Risk Analytics features

Platforms for advanced analysis of various risk types to support risk management decisions.

We ask vendors to mark their product against our feature list. It is not available for all products and in some cases we have derived data from publicly available sources. The list of features follows. Vendors can add a further 10 key features of their own.

Compliance and Regulatory Support

Support for meeting relevant banking and risk-related regulations through analytics and reporting.

Audit-ready Reporting: Ability to generate documentation and outputs required for external/internal audits.
Automatic Regulatory Updates: Product is kept current with major regulatory rule changes.
Basel Compliance Tools: Built-in models and reports aligned to Basel II/III requirements.
Compliance Policy Templates: Pre-built and customizable documentation to accelerate compliance efforts.
Comprehensive Risk Taxonomy: Library of risks classified in accordance with global regulatory standards.
Data Lineage: Traceability of all data points in regulatory reports back to origin.
IFRS 9/CECL Support: Features to support international and US accounting for credit impairment.
Regulatory Submission Integration: Direct interfaces for electronic regulatory report delivery.
Regulatory Test Suites: Standardized test suites to validate compliance outputs.
Regulatory Version Control: Ability to archive and roll-back compliance configurations.

Data Integration and Connectivity

Capabilities for connecting, aggregating, and cleaning data from numerous banking sources and third-party datasets, which are crucial for comprehensive risk analytics.

API Support: Availability of application programming interfaces for custom integrations.
Batch Processing Speed: Processing speed for large batches of imported data.
Cloud Database Compatibility: Support for major cloud storage/data platforms.
Data Enrichment: Capability to augment data with additional attributes or external sources.
Data Mapping Flexibility: Tools for flexible mapping between different data schemas.
Data Quality Monitoring: Tools to continuously check, profile, and improve data accuracy and consistency.
ETL Automation: Built-in extract, transform, load (ETL) processes for automated data management.
Multi-source Data Integration: Ability to import and unify data from multiple banking systems (core banking, CRM, external feeds, etc.).
Real-time Data Sync: Support for real-time or near-real-time data updates and streaming.
Unstructured Data Handling: Ability to process and analyze unstructured data (such as emails, documents, social media).

Integration and Extensibility

Enabling connection with other banking applications, BI tools, modeling environments, and enterprise systems.

BI Tool Compatibility: Native integration with major BI products (Power BI, Tableau, etc.).
Custom Workflow Integration: Ability to combine risk analytics into larger business workflows.
Data Export APIs: REST or SOAP APIs to export risk data/analytics to other systems.
Event-driven Integration: Trigger actions or analytics based on external events.
Extensible Data Schema: Ability for admins to easily extend data structures for additional fields.
Plug-in/API Library: Pre-built connectors or plug-ins for banking, BI, or risk management platforms.
SFTP/Batch File Interface: Support for exchanging bulk risk data using SFTP or shared storage.
Sandbox Environment: Environment for testing integrations and customizations safely.
Third-party Model Import: Ability to ingest externally developed models (e.g., PMML, Python, R).
Versioned API Support: Backward-compatible management of API version changes.

Performance and Scalability

Product’s ability to handle large data volumes, many users, and complex risk computations without degradation.

Analytic Calculation Speed: Average time needed for complex risk calculations.
Batch Processing Throughput: Amount of data processed per batch job.
Cloud Scalability: Native scalability in public/private/hybrid cloud environments.
Concurrent User Support: Number of users who can access/report simultaneously.
Failover/Disaster Recovery: Automated backup and recovery options for business continuity.
Load Balancing Support: Automated distribution of workload to maximize performance.
Maximum Data Volume: Amount of transactional or risk data that can be stored/processed efficiently.
Parallel Processing Capability: Ability to use parallel CPUs/cores for faster risk analytics.
Peak User Response Time: Maximum time for dashboard or report to load at peak usage.
Uptime/Availability SLA: Service level agreement for availability/reliability.

Predictive Analytics and Machine Learning

Advanced analytics to anticipate risk using statistical and AI methods.

Anomaly Detection: Automatic identification of unusual risk patterns.
AutoML Capabilities: Support for automatic model selection and hyperparameter tuning.
Automated Feature Engineering: Automatic detection and creation of useful input features for predictive models.
Batch Scoring Speed: The speed at which models can score data in batch processes.
Custom Algorithm Support: Ability to plug in proprietary or custom-developed models.
Machine Learning Model Integration: Ability to deploy, score, and retrain machine learning models.
Model Explainability Tools: Features for interpreting ML model outputs (e.g., Shapley values, LIME).
Model Performance Monitoring: Ongoing tracking of predictive model accuracy and drift.
Risk Alerting Based on Predictions: Automated notification based on predictive risk thresholds.
Time-series Forecasting: Support for forecasting risk using time series/sequence models.

Reporting and Visualization

Advanced analytical reporting and visualization of risk, providing actionable insights.

Automated Report Generation: Tools for scheduled and one-click creation of risk reports.
Custom Report Builder: User-defined templates and configuration for bespoke reporting.
Drill-down Functionality: Ability to drill into report figures to explore underlying data.
Exception Reporting: Alerting on outliers, breaches, or significant risk events.
Export Options: Ability to export reports/data to popular formats (PDF, Excel, CSV, etc.).
Interactive Dashboards: Customizable dashboards for visualizing key risk metrics and trends.
Mobile Accessibility: Support for report and dashboard access on mobile devices.
Regulatory Report Templates: Built-in templates for key regulatory risk reports (e.g., Basel, IFRS 9, CECL).
Trend Analysis: Historical views and trend projections for risk indicators.
Visualization Types: Number of chart/visualization types supported.

Risk Data Governance and Security

Mechanisms to ensure data privacy, regulatory compliance, and control in risk analytics.

Audit Trail: Comprehensive logs of data changes and analytic actions.
Automated Data Retention Policies: Configurable rules for retaining and purging risk data.
Data Encryption: Support for encryption at rest and in transit.
Data Masking: Redacting sensitive information in outputs and analytics.
GDPR/CCPA Compliance: Certified support for major data privacy laws.
Incident Response Framework: Structured response and notification policies for security events.
Multi-Tenancy Support: Ability to securely segment data and processes by user or division.
Physical Security Certifications: Provider holds relevant data center and process security certifications.
SAML/SSO Integration: Support for federated login and identity management.
User Access Controls: Role-based permissions and user management.

Risk Modeling and Scoring

Core analytics features to quantify and model risks in banking portfolios, customers, and operations.

Credit Risk Assessment: Ability to model, calculate, and report on credit risk exposure.
Custom Risk Scorecard Builder: Ability to design, implement, and manage custom risk scoring systems.
Exposure at Default Estimation: Tools to model EAD figures.
Loss Given Default Estimation: Tools to estimate LGD values.
Market Risk Analytics: Support for calculating risks related to market volatility, value at risk (VaR), etc.
Model Calibration Tools: Functionality to recalibrate and validate predictive risk models.
Operational Risk Models: Tools for quantifying and simulating operational risks (fraud, process failure, etc.).
Probability of Default Calculation: Support for quantitative PD modeling.
Scenario Analysis: Capability to analyze the effect of different market and credit scenarios.
Stress Testing: Simulation of extreme scenarios to assess resilience.

Scenario and Stress Testing

Features for simulating, stress testing, and understanding risk under adverse or hypothetical conditions.

Flexible Scenario Definition: User-definable parameters and variables for scenario analysis.
Large-scale Simulation Capacity: Maximum number of simultaneous scenarios that can be run.
Macro-economic Scenario Modeling: Built-in or customizable macroeconomic scenario setups for stress testing credit and market risk.
Real-time Impact Calculation: Instantaneous computation of risk metric changes as scenarios are applied.
Regulatory Stress Test Alignment: Templates and configuration aligned to regulatory stress test requirements (e.g., CCAR, EBA).
Reverse Stress Testing: Ability to identify scenarios that would cause portfolio or firm-wide failure.
Scenario Comparison Visualization: Tools to visually compare outputs under multiple scenarios.
Scenario Library: Pre-configured sets of sample scenarios for rapid analysis.
Scenario Result Export: Ability to export scenario outputs for reporting or further analysis.
Test Automation: Scheduling and automation capabilities for regular stress and scenario runs.

User Experience and Collaboration

Tools for analyst productivity, team sharing, transparency, and ease of use.

Commenting and Discussion Tools: Inline commenting for risk findings and analytic results.
Customizable Dashboards: Drag-and-drop or configurable dashboards.
Export/Import User Settings: Ability to save, export, or migrate user configurations.
Mobile/Web Access: Full functionality via browser or mobile app.
Personalized Views: User-customized layouts, favorites, and bookmarks.
Role-specific Interfaces: UI/UX tailored to different types of users (analysts, managers, IT, etc.).
Scheduling and Email Notifications: Support for scheduled reports and email-based alerts.
Self-service Analytics: Ability for business users to run and customize analytics without IT.
Shared Workspaces: Team collaboration areas for shared analytics and annotation.
User Onboarding Guidance: Interactive help, tutorials, or guided onboarding for new users.

Features in Risk Analytics

for Analytics and Business Intelligence