Insurance Analytics
Accelerating Outcomes Driven by Digital Data Transformation in the Property & Casualty Insurance Industry
Insurance is a competitive business with regulated services that requires effective operational management & strategy to ensure optimal risk management. Diverse data sources serve as fuel for acquiring, augmenting & retaining customers and will enable the best experience for members. Modern data & analytics can work as an engine to unlock valuable insights across all insurance business functions. The streamlined data engine helps insurers to get the data on-demand.
The Cloud-based, AI-powered platform, purpose-built for claims. Seamlessly ingests claims data, fuses a myriad of syndicated data sources, finds patterns using deep learning neural networks to provide insightful predictions during a claims lifecycle for more efficient processing of claims. Technology platform agnostic provides API-based integration for super easy deployment.
Insurance Data and Analytics on Cloud (IDAC)
IDAC is a MetaData Driven Accelerator, custom built for P&C Insurers to fast track Data Modernization journey through smart acquisition, integration & encapsulation. Insurance companies have an opportunity to leverage the vast amount of data at their conveyance to jump-start their digital-transformation journeys and pave the way for an enhanced business-user experience.
AI Subrogation
Advanced AI solution to examine claims quickly and accurately for possible subrogation opportunity.
Investment Data Hub
Hydra provides standardized adapters to industry-leading market data providers (securities/instruments and counterparty reference data) and a centralized document management system with enterprise data acquisition, and data syndication.
Quality Assurance for Data and Dependencies (QADD)
Insurance Quality Assurance for Data & Dependencies (QADD) is a rule-based framework that will help in surfacing data quality issues. This is a simple and plug-and-play solution which can focus on specific data problems.

Insurance Data and Analytics on Cloud (IDAC)
Saama’s primary offering is an encapsulated data and analytics platform that enables rapid digital transformation and an optimal customer experience. Using intuitive, self-service analytics, IDAC offers a strategic view into disparate data sources through a unified data hub, for extremely efficient data management and modeling.
Features include:
- Intelligent data ingestion
- Custom-built metadata repository
- Actionable insights across business functions
AI Subrogation
The AI platform segments new claims by risk category to allow your company to quickly triage the high-risk claims and assign them to your experienced adjusters, and to streamline the settlement of your smaller claims.
AI Guided Process, From FNOL to Recovery
- AI-driven insight throughout the lifecycle
- Automatic application of state-specific Recovery Laws
- Near real-time Predictive insights for faster intervention
- Subrogation pattern detection and customization
- Easy Codeless Integration for faster implementation
Subrogate More for Better Business Outcomes
Up to 30% More Subrogation Claims
More than 40% Reduction in LAE
60% Faster Time in Overall Recovery

With Snowflake COE & Expertise, Saama Insurance Analytics can help you leverage Snowflake’s unique architecture for unlimited scalability and compelling performance.

Next-Generation Solution for Evolving Investment Data Hub Needs
Simplify the management and deployment of a plethora of securities data to deliver a centralized corporate action plan and a real-time operational view. Saama’s Hydra combines multiple sources of reference data into one Key Copy/Single Source of Truth database for centralized operational control and distribution to downstream systems, significantly improving business-wide data consistency and eliminating manual processes.
Quality Assurance for Data and Dependencies (QADD) for P&C Insurers
Insurance companies struggle with data that’s hard to accurately measure and consolidate. Being one of the most sensitive industries, data quality and efficient management is extremely important for insurers. Quality Assurance for Data and Dependencies (QADD) removes the risk of data duplicacy, inaccuracy, and inconsistency by implementing a functional data quality management system. We recommend applying the QUADD framework at the beginning of the data pipeline to avoid larger data quality issues in the future.
- Save up to 20% on the data downtime
- Easily configurable / restartable framework
- Customized DQ rules template

More for Insurance Business Process with Analytcs

Underwriting Analytics powered by ICAAM
Predictive analytics has the power to help insurance companies develop stronger pricing, faster underwriting and effective risk management strategies to accelerate growth. ICAAM is an API-driven, AI-powered engine that provides Underwriting insights, reduces customer churn, boosts policy renewal rates, and improves cross-sell and up-sell efforts by up to 40%.
- Cost-effective package recommendations
- Customer segments for a more targeted marketing strategy
- Policy renewal probability
- Cross-sell and up-sell propensity

Claims Analytics
To succeed at an end-to-end digital claims closure without escalating costs, insurance companies need a strong functional system that allows seamless data ingestion throughout the claims lifecycle to detect damage severity and fraud propensity. The AI is trained to extract relevant facts, find patterns, and then leverage a deep learning model to predict damage severity, and fraud potential.
- Prediction Across Claim Lifecycle
- Data Safety and Security
- Supercharged AI
- Fast and Flexible Integration

Analytics-driven Information Security
The insurance industry faces cyber-attacks more than any other industry and with much more complexities. The attempt to steal the exposed data, embed malware or ransomware, or security breaches. All attacks involve a high risk not only to financial data, but also to the business network. Our InfoSec Analytics combine data from the various sources and look for correlations and anomalies within the data.
- User 360 Analytics
- Privacy on Demand (PoD)
- Phishing Assessment & Actionalble Insights
- Training & Next Best Actions
- Cyber Risk Listening

Data DevOps on Demand
Insurance companies encounter challenges to integrate digital technologies into complex systems backed by legacy processes at a time when rapid innovation is a necessity. Adopting Saama Data DevOps can bring the modern approach which will allow processes to iterate and improve quickly, giving insurers the ability to roll out new features to serve business users better. Plethora of Data DevOps advantages:
- Establish & Align to Enterprise Functions
- Automate First, Everything else Next
- Agile & On Demand
- Reuse & Containerize