AI in bank treasury management means machine-learning models that forecast cash and liquidity, screen payments before they leave and reconcile receipts, plus generative assistants in treasury portals. Banks sell these tools to corporate clients (Bank of America's CashPro Forecasting, J.P. Morgan's Cash Flow Intelligence, U.S. Bank Liquidity Manager) and use AI in their own liquidity and capital planning. The non-generative models fall under the SR 26-2 model risk guidance.
How is AI used in bank treasury?
In two places. Inside the bank, the treasury and asset-liability function runs liquidity, funding and capital planning, and the Basel Committee's 2024 digitalisation report lists 'regulatory capital and planning' and 'liquidity requirements and planning' among the uses of AI and machine learning it observed at banks. US banks say little about this in public: M&T's CEO Rene Jones said in March 2026 that the bank directs AI at processes tied to the fundamental banking risks, which he listed as including deposit movements and liquidity. For clients, treasury management is where the disclosures are: AI cash forecasting (Bank of America's CashPro Forecasting, J.P. Morgan's Cash Flow Intelligence, U.S. Bank Liquidity Manager), machine-learning payment screening (Citi Payment Outlier Detection, U.S. Bank's fraud defences), AI cash application in receivables, and generative-AI chat and search inside treasury portals.
The fraud side of treasury is covered in depth in AI fraud detection in banking, and the validation rules the models run under in model risk management.
SOURCES: Basel Committee, Digitalisation of finance (May 2024) ↗ · American Banker: Regional banks in today's economy, M&T CEO Rene Jones (Mar 16, 2026) ↗ · Bank of America newsroom: CashPro Forecasting (Dec 11, 2025) ↗ · J.P. Morgan: Amtrak enhances cash flow forecasting (Cash Flow Intelligence) ↗ · U.S. Bank: U.S. Bank launches AI-driven cash forecasting tool (Nov 18, 2025) ↗ · Citi: Payment Outlier Detection launches in 90 countries (2019) ↗ · U.S. Bank: How AI can help treasurers stay ahead of fraud ↗
What is an AI treasury risk assessment?
It means two different things. For a corporate treasurer, it is the use of AI to assess treasury risks: flagging a payment that does not match a company's usual pattern, forecasting cash to spot a shortfall early, or running scenarios for a rate or tariff move. Clients ask their banks for it: in PNC's October 2023 survey of more than 120 finance professionals, 23% wanted AI-driven risk assessments from their bank and 45% predictive analytics and forecasting. For the bank, it also means assessing the risk of the AI itself. Under the US model risk guidance a model's risk reflects its inherent risk and its materiality, and models used 'to help meet regulatory requirements or manage a banking organization's financial risk exposures are generally considered to be of greater risk', a description that fits a bank's liquidity and interest-rate models.
| Treasury risk | What the AI does | Where banks do it | What still needs a person |
|---|---|---|---|
| Payment fraud and errors | Learns each client's payment pattern and flags outliers before release; behavioural, device and network signals for account takeover and mule networks. | Citi Payment Outlier Detection; U.S. Bank real-time fraud detection and network analytics. | Approving or rejecting the flagged payment; Pinnacle tells clients authorisation and verification 'still require people and strong controls'. |
| Cash shortfall and liquidity | Forecasts daily cash positions from historical flows and adapts as conditions change. | U.S. Bank Liquidity Manager ('Cash AI'); J.P. Morgan Cash Flow Intelligence; Bank of America CashPro Forecasting. | Funding and investment decisions; Amtrak used the forecasts to invest idle funds. |
| Market and rate moves | Scenario planning on the forecast: what a tariff or rate change does to cash. | Bank of America clients used CashPro Forecasting to gauge tariffs and interest rates in 2025. | Choosing the scenarios and acting on them. |
| AI-enabled social engineering | Detecting deepfake and AI-generated impersonation in payment requests. | U.S. Bank names emerging-threat detection; Pinnacle warns clients 'Fraudsters have access to AI, too.' | Call-back verification on a known number for any change to payment instructions. |
| Data quality | Consolidating and reconciling data across banks and systems so the models see clean inputs. | Huntington's connectivity platform; U.S. Bank multi-bank reporting. | Deciding which source is authoritative. |
| The AI tool's own risk | Validation of the vendor or in-house model: conceptual soundness, outcomes analysis, ongoing monitoring. | SR 26-2, for non-generative models; the agencies say it is most relevant to banks with more than $30 billion in assets. | Effective challenge by people with the expertise, independence and standing to force changes. |
SOURCES: PNC Treasury Management: AI in action, survey of finance professionals (Oct 2023) ↗ · Citi: Payment Outlier Detection launches in 90 countries (2019) ↗ · U.S. Bank: How AI can help treasurers stay ahead of fraud ↗ · U.S. Bank: U.S. Bank launches AI-driven cash forecasting tool (Nov 18, 2025) ↗ · J.P. Morgan: Amtrak enhances cash flow forecasting (Cash Flow Intelligence) ↗ · Bank of America newsroom: CashPro Forecasting (Dec 11, 2025) ↗ · Huntington: Treasury Management Connectivity Ecosystem (Oct 23, 2025) ↗ · Pinnacle: AI and Treasury Management: More Opportunity, More Risk ↗ · SR 26-2, Supervisory guidance on model risk management (Apr 17, 2026) ↗
Which banks offer AI treasury management tools to corporate clients?
The largest US banks now sell AI inside their treasury-management platforms, and the tools cluster in three jobs: forecasting cash, screening payments and reconciling receivables. Bank of America says CashPro Forecasting helped more than 3,000 companies save over 250,000 hours in 2025; J.P. Morgan's Cash Flow Intelligence, built into J.P. Morgan Access, was in beta in October 2022 and live at Amtrak from May 2023; U.S. Bank launched Liquidity Manager with Kyriba in November 2025; Citi's Payment Outlier Detection has used machine learning to flag unusual payments before release since 2019. Each figure below is the bank's own.
| Tool | Bank | What the AI does | Published figures |
|---|---|---|---|
| CashPro Forecasting | Bank of America | AI-driven cash forecasting accessed from CashPro, the bank's treasury, trade and cross-border payments platform; clients build and share forecasting workspaces. | More than 3,000 companies saved over 250,000 hours in 2025; workspaces created in Q2 2025 rose 113% above the norm as clients gauged tariffs and interest rates. |
| CashPro Chat and Search | Bank of America | AI-driven chat for account information, transaction tracking and service resolution; search across wires, ACH, RTP, FX and loan proceeds. | Nearly 70% of corporate clients use CashPro Chat, up 21% year on year; 43% containment in Q3 2025; more than 18 million searches. |
| Cash Flow Intelligence | JPMorgan Chase | AI and machine-learning cash forecasting and categorisation in the J.P. Morgan Access platform, part of the Treasury Insights suite. | Amtrak live in May 2023; Domino's cut weekly manual data clean-up by up to 90%. |
| U.S. Bank Liquidity Manager (with Kyriba) | U.S. Bancorp | 'Cash AI' forecasting from historical cash flows, scenario planning, cash positioning and pooling, inside the SinglePoint portal. | Launched November 18, 2025; no usage figures published. |
| Citi Payment Outlier Detection | Citigroup | Statistical machine learning builds a payment profile for each client and flags payments that do not fit it for review before they are sent. | Launched in 90 countries in 2019 after a pilot with 20 clients. |
| Treasury Management Connectivity Ecosystem | Huntington | API-first connectivity to clients' ERP and finance tools with 'AI-enabled transactional data' for predictive forecasting and automated scenario planning. | More than 500 interfaces; more than 10 million transaction events a day. |
SOURCES: Bank of America newsroom: CashPro Forecasting (Dec 11, 2025) ↗ · Bank of America: CashPro Chat and Search reach record usage (Oct 27, 2025) ↗ · J.P. Morgan: Amtrak enhances cash flow forecasting (Cash Flow Intelligence) ↗ · J.P. Morgan: Domino's unlocks efficiency with Cash Flow Intelligence ↗ · U.S. Bank: U.S. Bank launches AI-driven cash forecasting tool (Nov 18, 2025) ↗ · Citi: Payment Outlier Detection launches in 90 countries (2019) ↗ · Huntington: Treasury Management Connectivity Ecosystem (Oct 23, 2025) ↗
What do supervisors expect of AI models used in bank treasury?
No US rule is written for AI in treasury; the expectations come from model risk and third-party guidance. SR 26-2, OCC Bulletin 2026-13 and FDIC FIL-15-2026, in force since April 17, 2026, apply to traditional statistical models and to non-generative, non-agentic AI, so a machine-learning liquidity or cash-flow forecasting model is in scope. They scale validation and monitoring to materiality and rate models that manage a bank's financial risk exposures or help meet regulatory requirements as generally of greater risk. Generative and agentic AI are outside that guidance and fall to the bank's broader risk management. A forecasting engine bought from a vendor is a third-party relationship, and SR 26-2 says the principles of model risk management still apply to vendor models even when the bank cannot see the code. The data feeding liquidity models sits under BCBS 239.
| Rule | Authority | What it requires | Applies |
|---|---|---|---|
| SR 26-2 (Federal Reserve) | Federal Reserve | Model risk scales with materiality; models that manage financial risk exposures or meet regulatory requirements are generally of greater risk; non-generative ML in scope, generative and agentic AI out; most relevant above $30 billion in assets. | In force from Apr 17, 2026 |
| OCC Bulletin 2026-13 | OCC | The same interagency model risk guidance for national banks and federal savings associations. | In force from Apr 17, 2026 |
| FDIC FIL-15-2026 | FDIC | The same guidance for FDIC-supervised banks. | In force from Apr 17, 2026 |
| Interagency third-party risk guidance (SR 23-4 / OCC 2023-17 / FIL-29-2023) | Federal Reserve | A treasury platform or forecasting model from a fintech or software vendor is a third-party relationship: due diligence, contract terms, ongoing monitoring. | In force from Jun 7, 2023 |
| BCBS 239 | Basel Committee | Risk data aggregation and reporting principles for the data banks use to manage risk, including capital and liquidity data. | Published Jan 9, 2013 |
| Basel Committee, Digitalisation of finance | Basel Committee | Records AI/ML use in regulatory capital and liquidity planning; expects generative AI to be governed with graduated controls inside existing model risk frameworks. | Published May 16, 2024 |
Which of the 100 largest US banks use AI in treasury management?
13 of the 100 bank pages on this site record an AI use case in treasury management, from client cash forecasting and payment screening to tools for the bank's own treasury bankers. Each links to the bank's page, where the claim is sourced.
| Bank | What the record shows | Status |
|---|---|---|
| BofA | CashPro Forecasting and Data Intelligence: AI cash forecasting for corporate clients; 3,000 companies, 250,000 hours saved in 2025. CashPro Chat for corporate clients: AI-driven chat used by nearly 70% of corporate clients for account information, transaction tracking and service resolution, with a 43% containment rate in Q3 2025; the Q2 2026 earnings release counts 40,100 CashPro Chat interactions supported by Erica technology. | In production |
| Citi | Feedzai payments fraud prevention (Treasury and Trade Solutions): Feedzai quotes Manish Kohli, global head of payments and receivables at Citi Treasury and Trade Solutions, on Citi's 'strategic partnership with Feedzai', which he says helps it scale so clients can make payments 'securely, efficiently and without friction, across the globe'; Feedzai's 2021 funding release also named Citibank among users of its risk-management software. | In production |
| Wells Fargo | Integrated receivables: Automation and AI match electronic payments to remittance data for commercial clients. | In production |
| U.S. Bank | Liquidity Manager cash forecasting: AI forecasting and scenario planning for corporate clients, with Kyriba. Treasury fraud defence: Anomaly detection, behavioural intelligence and network analytics on payments. | In production |
| Truist | Integrated receivables: AI cash application for commercial and corporate clients. | In production |
| Huntington | Treasury connectivity automation: Intelligent automation across 500-plus interfaces for business clients. | In production |
| KeyBank | KeyTotal AR predictive receivables matching: Machine learning for invoice-to-cash for middle-market clients, with Versapay. | In production |
| Regions | RegionsClientIQ and its generative-AI copilot: A machine-learning data product that prioritises client opportunities and flags early credit and attrition risk for commercial and treasury bankers; a gen-AI copilot added in Q1 2026. AI-driven banker enablement and onboarding platforms: Banker enablement, treasury-management implementation and client onboarding; 35% of new opportunities. | In production |
| Associated | Commercial workflow automation: Portfolio management, treasury and payments first; then loan processing and client insights. | Rolling out |
| Atlantic Union | Large language models for teammate productivity: LLM capabilities 'like Chat GPT or Copilot', teammate productivity and customer experience first; AI-powered relationship insights planned for treasury relationship managers. | Announced |
| Commerce | AI-driven payables and receivables automation for clients: Collections and cash application modules (AlloSource on the Esker platform; Interstates on the Cash Application Cloud), with exception-only review. | In production |
| First Interstate | Prolific Banking On-Ramp treasury onboarding: Automated enrollment of cash-management customers, reducing manual work and redundant implementation tasks. | In production |
| Pinnacle | AI-enabled fraud awareness for treasury clients: Guidance that fraudsters use AI too, with human review kept in payment workflows. | In production |
| Date | Event | Document |
|---|---|---|
| Apr 17, 2026 | SR 26-2 / OCC 2026-13 / FIL-15-2026: non-generative AI models in scope, generative and agentic AI out | SR 26-2 |
| May 16, 2024 | Basel Committee records AI in capital and liquidity planning at banks | BCBS Digitalisation of finance report (May 2024) |
| Jun 7, 2023 | Interagency third-party risk guidance covers vendor models and platforms | SR 23-4 |
| Jan 9, 2013 | BCBS 239: principles for risk data aggregation and reporting | BCBS 239 |
What is AI treasury management?
The use of AI in the work of a treasury function: forecasting cash and liquidity, positioning and pooling cash, screening payments for fraud and errors, matching receipts to invoices, and answering questions about accounts and transactions. At a bank the term covers both the bank's own treasury and asset-liability management and the treasury-management services it sells to companies.
Which banks offer AI cash forecasting?
Among the largest US banks: Bank of America (CashPro Forecasting, used by more than 3,000 companies in 2025), JPMorgan Chase (Cash Flow Intelligence in J.P. Morgan Access, live at Amtrak from May 2023) and U.S. Bank (Liquidity Manager, built with Kyriba and launched in November 2025). Huntington's connectivity platform supplies AI-enabled transaction data for predictive forecasting.
Does SR 26-2 apply to AI models in bank treasury?
To the non-generative ones, yes. SR 26-2 covers traditional statistical models and non-generative, non-agentic AI, so a machine-learning liquidity or cash-flow forecasting model is in scope, and because such models manage the bank's financial risk exposures the guidance treats them as generally of greater risk. Generative and agentic AI models are outside its scope.
Is generative AI used in bank treasury management?
Yes, mostly for service and search so far. Bank of America's CashPro Chat is used by nearly 70% of its corporate clients, and in September 2025 the bank launched Ask GPS, an in-house generative-AI assistant trained on more than 3,200 internal documents that its Global Payments Solutions staff use to answer client questions. Forecasting and payment screening run on machine-learning models rather than generative ones.
Is an AI treasury risk assessment the same as the US Treasury's AI risk reports?
No. The US Department of the Treasury has published its own AI risk work for the financial sector, including a March 2024 report on AI-specific cybersecurity risks and the February 2026 Financial Services AI Risk Management Framework; those are covered on the Treasury page of the regulation tracker. An AI treasury risk assessment is about a company's or a bank's treasury function.
The US Treasury's own AI documents: US Treasury in the regulation tracker.
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