End-to-end quantitative investment platform for strategy design, backtesting, and implementation. Offers extensive historical data, sophisticated backtesting capabilities, factor modeling, and risk analysis with cloud-based computing infrastructure.
Software for statistical analysis, econometric modeling, and quantitative research to identify patterns, correlations, and potential investment opportunities based on historical data and mathematical models.
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Multi-source Data Import Ability to import data from various internal and external sources including APIs, CSVs, Excel, and databases. |
SigTech supports ingesting data from a wide variety of data sources, including APIs and files, as publicized in their 'data onboarding' documentation. | |
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Real-time Data Feeds Support for continuous ingestion of live market and financial data. |
SigTech highlights real-time market data support and continuous data ingestion for strategy implementation. | |
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Historical Data Storage Capacity to store and retrieve large volumes of historical data for backtesting and analysis. |
No information available | |
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Data Cleansing Tools Tools for removing duplicates, handling missing values, and normalizing data formats. |
Data cleaning and normalization is a feature in SigTech's standard onboarding and pipeline workflow. | |
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Metadata Management Ability to manage data dictionaries and ensure context/lineage of datasets. |
SigTech includes metadata management, such as data dictionaries and lineage, as described in technical product docs. | |
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Automated Data Transformation Automated processes for adjusting or standardizing data before use in models. |
Automated data transformation is built into SigTech’s onboarding pipeline, enabling standardization and preprocessing required for backtesting. | |
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Data Security & Access Controls Capabilities to restrict and monitor user access to sensitive or proprietary datasets. |
Role-level access controls and data security settings are integral to SigTech’s enterprise solution. | |
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Cloud Storage Compatibility Support for major cloud platforms for data storage and compute. |
SigTech is a cloud-native platform, supporting major cloud storage providers (AWS, Azure, GCP). | |
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Data Audit Trails Track and record changes and usage of datasets for compliance and transparency. |
The platform tracks and manages changes to datasets for compliance and auditability. | |
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Automated Data Refresh Scheduling and automation of regular data updates from sources. |
SigTech facilitates automated periodic data refreshes from designated sources. |
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Descriptive Statistics Generate measures such as mean, median, standard deviation, skewness, and kurtosis across datasets. |
Descriptive statistics and data profiling are available in the quant research toolkit. | |
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Correlation Analysis Assess and visualize relationships between different variables or assets. |
SigTech provides users with tools for analyzing correlations between multiple assets. | |
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Regression Modeling Build and analyze linear and nonlinear regression models, including multi-factor models. |
Users can build and analyze regression models using integrated Python libraries and platform modules. | |
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Time Series Analysis Conduct ARIMA, GARCH, and other time-series forecasting methods. |
The platform supports time series analysis and forecasting, including ARIMA/GARCH, as part of its quant analytics stack. | |
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Hypothesis Testing Built-in tools for t-tests, chi-square tests, ANOVA, and similar statistical tests. |
Hypothesis testing tools are available through the included Python (SciPy, statsmodels) integration. | |
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Factor Analysis Evaluate and decompose financial returns by factors such as value, momentum, or size. |
Factor analysis for returns decomposition (e.g., Fama-French, risk premia) is a core offering. | |
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Clustering & Classification Support for machine learning clustering/classification (e.g., k-means, decision trees). |
ML-based tools such as clustering/classification are available via Jupyter/Python unification. | |
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Principal Component Analysis (PCA) Dimensionality reduction and risk analysis via PCA. |
Dimensionality reduction and PCA are explicitly supported within the toolkit. | |
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Monte Carlo Simulation Run Monte Carlo simulations for portfolio risk and scenario analysis. |
Monte Carlo simulation methods are provided for portfolio and risk analysis per platform documentation. | |
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Custom Statistical Scripting Support for integrating custom statistical scripts (Python, R, etc). |
Researchers can run custom scripts in Python via JupyterLab environment and the SigTech API. |
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Panel Data Analysis Support for econometric techniques using cross-sectional/time-series panel data. |
Panel data and econometric analysis are enabled via support for common Python stats packages. | |
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Cointegration Testing Check for long-term equilibrium relationships between asset prices. |
Cointegration testing is available via integrated statistical packages. | |
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Error Correction Models (ECM) Implement and estimate ECMs to measure speed of adjustment to equilibrium. |
Error Correction Model support indirect through Python econometric libraries. | |
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Instrumental Variables Estimation Handle endogeneity in regression via instrumental variable methods. |
IV estimation (instrumental variables) is achieved through access to Python (statsmodels) from within the platform. | |
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Generalized Method of Moments (GMM) Implement and solve complex GMM models for efficiency. |
GMM is accessible to researchers through the integrated Python scientific stack. | |
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ARCH/GARCH Modeling Model time-varying volatility in financial series. |
ARCH/GARCH modeling is a highlighted feature for time-series risk modeling. | |
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Vector Autoregression (VAR) Multi-variable prediction and shock analysis. |
VAR modeling is available through Python libraries supported in SigTech’s notebooks. | |
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Structural Equation Modeling (SEM) Ability to estimate multiple and interrelated dependency relationships. |
SEM is supported via statistical libraries accessible in the Jupyter environment. | |
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Auto Model Specification Selection Automated selection of optimal statistical or econometric model structures. |
Auto model selection is possible in pipeline design via Python-based workflow automation. | |
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Macroeconomic Scenario Generation Simulate macroeconomic environments for stress testing portfolios. |
Macroeconomic scenarios for stress-testing are available and can be integrated into portfolio analysis. |
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Mean-Variance Optimization Classical Markowitz portfolio optimization. |
Mean-variance optimization and Markowitz methodology are documented as supported optimization functions. | |
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Black-Litterman Model Support Support for running Black-Litterman blended optimization. |
The Black-Litterman model is specifically called out as included in SigTech’s portfolio tools. | |
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Risk Budgeting Allocate capital based on asset/strategy risk contributions. |
Risk budgeting via marginal contribution analysis and similar tools provided in optimization workflows. | |
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Custom Constraint Handling Flexible constraint definitions for liquidity, sector, geography, and other rules. |
Custom constraints can be applied in portfolio construction, including liquidity, sector, and geographic rules. | |
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Transaction Cost Modeling Estimate and incorporate transaction costs into optimization. |
Transaction cost modeling is integrated into optimization, per product docs. | |
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Tax-aware Optimization Include the impact of different tax treatments in portfolio decision making. |
Tax impact calculations are enabled by customizable portfolio analytics scripting. | |
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Scenario Analysis Analyze portfolio responses to hypothetical or user-defined scenarios. |
Scenario analysis is a core component within strategy and risk modules. | |
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Backtesting Evaluate portfolio strategies against historical data to assess performance. |
Backtesting is a central feature — SigTech was built for this purpose. | |
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Multi-period Optimization Optimize portfolios through multiple rebalancing periods. |
Multi-period optimization including scenario and rebalance simulation supported. | |
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ESG/Sustainability Integration Support for optimizing portfolios with ESG or sustainable investment constraints. |
ESG integration is available through customizable constraints and ESG data sources. |
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Value at Risk (VaR) Calculation Calculate portfolio or asset VaR using various methods (historical, parametric, Monte Carlo). |
Value at Risk calculation features are standard in the platform's risk module. | |
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Conditional VaR (CVaR) Support for tail risk calculations using CVaR. |
Conditional VaR (CVaR) is included in tail risk analysis modules. | |
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Stress Testing Test performance against extreme but plausible adverse market scenarios. |
Stress testing is natively integrated, with the ability to simulate adverse market scenarios. | |
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Sensitivity Analysis Analyze the impact of changes in risk factors (e.g., interest rates, spreads). |
Sensitivity analysis is possible on interest rates, spreads, and custom risk factors. | |
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Exposure Analysis Detailed views on exposures by asset class, region, sector, and risk factor. |
Portfolio and position-level exposure analysis is supported with interactive dashboards. | |
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Liquidity Risk Models Assess portfolio vulnerability to liquidity constraints. |
SigTech supports liquidity risk assessment and liquidity-driven scenario modeling. | |
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Factor Risk Decomposition Break down portfolio risk by systematic and idiosyncratic factors. |
Factor risk decomposition is available, cross-referencing factor exposures and idiosyncratic risks. | |
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Automated Alerts Configurable risk alerts on breaches of thresholds or limits. |
Automated and configurable alerts for risk thresholds and portfolio breaches available via dashboard. | |
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Credit Risk Assessment Model and evaluate credit risk exposure within portfolios. |
Credit risk assessment via integrated analytics and Python capabilities. | |
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Integrated Risk Dashboard Visual summary of all risk measurements for quick decision making. |
Unified risk dashboard is highlighted as a key management and reporting interface. |
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Time-weighted & Money-weighted Returns Generate both TWR and IRR-style returns for portfolios and benchmarks. |
Built-in performance measurement supports both time-weighted and money-weighted returns. | |
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Multi-level Performance Attribution Decompose contributions to return by asset, sector, region, or factor. |
Multi-level performance attribution available for assets, sectors, and custom groupings. | |
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Custom Benchmark Comparison Measure performance relative to user-defined benchmarks. |
SigTech enables comparison against user-defined (and index) benchmarks. | |
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Style Analysis Quantitatively analyze styles (growth/value, small/large-cap, etc.). |
Style analysis (e.g., growth/value) is possible with supplied analytics modules. | |
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Risk-adjusted Performance Metrics Automatically calculate Sharpe, Sortino, Information Ratio, Alpha, Beta, etc. |
Risk-adjusted performance metrics such as Sharpe and Sortino ratios are provided. | |
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Attribution by Decision Layer Segment attribution to allocation, selection, timing, and interaction effects. |
Attribution by decision layer available through contribution analytics functions. | |
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Custom Time Period Analysis Flexible analysis periods (monthly, quarterly, YTD, custom date ranges). |
Flexible analysis periods, including custom date range queries built into reporting tools. | |
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Peer Group Comparison Analyze performance versus peer group portfolios or funds. |
Peer group comparison is supported via importing external performance data sets. | |
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Return Decomposition Visualization Graphical breakdown of absolute and relative performance drivers. |
Visualization components provide return decomposition and performance drivers. | |
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Attribution Report Generation Exportable reports with detailed attribution analyses. |
Automatically generated attribution reports are available for download. |
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Customizable Dashboards User-defined dashboards for quantitative analytics and monitoring. |
User-customizable dashboards for different analytic modules are featured. | |
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Interactive Charting Dynamic charts (line, bar, scatter, heatmap, etc.) allowing deep data exploration. |
Interactive charting options (line, bar, scatter, heatmap) build upon Python and dashboard libraries. | |
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Scenario & What-if Visualization On-the-fly graphical analysis of potential investment scenarios. |
Scenario and what-if visualization modules for portfolio simulations are documented capabilities. | |
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Automated Report Scheduling Schedule regular, automated delivery of reports to stakeholders. |
Report scheduling and automatic email delivery are supported in platform's reporting suite. | |
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Export Formats Support for exporting reports/visualizations in PDF, Excel, PowerPoint, HTML, image formats. |
Export to PDF, Excel, PowerPoint, HTML, and images indicated in user documentation. | |
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Custom Template Builder Branding and customization options for client-ready reports. |
Customizable report templates enable white-label output for clients. | |
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Annotation Tools Mark up charts and reports with comments and visual cues. |
Annotation tools available for annotated charts and reports. | |
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Drill-down Capabilities Detailed exploration from high-level dashboards to granular data points. |
Dashboards support drill-down to individual trades, assets, and sub-portfolios. | |
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Report Access Controls Permissions and restrictions for report viewers. |
User-based permissions for viewing and exporting reports are available. | |
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Real-time Visualization Updates Automatic refresh of visuals with underlying data changes. |
Visualizations update in real time when underlying data changes, e.g., post-backtest. |
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Workflow Orchestration Design, schedule and automate common quantitative analysis processes. |
Common analysis pipelines can be scheduled and automated for quant/ops workflows. | |
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Event-driven Triggers Ability to initiate tasks or rerun analyses based on market or data events. |
Event-driven automation for rerunning analysis after data updates is available. | |
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Batch Processing Support for high-volume batch analysis jobs. |
Batch processing of large analysis jobs supported by cloud compute environment. | |
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Version Control Integration Integration with source control systems for managing code and model versions. |
SigTech integrates with GitHub and internal versioning for code/notebooks/models. | |
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Concurrent User Support Number of users who can access and operate the platform simultaneously. |
No information available | |
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Collaboration Tools Features for discussion threads, shared documents and commentaries. |
Collaboration features include sharing notebooks, comments, and result objects between users. | |
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Automated Notifications Alert users to workflow status, errors, or results. |
Automated and user-triggered notification system about workflow/run status provided. | |
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Role-based Task Assignment Assign steps in analysis workflows to specific users or teams. |
Role-based workflow assignments supported for team and project collaboration. | |
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API-based Task Automation Automate analysis tasks via API calls. |
Platform supports API-driven workflow automation as documented for enterprise users. | |
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Audit Logging Comprehensive tracking of workflow executions. |
Comprehensive audit logging of analysis tasks and user actions is built-in. |
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API Support Comprehensive APIs for importing/exporting data and calling analytical routines. |
Extensive API documentation suggests broad API support for data and analytics integration. | |
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Database Connectivity Native connectors for common relational, time-series, and NoSQL databases. |
Native connectors for SQL, time-series, and NoSQL databases are supported. | |
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Programming Language Support Integration with languages such as Python, R, MATLAB, C++, etc. |
Supports Python, with R, MATLAB, and other language integrations available as plug-ins or via API. | |
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Plug-in/Extension Framework Support for 3rd-party and custom plug-ins to extend functionality. |
Plug-in framework for custom analysis and extensions is supported (private customer API). | |
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Cloud & On-premise Deployment Ability to deploy in cloud, on-site, or hybrid environments. |
Supports both cloud-native and client-hosted (on-premise/hybrid) deployments. | |
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Excel Integration Ability to read/write from Excel and embed live formula links. |
Deep Excel connectivity for importing/exporting and maintaining live links to models. | |
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Single Sign-On (SSO) Authentication integration with enterprise identity providers. |
Single Sign-On (SSO) integration with enterprise identity providers is available. | |
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Mobile Access Mobile app or responsive web UI support. |
Responsive web UI supports mobile access to platform dashboards and analyses. | |
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Data Vendor Feeds Integration Direct links to Bloomberg, Refinitiv, FactSet, etc. |
Direct datafeeds (Bloomberg, FactSet, etc) are available or can be added via vendor APIs. | |
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Custom API Endpoints User-defined endpoints for integration with internal systems. |
Enables users to define custom API endpoints for internal system integration. |
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Computation Speed Performance of core analytics and model calculations. |
No information available | |
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Concurrent Model Runs How many parallel model runs the system can support. |
No information available | |
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Real-time Analytics Support for real-time or near real-time processing and output. |
Platform offers real-time and near-real-time analytics outputs for supported datasets. | |
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Scalable Compute Architecture Ability to scale up/down resources as data/model size grows. |
Cloud-native scalable infrastructure supports resizing compute resources as needed. | |
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Distributed Computing Leverage distributed frameworks to accelerate analysis. |
Distributed/cloud computing infrastructure built-in for parallel analyses. | |
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Load Balancing Automatically distribute analysis tasks for optimal performance. |
Analysis jobs distributed automatically for load balancing in cloud deployments. | |
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Resource Usage Monitoring Monitor and report system CPU, memory, and storage consumption. |
Resource monitoring dashboards available to track compute/storage. | |
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High-availability (HA) Support Built-in redundancy or failover to minimize downtime. |
High-availability and failover options are standard in enterprise-level cloud-native applications. | |
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Job Queue Management Efficiently manage and prioritize multiple analysis jobs. |
Job queue management available for prioritizing analyses and runs. | |
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Latency Metrics Dashboard Visual and numeric display of computational response times. |
Response time metrics and latency dashboards are present for monitoring performance. |
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Data Encryption (At Rest/In Transit) Protects sensitive data via encryption during storage and network transfer. |
Platform uses industry-standard encryption both at rest and in transit. | |
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User Authentication & Authorization Granular user permissions, authentication options, and MFA support. |
Authentication, granular permissions, and MFA are offered in enterprise settings. | |
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Audit Trails & Logging Comprehensive event and access logging for auditing and compliance. |
Comprehensive audit log covering both analysis events and user/system access. | |
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Regulatory Compliance Modules Support for MiFID II, AIFMD, SEC, GDPR, and other regulations. |
SigTech states regulatory compliance support, including MiFID II, SEC, and GDPR modules for relevant operations. | |
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Data Retention Policy Tools Automate and implement policies for data archiving and removal. |
Data retention policies and automation features are implemented as part of enterprise data governance. | |
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Vulnerability Management Regular updates for system vulnerabilities and compliance. |
Regular vulnerability scanning and patch management described in security overview. | |
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Third-party Security Certifications SOC 2, ISO/IEC 27001, and other certifications. |
SigTech advertises SOC 2 and ISO/IEC 27001 certifications for the platform. | |
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Secure API Gateways Ensure API connections are secure and monitored. |
Secure API gateways and monitored connections are described in security and IT documentation. | |
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User Activity Monitoring Real-time and historical monitoring of user activity for anomalies. |
User activity is monitored in real time and logs are auditable for anomalies. | |
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Incident Response Procedures Documented protocols and in-system playbooks for responding to breaches. |
Incident response procedures and playbooks are outlined as part of SigTech's operational security. |
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