Implementing Rating Engines with Business Rules and Lookup Models
Rating engines, just like scoring engines, pricing engines, compensation calculations, claims payment calculations, and many other types of calculation engines, aim to calculate fees or costs. Besides this commonality, they also share some complexity on the fine prints.
For example, insurance underwriters and lenders alike manage pricing sheets, often in the form of a spreadsheet. More often than not, these spreadsheets can contain thousands or tens of thousands of rows. While runtime performance may be a concern, maintainability is certainly a priority. Furthermore, the pace of change requires additional tracking and management to roll these rates over disparate geographies.
Over the years, the implementation of a rating engine has relied on different technologies. As of today, the debate still continues: can you use business rules for a rating engine? The definitive answer is yes.
Through a demo from real use cases, you will learn how to:
- Retrieve rates from a very large set of options
- Fine-tune rates, dealing with exceptions and overrides
- Manage rates over time, rolling over new price sheets over different time horizons per geography for example
This webinar is hosted by Carole-Ann Berlioz, Chief Product Officer at Sparkling logic
About Sparkling Logic SMARTS
Sparkling Logic SMARTS is an end-to-end, low-code/no-code decision management platform for business analysts and business users to leverage data, models, and business rules to automate and improve the quality of enterprise-level decisions.