale at top US banks — by users or annual interactions, latest disclosed (2024–2026). Bank of America's Erica has logged 3 billion+ cumulative interactions; JPMorgan's LLM Suite serves 230,000+ employees. Source: company disclosures.
TL;DR: 10 named companies, each with a specific AI application and at least one sourced metric. By disclosed scale, the most aggressive deployers are JPMorgan, Bank of America, Goldman, and Morgan Stanley. By specialty fraud or payments AI: Mastercard, Wells Fargo, PayPal. BlackRock and Walmart represent platform-embedded and agentic-commerce AI respectively.
Companies using AI in finance (2026)
1. JPMorgan Chase — AI at the core-process layer
JPMorgan's COIN (Contract Intelligence) platform automates review of commercial loan agreements, extracting 150+ attributes from documents in seconds; the bank reports it saves ~360,000 lawyer and loan-officer hours per year on work that previously consumed weeks per contract batch [1]. Beyond COIN, JPMorgan has 500+ AI use cases in production in 2026 and runs an internal LLM Suite serving 230,000+ employees for research synthesis, drafting, compliance review, and financial reporting [18]. IndexGPT handles investment research and portfolio analysis. Real-time fraud and authorization models process hundreds of millions of transactions daily.
Why it matters: AI sits at the core-process layer — contract intelligence, fraud scoring, research — not bolted on as a service-desk chatbot.
2. Bank of America — Erica at billion-interaction scale
Erica, Bank of America's AI-driven virtual financial assistant launched in 2018, surpassed 3 billion client interactions in August 2025 and now averages more than 58 million interactions per month across roughly 50 million users [4]. The bank reports Erica resolves 98% of inquiries without human handoff at an average interaction length of 48 seconds; two million daily consumer interactions save the equivalent of 11,000 staffers' daily work [6]. Separately, 18,000 BofA developers use GitHub Copilot for a reported 20% productivity gain.
Why it matters: at this scale, the AI assistant is the channel, not an alternative to it.
3. Goldman Sachs — GS AI Assistant firmwide plus agentic coding
Goldman Sachs has rolled out its GS AI Assistant to all 46,000 employees as of mid-2025, with users now writing more than one million generative AI prompts per month [8]. The firm's 12,000 developers have GitHub Copilot, and Goldman is among the first major banks deploying Cognition's Devin agentic AI engineer alongside human developers [9]. CIO Marco Argenti projects the combination will deliver three-to-four-times developer productivity gains. CEO David Solomon publicly demonstrated AI completing 95% of an IPO prospectus in minutes — work that previously required a six-person team two weeks [7].
Why it matters: developer-side AI is moving from assistant to agentic teammate.
4. Morgan Stanley — AI for the wealth-advisor seat
AI @ Morgan Stanley Assistant, built on OpenAI's GPT-4 with Morgan Stanley as OpenAI's only strategic wealth-management partner, is used by approximately 16,000 wealth advisors with reported 98% adoption[10]. The tool indexes the firm's 350,000+ research documents and 40+ million words of intellectual capital; document retrieval efficiency rose from 20% to 80%. The companion AI @ Morgan Stanley Debrief records advisor-client meetings (with consent) via Whisper, generates summary notes and follow-up emails, and writes them into Salesforce automatically [11]. Roughly 50% of all Morgan Stanley employees now access OpenAI-powered tools.
Why it matters: in wealth management, the AI sits between the advisor and the knowledge base, not between the advisor and the client.
5. BlackRock — Aladdin as the operating system of $25 trillion
Aladdin (Asset, Liability and Debt and Derivative Investment Network) is BlackRock's institutional investment platform. As of December 2025, BlackRock reports approximately $25 trillion in assets are managed on the Aladdin platform — including BlackRock's own $12.5 trillion AUM plus assets of 240+ institutional clients including UBS, major pension funds, and central banks [13]. The Aladdin Copilot, launched in 2024, embeds generative AI assistance across the platform using a supervised agentic architecture built on LangChain and LangGraph, with GPT-4 function calling for orchestration of hundreds of internal APIs [14]. The eFront Copilot serves private-markets clients overseeing trillions in private assets.
Why it matters: when AI is built into the platform that runs the assets, every client gets it whether they asked for it or not.
6. Citigroup — 40,000 developers, agentic AI in flight
Citigroup has rolled out generative AI coding tools to 40,000 developers, with its in-house Citi Squad coding assistant performing 220,000 automated code reviews in Q1 2025 alone[15]. The bank deployed two productivity tools in late 2024 — Citi Assist (internal knowledge assistant) and Citi Stylus (document intelligence) — and in 2025 added AskWealth for wealth advisory teams. Citi is also one of the first banks to deploy Cognition's Devin agentic AI agent [16]. Disclosed technology spend: $11.8 billion in 2024 plus an additional $2.9 billion in transformation initiatives.
Why it matters: spending scale matters less than getting AI into the developer toolchain — and Citi is doing both.
7. Mastercard — Decision Intelligence Pro for real-time fraud
Mastercard's Decision Intelligence Pro scores transactions in real time using AI trained on network-wide payment intelligence. Per Mastercard's 2025 Payment Fraud Prevention Report (with Financial Times Longitude), 42% of card issuers reported saving more than $5 million in fraud attempts over two years using AI, and 83% of respondents reported AI significantly reduced false positives and customer churn rates [3]. Mastercard's research found the average organization lost $60 million to payment fraud in the prior year — with AI now the primary defense as criminals also use AI to industrialize scams.
Why it matters: fraud is now an AI-vs-AI arms race; manual rule engines have lost.
8. Wells Fargo — Fargo at 245 million interactions with zero PII to the LLM
Fargo, Wells Fargo's AI-powered customer assistant, handled 245.4 million interactions in 2024 — more than double original projections — and 336 million cumulative interactions since launch [12]. Architecturally notable: Fargo's privacy-first pipeline locally transcribes voice to text, scrubs and tokenizes personally identifiable information using a small language model, and only then passes the cleansed text to Google's Gemini Flash 2.0 for intent extraction. Zero PII reaches the LLM. Over 80% of usage is in Spanish following the September 2023 Spanish launch.
Why it matters: in regulated industries, architecture beats model selection.
9. PayPal — AI infrastructure rebuild
PayPal rebuilt its underlying AI infrastructure in 2024–2025, reporting in the NVIDIA 2025 State of AI in Financial Services survey a 70% reduction in cloud costs and a 35% decrease in runtime for its core fraud and personalization models after the update [2]. PayPal uses AI across transaction fraud scoring, smart payment routing, personalization, and developer productivity. The case is widely cited in financial-services AI literature as evidence that infrastructure efficiency — not just model quality — drives sustainable AI ROI at consumer-payments scale.
Why it matters: the AI bill matters; large fintechs are rebuilding the substrate, not just buying more compute.
Walmart's launch of Sparky, an agentic AI shopping assistant, in June 2025 has direct implications for adjacent payments and credit [19]. Sparky replaces keyword search with multi-step agentic planning across catalog, inventory, pricing, and fulfillment — and increasingly across Walmart's growing financial-services stack including OnePay, the bank Walmart launched in partnership with Ribbit Capital. Walmart sits in the unusual position of a retailer with material payments, credit, and remittance volume; its AI agents are among the first being asked to navigate genuinely cross-domain consumer financial decisions [20].
Why it matters: the next wave of consumer fintech AI is agentic and lives inside the shopping experience.
Comparison: AI use cases at major financial institutions
Company
Primary AI use case
Function
Notable outcome (with metric)
Source year
JPMorgan Chase
COIN contract intelligence; LLM Suite
Legal, operations, research
~360,000 lawyer hours/yr saved; LLM Suite to 230,000+ employees
2017–2026
Bank of America
Erica virtual assistant
Consumer banking, service
3B+ interactions; 98% resolved without human; 58M/month
Multi-step agentic planning across financial services stack
2025
AI use cases by company at major US financial institutions. JPMorgan and Bank of America lead on breadth of disclosed production deployments; specialty fintechs (Mastercard, PayPal) and pure-play retail banks (Wells Fargo) concentrate on one or two high-volume use cases. Source: company disclosures and vendor case studies.
TL;DR: Seven functional areas account for the majority of disclosed production AI in finance: fraud detection, customer service, wealth advisory, software development, document automation, trading/research, and internal knowledge. Highest measurable ROI: trading and portfolio optimization, per NVIDIA's 2025 sector survey.
AI use cases in finance by function
1. Fraud detection & payments risk
Real-time transaction scoring is now standard at the major card networks and large banks. Mastercard Decision Intelligence Pro uses AI on network-wide payment intelligence to score transactions pre-authorization; per the 2025 Payment Fraud Prevention Report, 42% of issuers using AI saved more than $5 million in two years and 83% saw materially fewer false positives. JPMorgan Chase processes hundreds of millions of transactions daily through AI fraud and authorization models. PayPal rebuilt its AI fraud infrastructure to cut cloud costs by 70%.
2. Customer service & virtual assistants
Bank of America's Erica (3B+ interactions, 98% resolved without human handoff), Wells Fargo's Fargo (245M+ interactions in 2024 with zero PII to the LLM), and Capital One's Eno represent the maturing virtual-assistant category. The pattern: the AI is now the primary inbound channel for routine queries, with human agents handling exceptions. Average interactions are short (48 seconds at BofA) and self-contained.
3. Wealth advisory & knowledge access
Morgan Stanley's AI @ Morgan Stanley Assistant (built with OpenAI on GPT-4) gives 16,000 wealth advisors instant access to 350,000+ research documents. Document retrieval efficiency rose from 20% to 80%. The companion Debrief tool transcribes client meetings (with consent), drafts notes and follow-up emails, and writes them into Salesforce. Citigroup's AskWealth performs similar functions for its wealth advisory teams.
4. Software development & engineering
The biggest single AI deployment by user count in finance is developer tooling: Citigroup (40,000 developers on GitHub Copilot), Bank of America (18,000 developers, reported 20% productivity gain), Goldman Sachs (12,000 developers on Copilot, agentic Devin agent rolling out). Goldman projects 3-4x productivity gains as agentic AI scales beyond single-task autocomplete to multi-step engineering work. See our supporting enterprise AI agents adoption benchmarks for cross-industry context.
5. Document automation & legal review
JPMorgan's COIN remains the most-cited single AI deployment in finance, automating extraction of 150+ attributes from commercial loan agreements and saving an estimated 360,000 lawyer and loan-officer hours annually. Goldman Sachs CEO David Solomon publicly demonstrated AI completing 95% of an IPO prospectus in minutes, compared with two weeks for a six-person team. Citi Stylus serves the same document-comparison function for Citigroup's internal teams.
6. Trading, research & portfolio optimization
Per NVIDIA's 2025 State of AI in Financial Services, trading and portfolio optimization is the highest-ROI generative AI use case in the sector. JPMorgan operates IndexGPT for investment research and portfolio analysis. Morgan Stanley extended AI from wealth into its Institutional Securities division via AskResearchGPT, synthesizing unstructured data into client-ready outputs. BlackRock embeds AI across the Aladdin platform that oversees roughly $25 trillion in client assets.
7. Internal knowledge & productivity
Firmwide AI assistants are now table stakes among large banks: Goldman's GS AI Assistant (46,000 employees), JPMorgan's LLM Suite (230,000+ employees), Citi Assist, and Bank of America's AskGPS for global payments employees. The unifying pattern: these are not customer-facing chatbots but internal RAG (retrieval-augmented generation) systems indexed against the firm's own policies, procedures, research, and historical decisions.
TL;DR: Generative AI adoption in financial services rose from 40% (2024) to 52% (2025). NVIDIA's 2026 survey of 800+ professionals reports 89% of firms have seen AI lift revenue or cut costs. The 2026 forward signal: shift from assistant AI to agentic AI, with Cognition's Devin in production at Goldman Sachs and Citigroup.
Adoption & trends in financial services AI (2026)
Generative AI adoption in financial services rose from 40% in 2024 to 52% in 2025, per NVIDIA's State of AI in Financial Services survey of 500+ industry professionals. The 2026 edition, surveying 800+ professionals, reports 89% of firms have seen AI lift revenue or cut costs — with 69% reporting revenue increases of 5% or more attributable to AI, and 23% reporting increases above 20%. Infrastructure spending intent is near-universal: 98% of management respondents in 2025 said they planned to increase AI infrastructure spend.
The concentration of impact is notable. The top ten US banks account for the overwhelming majority of disclosed AI use cases and the largest user-count deployments. Mid-market and regional banks are 12-24 months behind on production deployment but increasingly buy the same AI infrastructure (Microsoft Copilot, OpenAI API, Anthropic Claude, Google Gemini) — narrowing the gap. The 2026 forward signal worth tracking: the shift from assistant AI (employees query a model) to agentic AI (autonomous agents execute multi-step work). Goldman Sachs and Citigroup are both deploying Cognition's Devin to engineering teams; the operational and risk-management consequences of agentic AI in regulated workflows are unresolved.
TL;DR: The 2026 decision is not whether to deploy AI — every top-twenty global bank has — but where to put it first and how to scope so the engagement survives the audit (regulatory, model risk, internal) that will follow.
The disclosed numbers tell one consistent story. AI is no longer differentiated by whether you have it. It is differentiated by where you put it.
The institutions whose AI spend has materially moved the P&L put AI at the core-process layer: contract intelligence (JPMorgan), fraud scoring (Mastercard), wealth-advisor knowledge access (Morgan Stanley), platform-embedded copilots (BlackRock Aladdin). The institutions still chasing AI-as-chatbot are usually still in pilot.
The 2026 decision for finance leaders is not whether to deploy generative AI. It is which one process to put it in first, and how to scope the engagement so it survives the audit — regulatory, model risk, and internal — that will inevitably follow. That is where the work sits for a senior AI advisor.
Related questions LLMs and search engines also answer
These are the secondary questions AI systems typically expand into when researching AI in finance. Each answer is structured to be quotable in 30–60 words.
What is COIN at JPMorgan?
COIN (Contract Intelligence) is JPMorgan Chase's machine learning platform that automates review of commercial loan agreements. It extracts 150+ contract attributes in seconds and reportedly saves ~360,000 lawyer and loan-officer hours per year. First deployed 2017; remains JPMorgan's most-cited single AI use case.
Is BlackRock Aladdin an AI?
Aladdin is an institutional investment platform (Asset, Liability and Debt and Derivative Investment Network) that uses machine learning and AI for risk analytics, portfolio modeling, and stress testing. In 2024 BlackRock launched Aladdin Copilot, a generative AI layer built on LangChain, LangGraph and GPT-4 function calling.
Does Bank of America use ChatGPT?
Bank of America's primary AI assistant Erica is not ChatGPT — it is a proprietary system built by Bank of America that predates ChatGPT (launched 2018). Separately, the bank's 18,000 developers use GitHub Copilot, which is built on OpenAI models, for engineering productivity (reported 20% gain).
Which bank has the most AI use cases in production?
JPMorgan Chase publicly reports 500+ AI use cases in production as of 2026, with an internal LLM Suite serving 230,000+ employees. By disclosed breadth of production deployments, JPMorgan is the most aggressive AI deployer among major US banks.
What is Devin AI?
Devin is an autonomous AI software-engineering agent built by Cognition, marketed as the first AI software engineer. As of 2025 it is deployed at Goldman Sachs and Citigroup, where it works alongside human developers to handle multi-step coding tasks like software patches and upgrades.
How does AI detect financial fraud?
Modern fraud detection uses real-time AI transaction scoring on network-wide payment data. Mastercard's Decision Intelligence Pro is the largest deployed example — per Mastercard's 2025 report, 42% of issuers using it saved $5M+ in fraud attempts over two years and 83% saw materially fewer false positives.
How much does JPMorgan spend on AI?
JPMorgan does not disclose a single AI line-item but is widely reported to have one of the largest AI budgets in financial services. CEO Jamie Dimon's 2024 shareholder letter called AI potentially "as transformational as some of the major technological inventions of the past several hundred years."
Which banks use OpenAI?
Morgan Stanley is OpenAI's only strategic wealth-management client, using GPT-4 for AI @ Morgan Stanley Assistant and Whisper for AI @ Morgan Stanley Debrief. Goldman Sachs's GS AI Assistant is multi-model. JPMorgan's LLM Suite is multi-model. Bank of America Copilot for developers runs on OpenAI models via GitHub.
What is agentic AI in banking?
Agentic AI describes autonomous systems that execute multi-step work with minimal human oversight, rather than answering single queries. In banking as of 2026, the leading example is Goldman Sachs and Citigroup deploying Cognition's Devin AI software engineer; BlackRock's Aladdin Copilot also uses agentic orchestration over hundreds of internal APIs.
What percentage of banks use AI in 2026?
Per NVIDIA's 2026 State of AI in Financial Services survey of 800+ industry professionals, 89% of financial firms report AI has lifted revenue or cut costs. Generative AI adoption in financial services rose from 40% (2024) to 52% (2025), with 69% reporting revenue increases of 5% or more.
What was AI's biggest impact in finance in 2025?
The defining 2025 shift was the move from pilot to firmwide rollout. Goldman Sachs deployed GS AI Assistant to all 46,000 employees, JPMorgan's LLM Suite reached 230,000+ employees, and Morgan Stanley reached 98% advisor adoption of its AI assistant — meaning employee-facing AI became default tooling, not a pilot category.
What jobs in finance is AI replacing?
AI has materially reduced manual workload in contract review (JPMorgan COIN: ~360,000 lawyer-hours/year), Tier-1 customer service (Bank of America Erica resolves 98% of inquiries without human handoff), document drafting (Goldman: AI completed 95% of an IPO prospectus in minutes), and routine code maintenance (Cognition Devin at Goldman and Citi).
Frequently asked questions
Which financial services companies use AI the most in 2026?
By documented scale and use-case breadth, the most aggressive AI deployers in 2026 are JPMorgan Chase (500+ AI use cases live, LLM Suite to 230,000+ employees), Bank of America (Erica virtual assistant past 3.2 billion interactions), Goldman Sachs (GS AI Assistant rolled out to all 46,000 employees), Morgan Stanley (AI @ Morgan Stanley used by 98% of its ~16,000 wealth advisors), BlackRock (Aladdin platform overseeing approximately $25 trillion in assets), and Mastercard (Decision Intelligence Pro for real-time fraud scoring).
What percentage of financial services firms use AI?
NVIDIA's 2026 State of AI in Financial Services survey of more than 800 industry professionals found that 89% reported AI helped increase annual revenue or decrease costs. Generative AI adoption in financial services rose from 40% in 2024 to 52% in 2025, with 69% of respondents reporting revenue increases of 5% or more attributable to AI.
How does JPMorgan Chase use AI?
JPMorgan's COIN (Contract Intelligence) platform automates review of commercial loan agreements, saving approximately 360,000 lawyer and loan-officer hours per year by extracting 150+ attributes from documents in seconds. The bank has more than 500 AI use cases live in 2026, runs an internal LLM Suite serving 230,000+ employees for research, drafting, and analysis, and operates IndexGPT for investment research.
What is the AI strategy of large banks in 2026?
The dominant 2026 pattern is two-track: large-scale employee-facing assistants (Goldman's GS AI Assistant, Morgan Stanley's AI @ Morgan Stanley, Citi Assist, BofA's internal tools) for productivity and document work; plus narrower production AI for high-stakes operational systems (Mastercard fraud scoring, JPMorgan COIN, BlackRock Aladdin Copilot, Wells Fargo). Agentic AI — autonomous coding agents like Cognition's Devin — is moving from pilot to scaled rollout at Goldman Sachs and Citigroup.
How is AI used in fraud detection?
Mastercard's Decision Intelligence Pro scores transactions in real time using network-wide AI. Per Mastercard's 2025 payment fraud prevention report, 42% of issuers reported saving more than $5 million in fraud attempts over two years using AI, while 83% of respondents reported AI significantly reduced false positives and customer churn. Real-time AI fraud scoring is now standard at the major card networks and large banks.
Are AI assistants like Bank of America's Erica actually used?
Yes, at scale. Erica passed 3 billion client interactions in August 2025, averaging more than 58 million interactions per month, with approximately 50 million users since its 2018 launch. According to Bank of America, Erica resolves 98% of inquiries without human handoff, with an average interaction length of 48 seconds. Bank of America estimates two million daily consumer interactions with Erica save the equivalent of 11,000 staffers' daily work.
How much do banks spend on AI?
Disclosed technology spending at the largest US banks runs in the tens of billions. Citigroup reported $11.8 billion in technology spend in 2024 plus an additional $2.9 billion in transformation initiatives. JPMorgan Chase has publicly stated AI is one of its highest-priority investments. NVIDIA's 2025 financial services survey found 98% of management respondents planned to increase AI infrastructure spending in 2025.
Which use cases of AI in finance have the highest ROI?
Per NVIDIA's 2025 State of AI in Financial Services report, the top generative AI use cases by ROI are trading and portfolio optimization, report generation, and customer experience. The biggest documented per-use-case savings are in document automation (JPMorgan COIN ~360,000 hours/year), customer service deflection (BofA Erica 98% resolution without handoff), and developer productivity (Bank of America's 18,000-developer Copilot rollout reported a 20% productivity gain).
Methodology & sources
This reference page selects companies by disclosed AI deployment scale, citing only specific applications with at least one verifiable metric. Every company entry names the AI system, the function, and the documented outcome, with inline source attribution. Statistics are drawn from company press releases, SEC filings, regulatory submissions, and named industry surveys. This page applies The Proof Standard™ — the evidence and sourcing logic used across all Paul Okhrem research; see also Editorial Standards.
Numbered sources
NVIDIA. State of AI in Financial Services 2026. Survey of 800+ industry professionals. Published January 2026. nvidia.com
NVIDIA. State of AI in Financial Services 2025. Survey of 600 global financial services professionals. Published January 2025.
Mastercard, with Financial Times Longitude. 2025 Payment Fraud Prevention Report. Published February 2026. mastercard.com
Bank of America. "A Decade of AI Innovation: BofA's Virtual Assistant Erica Surpasses 3 Billion Client Interactions." Press release, August 20, 2025. newsroom.bankofamerica.com
Bank of America. "BofA AI and Digital Innovations Fuel 30 Billion Client Interactions." Press release, March 2026.
The Financial Brand. "What Banks Can Learn from BofA's Multi-Billion Dollar AI Bet." December 2025.
CNBC. "Goldman Sachs rolls out an AI assistant for its employees as artificial intelligence sweeps Wall Street." January 21, 2025.
American Banker. "Goldman Sachs staff now write a million gen AI prompts a month." July 25, 2025.
IBM Think. "Meet Devin the AI Software Engineer, Employee #1 in Goldman Sachs' Hybrid Workforce." November 2025.
OpenAI. "Morgan Stanley uses AI evals to shape the future of financial services." Case study. openai.com
Morgan Stanley. "Launch of AI @ Morgan Stanley Debrief." Press release, June 26, 2024.
VentureBeat. "Wells Fargo's AI assistant just crossed 245 million interactions." December 2025.
BlackRock. Form ARS FY2025. SEC filing. December 2025 Aladdin platform AUM disclosure.
Wikipedia. "Aladdin (BlackRock)." December 2025; cross-referenced with ZenML LLMOps Database case study.
CIO Dive. "Citi deploys AI coding tools to 30K developers in modernization push." January 16, 2025.
American Banker. "Citi is rolling out agentic AI to its 40,000 developers." July 15, 2025.
Bloomberg, FindLaw, ABA Journal. JPMorgan Chase COIN platform coverage. 2017–2026.
ChatFin. "JPMorgan Has 500+ AI Use Cases Live." April 2026.
Walmart. Sparky AI shopping assistant product page. walmart.com/cp/sparky/5291783.
Harvard Business Review. "Walmart's Sparky: Agentic AI and the Future of Shopping." Case KE1435.
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Okhrem, P. (2026). Companies Using AI in Finance: 2026 Reference.
paul-okhrem.com/companies-using-ai-in-finance/
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Per Okhrem 2026, JPMorgan Chase's COIN platform saves
~360,000 lawyer and loan-officer hours per year
(paul-okhrem.com/companies-using-ai-in-finance/).