Executive Summary
Al-Etihad Cooperative Insurance Co., a prominent Saudi insurer offering a diverse range of commercial and personal insurance products, faced challenges in managing and analysing their premium and claims data. The reliance on Excel for data processing led to inefficiencies, increased risk of errors, and delays in actuarial assessments, hindering timely strategic decision-making.
The Solution
BADRI developed and deployed a comprehensive Actuarial Technical Analysis Tool using the Qlik Sense platform. This solution integrated data from multiple sources, transforming and visualizing it through QVD structures, enabling real-time analysis of premiums, claims, reserves, and recoveries across various lines of business.
The Outcome
The implementation resulted in significant improvements in data processing speed, accuracy, and decision-making capabilities. Actuarial teams now benefit from interactive dashboards, automated validation checks, and robust drill-down functionalities, enhancing their ability to perform detailed analyses and make informed decisions promptly.
Background and Context
Organization Overview
Al-Etihad Cooperative Insurance Co., established in 2006, is a leading provider of insurance services in Saudi Arabia. The company offers a wide array of products, including motor, health, property, marine, engineering, and medical malpractice insurance, catering to both individual and corporate clients. Al-Etihad is recognized for its strong market position and has received an A3 financial strength rating from Moody’s, reflecting its solid asset quality and capital adequacy.
The Initial Situation
Prior to the implementation of the BI solution, Al-Etihad relied heavily on Excel spreadsheets to manage and analyze premium and claims data. This approach led to several challenges:
- Manual data compilation from disparate sources
- Delays in generating reports and conducting analyses
- Lack of a centralized, real-time view of actuarial data
- Limited capability for historical trend analysis and segmentation
The Implemented Solution
Objectives
Replace Excel-based processes with an automated BI platform
Enable real-time access to comprehensive actuarial data
Implement modules for reserves analysis (UPR, OSLR, IBNR)
Enhance data accuracy through automated validation checks
Support advanced segmentation and large-loss analysis
