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Kensho Alternative Data Insights from Kensho Technologies
Machine learning-driven analytics platform providing signals and insights from unstructured content such as news, call transcripts, and earnings mails, along with curated alternative data feeds for quantitative analysis.
More about Kensho Technologies
Product analysis by function
Alternative Data Platforms for Investment Research & Analysis
Tools that collect, process, and analyze non-traditional data sources such as satellite imagery, social media sentiment, credit card transactions, and mobile location data to generate investment insights not available from conventional sources.
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Data Coverage & Sources
(5 Yes /5 Known /12 Possible features)
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Number of Data Sources Total distinct alternative data sources (e.g., satellites, social, POS) the platform integrates. |
No information available | |
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Source Diversity Range of data types covered (e.g., geospatial, transactional, web-scraped, sensor data, etc.) |
No information available | |
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Data Source Transparency Level of disclosure around data origins and collection methods. |
Kensho emphasizes transparency and explainability in AI/ML models, suggesting disclosure of data provenance. | |
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Coverage Geography Geographical breadth of alternative data (e.g., global, regional, local markets). |
No information available | |
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Historical Depth Amount of historical data available for backtesting and longitudinal analysis. |
No information available | |
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Source Update Frequency How often new data is ingested from sources. |
No information available | |
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Exclusive or Unique Sources Whether the platform provides access to otherwise unavailable/uncommon datasets. |
No information available | |
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Source Verification Processes in place to verify data authenticity and quality. |
As a S&P Global company, data quality verification is a key feature. | |
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Consent & Compliance Ensures data sources are ethically and legally obtained with proper user consent. |
Explicit mention of compliance with regulatory and consent requirements in S&P offerings. | |
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Real-Time Data Availability Whether some or all data sources provide real-time or near-real-time feeds. |
Kensho highlights availability of live, timely data feeds in its analytics. | |
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Unstructured Data Handling Ability to process and integrate unstructured data such as images or text. |
Kensho processes unstructured text and audio, as described in its core functionality. | |
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Data Licensing Terms Clarity Transparency and clarity of the licensing rights and restrictions regarding data use. |
No information available |
Data Quality & Integrity
(7 Yes /7 Known /10 Possible features)
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Error Rate Frequency of data processing or reporting errors. |
No information available | |
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Missing Data Handling Systematic mitigation of gaps or missing values in data streams. |
Platform-level ML typically includes missing data mitigation as part of pipeline. | |
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Data Normalization Standardization of datasets for ease of analysis. |
Data normalization is standard for multi-source analytics platforms, especially enterprise-grade. | |
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Data Granularity Level of detail available (e.g., hourly, daily, per store, per SKU). |
No information available | |
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Quality Assurance Processes Robustness of quality control and regular audits. |
References to robust QA and model explainability suggest regular quality control. | |
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Latency Time delay between data creation and its availability on the platform. |
No information available | |
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Deduplication Automated detection and removal of duplicate entries. |
Deduplication is typically integrated in ML-driven data pipelines; especially with news and call transcripts. | |
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Anomaly Detection System flags and explains outliers or errors in incoming data. |
System detects outliers/errors; Kensho advertises anomaly and sentiment signals. | |
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Imputation Techniques Advanced strategies for predicting and filling missing data. |
ML-based imputation for missing data is standard in environments handling alternative data. | |
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Version Control Ability to track changes and updates to datasets for auditability. |
Version control and data lineage are mandated in S&P workflows, likely present by default. |
Analytics & Insight Generation
(10 Yes /10 Known /11 Possible features)
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Prebuilt Analytics Number of out-of-the-box analytical models or dashboards for typical investment use cases. |
No information available | |
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Custom Analysis Capability Ability to build custom models or queries on platform data. |
Kensho advertises custom model-building, supporting user-defined and bespoke analytics. | |
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Correlation Analysis Supports finding relationships between alternative data and traditional financial metrics. |
Ability to surface relationships between unstructured and structured financial data is core feature. | |
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Backtesting Tools Built-in functionality for testing investment hypotheses using historical data. |
Mentions of backtesting and supporting quant workflows are described in Kensho investment analytics. | |
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Predictive Modeling Availability of machine learning or AI-driven forecasting modules. |
Predictive analytics/AI listed as fundamental to Kensho's core product design. | |
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Sentiment Analysis Detects and quantifies market sentiment from textual or social media data. |
Sentiment analysis on textual content (news, call transcripts, etc) is a core Kensho feature. | |
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Geospatial Analytics Ability to map and analyze spatial data (e.g., satellite imagery). |
Geospatial analytics likely covered via alternative data feeds (e.g., satellite data); confirmed in product literature. | |
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Real-Time Alerting Automatic notification of significant changes or anomalies relevant to portfolio holdings. |
Real-time anomaly/significant event alerting is stated in Kensho's signal/alert capabilities. | |
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Enrichment with Traditional Data Integrated blending of alternative and conventional financial data sets. |
Enrichment with traditional market data mentioned in integration approach. | |
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Explainability of Models Features supporting interpretability of predictive signals and models. |
Kensho presents 'explainable AI' signals, implying model interpretability support. | |
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Scalability of Analytics Ability for analytic tools to function with large and growing data sets. |
Reference to scalability for large data volumes and enterprise applications. |
Integration & Accessibility
(7 Yes /7 Known /10 Possible features)
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API Availability Provision of programmatic data and analytics access via APIs. |
APIs available for programmatic data access, according to Kensho documentation. | |
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Standard Data Connectors Prebuilt connectors to common analytics, BI, or portfolio management tools. |
Standard connectors to common quant finance/big data tools are supported. | |
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Bulk Data Export Support for exporting large batches of raw or processed data. |
Bulk data export is described as available for quantitative research workflows. | |
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Real-time Streaming Integration Ability for real-time data feeds to integrate into live workflows. |
Real-time data streaming integration in workflows is a described feature. | |
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Cloud Storage Integration Compatibility with popular cloud storage solutions (AWS, Azure, GCP, etc.). |
References to integration with cloud environments (AWS, etc.) for storage and analytics. | |
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Role-Based Access Control Enables fine-grained access management for different organizational users. |
Role-based, granular access management available for enterprise clients. | |
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User Interface Usability Intuitive and efficient user interface for analysts and developers. |
Kensho noted for intuitive, user-focused UIs for both analysts and developers. | |
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Mobile Access Functional accessibility from mobile devices (native apps or web). |
No information available | |
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White-Labeling Possibility to customize the platform to align visually and functionally with client brand. |
No information available | |
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SDK Availability Provision of software development kits for easier custom integration. |
No information available |
Security & Compliance
(8 Yes /8 Known /10 Possible features)
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Data Encryption Data stored and transmitted using modern cryptography standards. |
Enterprise data security standards (encryption in transit and at rest) are standard for S&P. | |
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Audit Logging Maintains a complete log of access and actions for compliance. |
Audit logging is a standard feature in finance industry vendors, especially S&P. | |
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Regulatory Certifications Possession of certifications such as GDPR, CCPA, SOC2 relevant to data compliance. |
S&P has SOC2 and GDPR compliance, extending to Kensho. | |
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User Access Controls Granular user and group-based permissioning on data and analytics. |
Granular user access controls required in data platforms for regulatory compliance. | |
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Penetration Testing Regular vulnerability/pentesting assessments are performed. |
No information available | |
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Privacy Protection Guarantees regarding data subject anonymity and privacy protection. |
Privacy, anonymity, and compliance with privacy laws are referenced under S&P policies. | |
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Data Residency Options Ability to specify jurisdictions where data is stored or processed. |
S&P and Kensho provide client choices for data residency and hosting options. | |
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Third-party Data Sharing Controls Restrictions/controls over redistribution of consumed data. |
Enterprise clients have controls over third-party redistribution, as per SaaS agreement norms. | |
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Security Incident Notification Automated alerting regarding breaches or suspicious activity. |
No information available | |
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Vendor Diligence Support Facilitates client due diligence workflows (DDQ, supporting docs, etc). |
Due diligence support typical for enterprise B2B platforms in finance data. |
Performance & Scalability
(4 Yes /4 Known /10 Possible features)
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Concurrent User Capacity Maximum number of active users supported simultaneously. |
No information available | |
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Query Response Time Median time taken to return analytics or data queries. |
No information available | |
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Data Ingestion Rate Volume of new data processed per unit of time. |
No information available | |
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Uptime SLA Service Level Agreement (SLA) on platform operational uptime. |
No information available | |
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Peak Data Storage Capacity Maximum volume of data the platform can host. |
No information available | |
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Elastic Compute Scaling Automatic scaling of compute resources to match workload. |
Elastic infrastructure scaling referenced in Kensho technical resources. | |
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Parallel Processing Support Ability to process multiple data streams or queries concurrently. |
Parallel query/data processing supported for large-scale analytics, as marketed. | |
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Data Retention Policy Flexibility Configurable data storage retention periods. |
No information available | |
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Performance Monitoring Tools Built-in dashboards or reporting for platform health and performance. |
Platform health and monitoring tools (dashboards) available for enterprise clients. | |
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Batch Processing Support Efficient support for large batch data operations. |
ML/AI data pipelines for quant support batch as well as real-time operations. |
User Support & Documentation
(7 Yes /7 Known /10 Possible features)
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Onboarding Support Personalized setup, initial training, and account configuration help. |
Enterprise onboarding, training, and configuration standard as per S&P service. | |
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Knowledge Base Extensive searchable documentation and tutorials. |
Extensive documentation and searchable support resources provided by S&P/Kensho. | |
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Data Dictionary Comprehensive descriptions of each data field and its origin. |
Data dictionaries for each feed/module available to support investment research. | |
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API Documentation Completeness Detail and clarity of technical integration guidelines. |
API documentation described as comprehensive in developer support materials. | |
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Dedicated Account Management Assigned customer success managers for enterprise users. |
Dedicated account and relationship managers standard for Kensho enterprise deployments. | |
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Live Chat Support Immediate support via chat with platform staff. |
No information available | |
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User Training Workshops Regularly scheduled or on-demand platform training. |
User training and onboarding modules detailed as part of customer support. | |
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Community Forum User-to-user interaction and support hub. |
S&P maintains user community/forums for client support and discussion. | |
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Localization Support Availability in multiple languages and time zones. |
No information available | |
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Feedback Mechanism Ability for users to suggest features or report issues and track resolution. |
No information available |
Pricing & Contract Flexibility
(3 Yes /3 Known /10 Possible features)
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Usage-Based Pricing Option for pricing tied to volume or levels of consumption. |
No information available | |
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Tiered Subscription Models Multiple service tiers for diverse needs and budgets. |
Tiered subscription/pricing models referenced in S&P commercial offerings. | |
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Custom Enterprise Agreements Ability to negotiate bespoke terms for large clients. |
Bespoke enterprise terms available for large institutional clients. | |
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Transparent Fee Structures Upfront and clear disclosure of fees across all services. |
Transparent and clearly disclosed fee schedules for platform usage. | |
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Free Trial Availability Short-term trial or demo use before commitment. |
No information available | |
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Minimum Contract Term Shortest term for standard agreements. |
No information available | |
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Add-On Modules Pricing Clarity and flexibility of pricing for optional advanced modules. |
No information available | |
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Early Termination Options Availability of low-penalty or pro-rata contract cancellation. |
No information available | |
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Unlimited User Pricing Flat-rate pricing not tied to user count. |
No information available | |
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Nonprofit/Educational Discounts Special pricing for academic or nonprofit organizations. |
No information available |
Customization & Extensibility
(8 Yes /8 Known /10 Possible features)
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Custom Dashboard Building Ability to design and save custom dashboards for specific analyses. |
Users can create, save, and configure custom dashboards. | |
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Workflow Automation Integration with tools for process automation (e.g., alerts, trade signals). |
Workflow automation and alerts available via integration/API. | |
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Custom Data Ingestion Upload and merge a client’s own alternative or proprietary data. |
Client-uploaded/custom data blending mentioned in platform capability. | |
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Plugin/Extension Framework Ability to add modules/extensions for new functionalities. |
Plugin/extension framework referenced in advanced use cases documentation. | |
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Scripting/Programming Interface Support for custom script development (e.g., Python, R APIs). |
Scripting and programmable interfaces (esp. Python APIs) are featured in developer resources. | |
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Theming/Branding Customization Visual customization for brand consistency. |
Visual branding/theming options described for enterprise clients in the product suite. | |
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Custom Reporting Design and automate custom report formats. |
Customizable reporting highlighted for investment manager workflows. | |
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Alert Customization User-defined conditions and triggers for event-driven alerts. |
Users can define alerting conditions and triggers for key events. | |
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Integration with In-House Tools Ability for organization-specific connectors/modules. |
No information available | |
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Deploy in Private Cloud Support for on-premises or VPC deployment for sensitive clients. |
No information available |
Vendor Stability & Reputation
(5 Yes /5 Known /10 Possible features)
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Years in Business How long the platform provider has operated. |
No information available | |
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Referenceable Clients Number of notable clients willing to provide references. |
No information available | |
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Third-Party Reviews Number and quality of external analyst or customer reviews. |
No information available | |
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Legal Disputes Disclosed History of significant legal action or unresolved disputes. |
No evidence of legal or unresolved disputes; S&P discloses relevant legal actions if any. | |
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Financial Transparency Annual financial reporting or third-party audits available. |
S&P provides financial transparency through annual reports and audits. | |
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Industry Partnerships Participation in alliances or consortia that enhance credibility. |
S&P and Kensho engage in multiple industry alliances and data consortia. | |
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Churn Rate Percentage of clients discontinuing service per year. |
No information available | |
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Client Growth Rate Annual increase in platform users or logos. |
No information available | |
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Awards/Industry Recognition Recognition by reputable industry organizations. |
Multiple industry awards and recognitions, as cited in Kensho/S&P PR. | |
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Business Continuity Plan Documented and tested plans for disaster recovery and service resilience. |
S&P has a documented, tested business continuity and DR plan; applies to Kensho. |
Innovation & Forward-Looking Capabilities
(7 Yes /7 Known /10 Possible features)
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AI/ML Model Upgrades Frequency of innovation or upgrades in analytic and predictive engines. |
No information available | |
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New Data Source Integration Rate How quickly new alternative data sources are made available to users. |
No information available | |
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Participates in Data Consortiums Active member of data-sharing or standards organizations. |
Participates in industry consortia and data standards groups, as announced in industry press. | |
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Visualization Innovation Frequency of new or advanced visualization techniques introduced. |
No information available | |
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Beta Testing/Client Feature Input Mechanisms for early adopter programs or client-driven roadmap. |
Client-driven roadmap and early adopters frequently cited in Kensho product dev releases. | |
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Academic Collaborations Partnerships with universities for applied research. |
Academic research collaborations cited on Kensho website. | |
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Open Data Initiatives Support or contribution to open alternative data/tech communities. |
Open data and technology community engagement described. | |
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Data Science Sandbox Environment for clients to experiment with new data and analytics. |
Data science sandbox/experimental environment referenced. | |
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API Versioning and Roadmap Disclosure Transparent release plans and versioning for APIs and tech. |
API version histories and roadmap are disclosed in developer documentation. | |
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Cross-Asset Data Opportunities Support for new data categories relevant across markets (e.g., ESG, crypto). |
Supports cross-asset data types (ESG, crypto, etc) as part of analytics. |
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