What should a bank look for in AI data and analytics software?
AI data and analytics software for banks is the data layer under machine-learning models and AI agents: consumer, credit and identity data from bureaus and data companies, entity resolution that links customers and counterparties across systems, and decision-intelligence platforms that build analytics and workflows on the bank's own data. Banks buy it on sales-led enterprise licences or subscription and per-transaction contracts. The questions that separate vendors are data lineage, entity-resolution quality, where the data lives, and how vendor data and models pass the bank's model validation.
What is AI data and analytics software for banks?
AI data and analytics software for banks is what supplies, links and prepares the data that machine-learning models and AI agents decide on. The vendors on this page fall into three kinds: data companies that supply external consumer, credit, identity and risk data with analytics and decisioning software around it (Experian, LexisNexis Risk Solutions); decision-intelligence platforms that unify the bank's internal and external data, resolve entities and build analytics and workflows on top (Quantexa, Palantir); and a fraud and AML platform that aggregates first- and third-party data and scores events with machine learning, device intelligence and a knowledge graph (DataVisor). Each vendor page lists its products, pricing notes and the banks named as customers, with sources.
Is a cloud data platform the same as an AI data vendor?
No. A cloud data platform such as Databricks or Snowflake hosts and processes the bank's own data and the models it trains on it; the bank brings the data. A data vendor supplies data the bank does not have: Experian sells credit data alongside its Ascend analytics platform, and LexisNexis Risk Solutions sells fraud, identity and financial-crime compliance data such as device and digital-identity risk scoring and sanctions screening. Decision-intelligence vendors work across both: Quantexa resolves entities and builds networks across internal and external data, and Palantir's Foundry and AIP integrate a customer's data and connect AI models to it. DataVisor applies machine learning to first- and third-party data for fraud and AML decisions. Many banks use a platform and several data vendors at once.
Which large banks use Databricks?
On the public record as of Nov 3, 2026, 9 of the 141 large banks profiled have a dated, sourced profile entry naming Databricks (a use case, a timeline move, a platform note or a vendor-page customer record). Ranked by entries naming Databricks, the top 5 are OceanFirst (9 entries), First Horizon (4 entries), Capital One (4 entries), Standard Chartered (3 entries) and Barclays (2 entries). OceanFirst's strongest evidence: AI through existing vendor relationships — the named stack covers Microsoft, Databricks, kore.ai, Five9 and MagicMirror, and the Q2 2026 10-Q lists dependence on… (use case, in production, Aug 7, 2026).
| # | Bank | Entries naming Databricks | Strongest entry | Date | Sources |
|---|---|---|---|---|---|
| 1 | OceanFirst | 9 | AI through existing vendor relationships — the named stack covers Microsoft, Databricks, kore.ai, Five9 and MagicMirror, and the Q2 2026 10-Q lists dependence on… (use case, in production, Aug 7, 2026) | Aug 7, 2026 | Investing.com ↗ · OceanFirst Financial Corp. (SEC filings) ↗ |
| 2 | First Horizon | 4 | Agentic layer on the Databricks data platform (use case, rolling out, Sep 15, 2026) | Sep 15, 2026 | Databricks ↗ |
| 3 | Capital One | 4 | Databolt Connect on Databricks Marketplace (move, Jun 16, 2026) | Jun 16, 2026 | Business Wire via FT Markets ↗ · Capital One Software ↗ |
| 4 | Standard Chartered | 3 | AI Factory and the single enterprise AI platform (with SC GPT) — At its May 2026 investor event the CEO said the bank 'took the step back two years ago to build a core AI platform… (platform, Oct 5, 2026) | Oct 5, 2026 | Standard Chartered PLC ↗ · Standard Chartered PLC ↗ |
| 5 | Barclays | 2 | Databricks (section, Oct 14, 2026) | Oct 14, 2026 | Databricks ↗ · Databricks ↗ |
| 6 | RBC | 2 | Capital Markets AI team: over 20 people, $19.8 million budget — American Banker profiles Grubert, whose team of over 20 people spans engineering, product, strategy and governance… (move, Jun 1, 2026) | Jun 1, 2026 | American Banker ↗ · FinAi News via ABA ↗ |
| 7 | City National | 2 | RBC Capital Markets AI head describes Aiden's build and partners — Databricks cited for governed genAI (move, May 4, 2026) | May 4, 2026 | FinAi News via ABA ↗ |
| 8 | Barclays US | 2 | 20-F names the group AI platform and technology partners — Reports about 100,000 Copilot licences, a Barclays AI platform, AWS, Microsoft, GitLab and Databricks as partners, AI… (move, Feb 10, 2026) | Feb 10, 2026 | SEC (Barclays PLC 20-F) ↗ |
| 9 | Synchrony | 1 | Illinois datathon uses Synchrony call-centre data — the contest banned AI tools and was sponsored by Synchrony, Databricks and AWS (move, Mar 27, 2026) | Mar 27, 2026 | University of Illinois Urbana-Champaign, Office of Data Science Research ↗ |
9 of the 141 profiled banks; the 9 highest are shown. Full ranking and method: Which large banks use Databricks? (Checked 2026-11-03 · bank profiles).
Which large banks use Snowflake?
On the public record as of Nov 3, 2026, 9 of the 141 large banks profiled have a dated, sourced profile entry naming Snowflake (a use case, a timeline move, a platform note or a vendor-page customer record). Ranked by entries naming Snowflake, the top 5 are Truist (5 entries), National Bank Holdings (5 entries), FNBO (3 entries), Northern Trust (3 entries) and Morgan Stanley (2 entries). Truist's strongest evidence: Qlik and Snowflake data pipeline for AI (use case, in production, Feb 24, 2026).
| # | Bank | Entries naming Snowflake | Strongest entry | Date | Sources |
|---|---|---|---|---|---|
| 1 | Truist | 5 | Qlik and Snowflake data pipeline for AI (use case, in production, Feb 24, 2026) | Feb 24, 2026 | SiliconANGLE ↗ · Truist Financial (SEC filing) ↗ |
| 2 | National Bank Holdings | 5 | 2UniFi vendor and cloud stack — John Finn named Finxact, Visa and Marqeta (as transcribed) as architecture partners and Snowflake and Microsoft Azure… (use case, in production, Feb 24, 2026) | Feb 24, 2026 | earnings call transcript (The Motley Fool) ↗ · National Bank Holdings Corporation (SEC filing) ↗ |
| 3 | FNBO | 3 | Partner dashboards with row-level security — Amazon QuickSight dashboards on a Snowflake warehouse let each of more than 90,000 users see only their own partner data (use case, in production, Dec 9, 2024) | Dec 9, 2024 | AWS Business Intelligence Blog (guest post by FNBO) ↗ |
| 4 | Northern Trust | 3 | Open Semantic Interchange and the data foundation — In June 2026 it became a founding member of the Financial Services Working Group of Open Semantic Interchange (OSI)… (platform, Jun 9, 2026) | Jun 9, 2026 | Northern Trust ↗ · Northern Trust ↗ |
| 5 | Morgan Stanley | 2 | Snowflake named strategic partner of the year (move, Sep 18, 2025) | Sep 18, 2025 | Snowflake (Business Wire) ↗ |
| 6 | USAA | 2 | CIO Dive: three-year push to a unified cloud data estate — Bajaj, who joined USAA about three years earlier, describes migrating warehouse and analytics environments from… (move, Jul 17, 2024) | Jul 17, 2024 | CIO Dive ↗ |
| 7 | Commonwealth Bank | 1 | Agentic fraud system deployed — built in three months on Snowflake and the bank's cloud core banking platform (move, Apr 24, 2026) | Apr 24, 2026 | Commonwealth Bank of Australia ↗ · Finextra ↗ |
| 8 | State Street | 1 | Snowflake (section, Oct 1, 2024) | Oct 1, 2024 | State Street ↗ |
| 9 | Capital One | 1 | Capital One Software launches with Slingshot — first product manages Snowflake cost and governance after 27% in-house savings (move, Jun 1, 2022) | Jun 1, 2022 | Capital One ↗ · Forbes ↗ |
9 of the 141 profiled banks; the 9 highest are shown. Full ranking and method: Which large banks use Snowflake? (Checked 2026-11-03 · bank profiles).
Observations from how these products are sold and regulated, not advice.
01
Data lineage and provenance
A model is only as defensible as the record of where its inputs came from. Ask whether each field a vendor supplies or derives can be traced to its source, with collection dates, consent basis and transformations, and whether that lineage can be exported into the bank's own data catalogue.
02
Entity resolution across sources
Customer, counterparty and beneficial-owner records rarely match across core, card, payments and external data. Ask how the vendor links records, how it measures match precision and recall, whether a person can see and override why two records were joined, and on whose data the accuracy figures were measured.
03
Where the data lives
Some products run in the vendor's cloud, some inside the bank's own cloud tenancy or data platform, and some on premises. Check which data leaves the bank, which jurisdictions it is stored and processed in, what the vendor may reuse to train its own models or enrich a shared network, and how data is returned or deleted at exit.
04
Model-ready features or raw data
A vendor may deliver raw records, engineered features and scores, or finished decisions. Features and scores save build time but put more of the model inside the vendor; raw data leaves more work, and more control, with the bank's own modellers.
05
Pricing by data volume, transaction or seat
Data vendors usually charge per record, per call or per transaction; platforms by licence, compute or user. Few publish prices. Model the cost at next year's data volume and query rate, including the fees for each new data source or integration.
06
How vendor data feeds model validation
Validators need to test a model's inputs, not only its outputs. Ask what documentation the vendor gives on data definitions, coverage, missing values and changes over time, how it notifies customers of a change to a data feed or score, and whether its own models come with a validation package.
Which rules apply to a bank using AI data and analytics software?
| Rule | Why it applies | Documents |
|---|---|---|
| BCBS 239 risk data aggregation | The Basel Committee's 14 principles set governance, accuracy, completeness and timeliness expectations for risk data at systemically important banks; its January 2026 newsletter says data lineage is still hard because of legacy and distributed systems, and that AI depends on high-quality data. | BCBS 239 BCBS 239 Implementation Newsletter (Jan 2026) |
| Model risk management (SR 26-2 / OCC 2026-13 / FIL-15-2026) | The April 2026 guidance defines a model as a method that processes input data into estimates and covers vendor and third-party models: a bank is expected to understand and validate purchased models and scores, including the data behind them. Generative and agentic AI are outside its scope. | SR 26-2 OCC Bulletin 2026-13 FDIC FIL-15-2026 |
| Third-party risk management | Licensing external data or a data platform is a third-party relationship under the 2023 interagency guidance: due diligence, contract terms on data use and ownership, ongoing monitoring and exit planning. | OCC Bulletin 2023-17 SR 23-4 FDIC FIL-29-2023 |
| FCRA where consumer-report data drives a decision | When bureau or other consumer-report data contributes to declining or repricing credit, the lender must give an adverse-action notice naming the reporting agency and, where a credit score is used, its key factors. | FCRA adverse action and credit-score disclosures (15 U.S.C. 1681m, 1681g(f)) |
| EU AI Act data governance | For high-risk uses such as credit scoring of people in the EU, Article 10 requires training, validation and testing data to meet data-governance and quality duties, and deployers must monitor the system and keep its logs. | Regulation (EU) 2024/1689 |
Documents link to the Regulation tracker. By use case: Model risk management · Third-party & vendor AI · Data & privacy · Credit scoring & underwriting · AML / KYC.
How do the AI data and analytics vendors compare?
| Vendor | What it does | Deployment | Pricing model | Published price | US bank customers* | Founded · ownership |
|---|---|---|---|---|---|---|
| LexisNexis Risk Solutions | Fraud, identity and financial-crime compliance data and analytics: ThreatMetrix, Emailage, IDVerse, Bridger Insight XG and Firco. | API and SaaS platforms (Dynamic Decision Platform, cloud-based RiskNarrative), sold direct and through partners | Subscription or transactional (volume-based) contracts, sold direct and through partners | Not published | 3 | 2008 · Wholly owned business of RELX PLC, which reports it as its Risk segment |
| DataVisor | Real-time fraud and AML decisioning platform using unsupervised machine learning, rules, device intelligence and Vera AI agents. | SaaS (cloud-based, multi-tenant); also pre-integrated into partner core and digital-banking platforms (DCI, Nymbus, VeriPark) | Sales-led enterprise SaaS contracts, sold directly or bundled through core and digital-banking partners; bought through a demo and proof of concept | Not published | 1 | 2013 · Private |
| Quantexa | Decision Intelligence platform: entity resolution and network analytics for AML, KYC and fraud; Cloud AML SaaS for US mid-size banks. | Enterprise platform licence; SaaS editions run on Microsoft Azure (Cloud AML) and as a Microsoft Fabric workload (Quantexa Unify) | Sales-led enterprise licensing (Quantexa reports 'license revenue'); Cloud AML is sold as SaaS, including through Azure Marketplace | Not published | 2 | 2016 · Private |
| Palantir (Foundry and AIP) | Data and AI platforms (Foundry, AIP) that banks configure for onboarding, KYC, customer data and anti-financial-crime work. | Platform licence (Foundry, AIP), deployable in almost any environment through Apollo, often with Palantir engineers embedded | Negotiated enterprise platform contracts, typically delivered with Palantir engineers embedded in the customer's team | Not published | 2 | 2003 · NASDAQ: PLTR |
| Experian | Credit bureau and decisioning software vendor: Ascend analytics platform, PowerCurve decisioning, CrossCore fraud and identity checks. | SaaS and APIs (Ascend Platform hosted in a hybrid-cloud environment; CrossCore is a cloud fraud and identity platform) | Sales-led enterprise contracts for decisioning, fraud and analytics software and data, quoted per client | Not published | 1 | 1996 · LSE: EXPN |
* Banks among the 120 largest US banks on this site publicly named as customers, each sourced on the vendor's page. Prices are shown only where the vendor publishes them for the AI product itself; a price for another product (a credit score, a notary plan, contact-centre seats) is listed on the vendor's page, not here. More vendors in this category are being researched.
What does each data and analytics platform sell, and who owns it?
From the vendor pages, where each fact is sourced. Products are those the vendor lists as generally available.
| Platform | How it is sold | AI products (generally available) | Founded | Ownership and funding |
|---|---|---|---|---|
| LexisNexis Risk Solutions | Sells banks fraud, identity and financial-crime compliance data and decision tools (device and digital-identity risk scoring, email and document checks, sanctions and transaction screening) on subscription or per-transaction contracts, largely built through acquisitions. | LexisNexis ThreatMetrix; LexisNexis Dynamic Decision Platform; Emailage and Emailage Adaptive; LexisNexis IDVerse; BehavioSec behavioral biometrics; Bridger Insight XG; Firco Continuity and WorldCompliance; RiskNarrative; Credit risk solutions | 2008 | Wholly owned business of RELX PLC, which reports it as its Risk segment; RELX shares trade in London (REL), Amsterdam (REN) and New York (RELX). Risk revenue was £3,485 million in 2025, about 36% of RELX revenue. |
| DataVisor | Sells banks, credit unions, card issuers and payment companies a cloud fraud and AML platform that combines unsupervised machine learning, a rules engine, device intelligence and case management, sold directly and pre-integrated through core and digital-banking providers, and since 2026 driven by conversational AI agents (Vera). | Fraud and risk platform; AML solution and AI SAR filing; Vera AI agents; Vera Code; dEdge device intelligence and Identity Graph; Sponsor-bank (BaaS) solution | 2013 | Private; backed by Brighton Park Capital (led a $40 million strategic growth investment in December 2022, with NewView Capital and GSR Ventures), Sequoia China (led the $40 million Series C in 2018), New Enterprise Associates and GSR Ventures. No valuation has been disclosed in DataVisor's releases. |
| Quantexa | Sells banks, insurers and governments a Decision Intelligence platform that resolves entities and builds networks across internal and external data for AML, KYC and fraud work, adding a packaged Azure SaaS AML product for US mid-size and community banks (2025) and agentic AI features (2025-2026). | Decision Intelligence Platform (Quantexa AI); Quantexa Cloud AML; Q Assist; Agent Gateway; Quantexa Unify for Microsoft Fabric; Quantexa News Intelligence | 2016 | Private; valued at $2.6 billion after a $175 million Series F in March 2025 led by Teachers' Venture Growth (Ontario Teachers' Pension Plan), with board representation from Warburg Pincus, Dawn Capital, BNY, Evolution Equity Partners, AlbionVC and HSBC. In August 2026 its CEO told Reuters it was considering a UK or US listing but had not decided when, and could remain private. |
| Palantir (Foundry and AIP) | Sells data-integration and AI platforms with its own engineers embedded at the customer, who build onboarding, KYC, anti-financial-crime and customer-data workflows on the bank's own data and systems. | Palantir Foundry; Palantir AIP; Anti-money laundering offering; Palantir Apollo | 2003 | Public (NASDAQ: PLTR since November 2024, after moving its listing from the NYSE); co-founder Alexander Karp has been chief executive since 2005. |
| Experian | Sells banks credit data plus decisioning, fraud and analytics software, increasingly through the cloud Ascend Platform, to which it has added generative and agentic AI tools since 2024. | Experian Ascend Platform; Ascend Analytical Sandbox and Ascend Ops; PowerCurve decisioning; CrossCore (with Precise ID and NeuroID); Experian Assistant; Experian Assistant for Model Risk Management; Agent Operating System; Financial Crime Compliance Perpetual Monitoring (UK) | 1996 | Public company listed on the London Stock Exchange (EXPN) and a FTSE 100 constituent since it demerged from GUS on 10 October 2006; corporate headquarters in Dublin, Ireland. |
Which banks use these data and analytics platforms?
9 banks with a profile on this site are named publicly as customers of the 5 data and analytics vendors above, in 9 entries; each naming is sourced on the vendor's page, and a vendor's own claim is marked as such there. Being named is not the same as running the product for credit decisions: the "what" column says what the source describes.
| Bank | Vendor | What the source describes | Status | Source date |
|---|---|---|---|---|
| Cathay Bank | LexisNexis Risk Solutions | Sanctions and AML screening: Cathay Bank's 2025 Wolfsberg questionnaire names LexisNexis Bridger Insight and Compliance Link as its vendor tools, run as a combination of automated and manual review. | In production | May 8, 2025 |
| City National | LexisNexis Risk Solutions | Sanctions screening: City National Bank's 2026 Wolfsberg questionnaire names ACI Money Transfer System and LexisNexis Bridger Insight as the vendor tools it uses, alongside internal systems, for automated sanctions screening. | In production | Sep 3, 2026 |
| EverBank | LexisNexis Risk Solutions | Fraud protection and risk decisions: EverBank's COO listed LexisNexis among vendors 'already put in place, or are just about to put in place' in July 2024; the product is not named. | Selected | Jul 16, 2024 |
| SoFi | DataVisor | Payments fraud and risk: Galileo, SoFi's payments-platform subsidiary (now SoFi Tech Solutions), built its Payment Risk Platform jointly with DataVisor in 2022 and is named as a DataVisor customer; in October 2026 a SoFi Tech Solutions payments-risk director described using DataVisor's Vera AI agents. | In production | Oct 20, 2026 |
| BNY | Quantexa | Data unification, entity resolution, master data management and graph analytics ('data fabric') across the bank since a 12-month engagement before its 2021 investment; an early adopter of the Q Assist generative AI copilot in 2024. Not described as an AML deployment. | In production | May 14, 2026 |
| Morgan Stanley | Quantexa | Entity Resolution technology that builds a unified view of customer and contact data across the firm, deduplicating records in an automated mode and a steward-reviewed mode; Morgan Stanley's head of integrated firmwide client intelligence is quoted, and Morgan Stanley gave Quantexa its 2026 Innovation Award for the work. | In production | Sep 30, 2026 |
| Customers Bank | Palantir (Foundry and AIP) | Foundry and AIP to rebuild deposit onboarding (document collection, entity verification, risk-signal aggregation), with Palantir engineers embedded beside the bank's AI and technology teams | Announced | Oct 16, 2026 |
| Citi | Palantir (Foundry and AIP) | Citi Wealth: per Palantir only, a Global Federated Customer Master built with Palantir for agentic account-opening, KYC and servicing workflows, with account opening cut from nine days to seconds (vendor-reported); Citi itself says only that its wealth data team is working with Google Cloud and Palantir on simplifying account opening, and has not said the build is live | Announced | Oct 26, 2026 |
| Santander | Experian | Fraud prevention for new-account application review and the Ascend Platform at Santander Bank, a relationship Experian says began nearly a decade before its February 2026 case study. | In production | Feb 18, 2026 |
Ranked from the bank records: which large banks lead in AI credit underwriting and AI and fair lending. Model validation: SR 11-7 and what SR 26-2 changed.
NYSE: RELX · founded 2008
LexisNexis Risk Solutions
Sells banks fraud, identity and financial-crime compliance data and decision tools (device and digital-identity risk scoring, email and document checks, sanctions and transaction screening) on subscription or per-transaction contracts, largely built through acquisitions.
Banks among the 120: Cathay Bank, City National, EverBank
Private · founded 2013
DataVisor
Sells banks, credit unions, card issuers and payment companies a cloud fraud and AML platform that combines unsupervised machine learning, a rules engine, device intelligence and case management, sold directly and pre-integrated through core and digital-banking providers, and since 2026 driven by conversational AI agents (Vera).
Banks among the 120: SoFi
Private · founded 2016
Quantexa
Sells banks, insurers and governments a Decision Intelligence platform that resolves entities and builds networks across internal and external data for AML, KYC and fraud work, adding a packaged Azure SaaS AML product for US mid-size and community banks (2025) and agentic AI features (2025-2026).
Banks among the 120: BNY, Morgan Stanley
NASDAQ: PLTR · founded 2003
Palantir (Foundry and AIP)
Sells data-integration and AI platforms with its own engineers embedded at the customer, who build onboarding, KYC, anti-financial-crime and customer-data workflows on the bank's own data and systems.
Banks among the 120: Customers Bank, Citi
Who are the leading AI data vendors for financial institutions?
This page compares only vendors with sourced pages on this site: Experian (credit data with the Ascend analytics platform, PowerCurve decisioning and CrossCore fraud and identity checks), LexisNexis Risk Solutions (fraud, identity and financial-crime compliance data, including ThreatMetrix and Bridger Insight XG), Quantexa (a Decision Intelligence platform built on entity resolution and network analytics), Palantir (the Foundry data-operations platform and AIP) and DataVisor (a real-time fraud and AML platform that aggregates first- and third-party data). Cloud data platforms such as Databricks and Snowflake are counted on the bank pages instead; the banks that name them are listed in a separate table on this page. No ranking is implied.
How is AI data software priced?
None of the five vendors compared here publishes prices. Their pages describe sales-led enterprise contracts, subscription or per-transaction (volume-based) contracts, and negotiated platform licences. The comparison table shows a published price only where the vendor's own site lists one; otherwise it says 'Not published'.
Is bank data for AI covered by BCBS 239?
BCBS 239 covers risk data aggregation and risk reporting, not AI as such, and binds systemically important banks through their supervisors. Data that feeds risk models and risk reports falls within it, and the Basel Committee's January 2026 implementation newsletter says AI and automation depend on the high-quality, traceable data the principles require.
Does a data vendor's model fall under SR 26-2?
Yes, where it is a model in the guidance's sense: a quantitative method that turns input data into estimates, such as a credit, fraud or identity score. SR 26-2, OCC Bulletin 2026-13 and FDIC FIL-15-2026 expect a bank to understand and validate vendor models it relies on, in line with third-party risk management. Raw data is not itself a model, but its quality is part of validating the models it feeds. Generative and agentic AI are outside the guidance's scope.
Which AI data and analytics vendors are compared here?
LexisNexis Risk Solutions (Fraud, identity and financial-crime compliance data and analytics: ThreatMetrix, Emailage, IDVerse, Bridger Insight XG and Firco); DataVisor (Real-time fraud and AML decisioning platform using unsupervised machine learning, rules, device intelligence and Vera AI agents); Quantexa (Decision Intelligence platform: entity resolution and network analytics for AML, KYC and fraud; Cloud AML SaaS for US mid-size banks); Palantir (Foundry and AIP) (Data and AI platforms (Foundry, AIP) that banks configure for onboarding, KYC, customer data and anti-financial-crime work); Experian (Credit bureau and decisioning software vendor: Ascend analytics platform, PowerCurve decisioning, CrossCore fraud and identity checks). Each has its own page with products, pricing, ownership and the banks among the 120 largest US banks that are named as customers. More vendors in this category are being added as their pages are researched and sourced.
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