High Performance Actuarial Modeling for Faster Turnaround and Risk-informed Decision Support
At a time when regulatory and market demands are placing high emphasis on transparency and superior insights into risks; capital and strategic management is fast becoming an industry imperative today. Actuarial models rely on data from a variety of sources and are critical to the superior performance of various aspects of insurance operations, including risk management, reporting and rate setting. Factors such as poor data quality and flawed assumptions or business rules can negatively impact decision making and competitiveness.
This WNS’ Actuarial Proprietary platform creates a central repository for all assets including assumptions, facts, scenarios and supporting data. It enables the creation of business rules to extract data and create asset files for actuarial modeling software. The solution drives asset modeling through automation of file generation processes to enable risk-informed decisions that drive growth.
- Automates and centralizes manual and fragmented processes of file generation for accurate asset modeling
- Enables seamless data acquisition along with data transformation and synthesis through business rules engine for rule creation / management
- Offers a built-in workflow for approving newly created / modified business rules and process management
- Provides user friendly interface, canned reports and ad hoc reporting for business users - in addition to audit trail, privilege-based access and Single Sign-On (SSO)
- Availability of actuarial data in an integrated data warehouse drives transformation, reconciliation and reporting
- Flexibility to generate any number of asset files and comparative analysis capability of historical processes and files enables improved decision-making
- Centralized data warehousing mitigates the need for spreadsheets and fragmented databases, enabling better control, reporting and analytical capabilities
- Doubling the model runs / scenarios helps significantly reduce errors and process inaccuracies