NASDAQ
Get email alerts
New customer deployments for NASDAQ, straight to your inbox. No account needed.
NASDAQ has 4 source-linked AI deployments documented in AIUseCaseHub, across 1 industry and 1 country.
4
1
1
Hyperscaler mix
See whether NASDAQ's cases are powered by Microsoft, AWS, GCP, or multiple providers.
How NASDAQ builds AI
Build / Buy / Compose across this company's documented cases
4 of 4 cases classified (100%) · Compare all use-case types
Use case portfolio
Use case types at NASDAQ
Risk assessment leads with 2 of 4 documented cases; 3 distinct types appear across the visible portfolio.
Reported outcomes
2 cases report measurable results
−60%
Time & speed
median · 3 metrics
+97%
Quality & accuracy
median · 1 metric
Medians of results published in NASDAQ cases, normalized for comparability. See all benchmarks →
Evidence persistence
1 of 1 judgeable case is still publicly referenced · 1 show the organization expanding AI use.
Durability of public evidence, not whether systems remain in production. How this is measured →
Technology snapshot
What NASDAQ uses across visible cases
18 named technologies are mentioned across 4 cases, led by Amazon Bedrock.
Capability mix
No capability flags are attached to these cases yet.
Technologies mentioned
All Use Cases (4)
Nasdaq: generative AI to improve market surveillance and fraud/AML workflows on AWS
Nasdaq implemented AWS generative AI to improve market surveillance for regulators and marketplaces globally.The solution streamlines triage and examination, helping clients more effectively monitor and detect potential market manipulation and insider dealing.The source also describes additional capital-markets applications for anti-money laundering, fraud prevention, and Entity Research Copilot workflows at Nasdaq Verafin.
Nasdaq integrated Microsoft Foundry and Azure OpenAI for AI-powered document summarization and workflow automation in Boardvantage
Nasdaq re-architected its Boardvantage platform on Azure, using Azure Kubernetes Service and Azure Database for PostgreSQL/Azure Database for MySQL as the data foundation.Microsoft Foundry and Azure OpenAI were integrated to provide AI-powered document summarization and workflow automation for board materials.
Financial institutions advance mission-critical workloads and Agentic AI at re:Invent 2025
At AWS re:Invent 2025, multiple financial institutions including NASDAQ, Visa, National Australia Bank, BlackRock, and Allianz Technology SE showcased advanced implementations of AI agents and mission-critical cloud workloads using AWS technologies.Financial institutions are rapidly shifting from debating AI adoption to deploying agentic AI for competitive advantage, with developer productivity significantly improved.Use cases showcased include real-time trading assistants, fraud detection, claims processing, compliance automation, and customer service enhancements using Amazon Bedrock AgentCore and other AWS AI tools.AWS provided enhanced infrastructure and service capabilities such as multi-region resiliency, data masking, catalog federation, and Amazon Nova Forge for custom frontier models.Several financial institutions demonstrated multi-agent architectures to automate insurance claims and customer service workflows, reducing processing times by up to 80%.Advanced AI agents are integrated with policy controls for regulatory compliance and auditability, supporting trading, payments, and wealth management applications.AWS innovations like Amazon Connect enhancements and AI-powered recommendations enable personalized customer experiences and operational efficiencies.
Automated Reasoning Checks in Amazon Bedrock Guardrails for Financial Services
AWS Financial Services customers like NASDAQ, State Bank of India, and Bridgewater use Amazon Bedrock Guardrails Automated Reasoning checks to enhance transparency and compliance in financial workflows involving foundation models.Automated Reasoning checks provide deterministic validation of generative AI outputs against logical rules encoded from source documentation, reducing risk of hallucinations.Use cases include insurance underwriting rule validation, legal triaging of claims, and claims processing, with audit trails and mathematical proof ensuring regulatory compliance and trust.This deterministic approach supports reproducible decision support, improves confidence in AI outputs, and safeguards regulated financial workflows against inaccuracies.
Ask the analyst
A question about NASDAQ the page doesn't answer? I read every one — the good ones get answered here.