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Evolve from being data “smart” to being intelligent operationally to support
data-driven decisioning throughout the entire value chain.


Gain the analytics maturity needed to compete in the digital insurance marketplace

Access all data sources to generate maximum results from analytics investments

Strategically use both structured data and unstructured data to help provide greater accuracy in all types of analytics from customer, underwriting and risk assessment.

Modernize the data architectures to enable advanced analytics

Big Data and advanced analytics are foundational for artificial intelligence for learning-based systems to help insurers achieve maximum value from their data initiatives and help them build more precise models that match market trends, adjusting through real-life learning methodologies.

Create a culture of shared data-intellect

Analytics strength and rigor must move beyond the actuarial department into other business units and functions such as claims, fraud and marketing using new sources of data and algorithms which can be operationalized in real-time and sourced from core systems. This will help optimize data throughout the enterprise, driving greater ROI where data has been underutilized in the past.

Business Challenges

Just-in-time decisioning & monitoring of data while managing privacy

The immediacy of business decisions requires regular monitoring of data a sophisticated technical infrastructure to collect and tabulate information. The importance and complexity of these decisions means insurers insist on very high standards for data-analytics tools. The sensitive nature of insurance decisions and data furthermore creates major concerns about privacy.

Problematic Data Conventions

Several data conventions in insurance hinder the widespread use of data analytics because data is split among different platforms and have different formats. Even well-structured data are often not available to insurers who could use them in useful ways.

Ease of Analytical Tool Usage & Workflow Disruption

The resistance to adoption of analytics is the requirement of learning new tools and the workflow disruption that results. For data analytics to truly transform insurance, data must be presented in tools that that are already in use.

Affordability of Data Infrastructure Costs

Insurers want to manage their data analytics investments so that extra costs are not passed on to consumers. Working with data in an efficient, timely manner helps makes insurance more affordable in a competitive environment.

Why AtScale?

Gain a complete view of your data

Get a single view of all of your data through intelligent data virtualization, providing dependable information and insights regardless of data location or format.

Improve data agility and performance

Autonomous engineering uses machine learning to optimize data queries to reduce time from hours to seconds and to make costs efficient and predictable.

Streamline operations

Provide data access through a single common interface and allow your data users to use the BI tools of their choice to look at data across the organization

Preserve security, privacy and compliance

An adaptive analytics fabric preserves the security policies of individual databases all the way to the individual user via intelligent data virtualization.

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Adaptive Analytics and Insurance

Optimize underwriting, pricing, and claims management and deploy analytics in a seconds and calculate what you need to be more operationally efficient and effective in the marketplace.


Drive growth, revenue, streamline business operations and serve your customers and partners in a more informed, personalized and faster way leveraging self-service analytics.


Apply autonomous systems to increase data reliability, speed, and security while reducing delays from manual data engineering.


Modernize data architecture, policies and procedures for improved securing for agents and insureds to protect your company from liability.


Simplify the process of bringing data together and providing high-speed insights in a complex, hybrid cloud environment.

Use Case Spotlight: Large insurance provider

The Challenge:

A large insurance provider with 10s of millions of members and processing 100s of millions of claims a year assesses the efficacy of the healthcare services reimbursed, the insurance industry uses a key metric called “PMPM” or “Per Member Per Month” (it refers to the cost of service divided by the number of members within that month). This metric, albeit seemingly appearing fairly basic, is fairly hard to get right when insurance members fluctuate, when services cost vary and when the tools used to compute and analyze these numbers range from excel spreadsheets, to Tableau reports to custom-build applications.

The Solution:

AtScale provided the ability to define key metrics in one place, secure them centrally yet make them accessible everywhere to transcend beyond the limitations of their outdated infrastructure, reduce costs, and empower their analysts and data consumers.



Download the Rise of the Adaptive Analytics Fabric


Fortune 50 DIY retailer optimizes a cloud data platform to increase ROI per analysis.

Toyota leverages AtScale, accelerating time-to-insight from weeks to minutes.

Fortune 100 industrial conglomerate embraces the cloud without business disruption.

Related Resouces

White Paper: Big Data & Governance

Get data governance best practices that will enable you to engineer compliance with regulatory requirements; create a single source of truth; ensure quick, reliable access to data; and provide consistent results across analytical tools.

White Paper: The Rise of the Adaptive Analytics Fabric

Learn how the prevalence of cloud transformation as a critical enterprise initiative has led to the emergence of the adaptive analytics fabric with intelligent data virtualization as a new paradigm in enterprise data architecture.

White Paper: Adaptive Analytics Fabric for Business

Learn how to move your business forward with an adaptive analytics fabric that enables business-centric data virtualization.


AtScale Adaptive Analytics

Deliver data for business intelligence and machine learning analytics just-in-time.
Shift resources from managing distributed data silos—to analyzing them.

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