Check out how one of our leading South African Insurance Company Achieved 10X more customers by integrating CRM workflows by reducing onboarding time by 50% and eliminating tedious manual processes during their digitally transformation journey.
About Client
The client is a leading service provider in the insurance domain since 25+ years, that engages with multiple insurance companies by offering white label solutions/products to their customers in South Africa with a 750,000+ client base
Country South Africa
Industry Insurance
Business Requirement
- Client was using Genesis CRM for a long which was built with a legacy technology & architecture which made managing 10 million databases of customers quite difficult
- There was multiple manual paper-based process, e.g., claiming the amount (covered under Insurance), due to which manual mistakes and delays were occurring
- Client was looking for a strategic IT service partner who could manage their end-to-end digital ecosystem
- Non-scalable systems needed to be resolved
- Restricted business growth needed expansion
- Dependency on people needed to be lowered
Our Solution
- During the discovery phase, we provided the consultancy to identify and implement the new CRM system
- Implemented microservices (migration from monolithic) based architecture to meet the desired numbers, not only from a scalability point of view but also for achieving higher availability. We hosted it over the cloud for security reasons, followed by DevOps to speed up the deployment process
- Used low code tool called Warewolf and developed more Microservices on top of it to maximize efforts
- Digitized the insurance sales by developing a mobile app for agents to capture the policy details. Adding to the same, customers were able to claim insurance amount with all necessary approvals & payments effectively
Key Features
BI & Data Analytics
- Management report
- Collection report for policies
- New sales report and more
Applied ML to make the CRM system intelligent for future predictions: integration with expedia to customer data and predict policy plan
- ML initials – To predict the affordability of a customer on the initial sales
- ML ongoing – To predict the customer’s propensity to pay for next month and based on that, take them through various journeys
- Next best offer – To predict the next best product that we offer to have a higher success rate on the conversion
Tools & Technology
- Platform: MS Azure, Docker & Kubernetes, MS Dynamics
- Technology: .NET Core, Angular, WAREWOLF (Low Code Tool), React Native, Redux form
- Database: MS Azure SQL, Elastic Search
- BI: Tableau, Power BI & SSRS
- AI: Python, Xgboost & Scikit Learn libraries, Pyodbc/PYsql and Matplotlib/Seaborn
- Tools: Jenkins, Bitbucket
Business Outcome
- Average Insurance Selling increased by 50%
- Onboarding Process Time Improved by 50%
- Capture policy data without an internet connection and Sync
- Business-ready system to accommodate exponential customer growth
- Digitally enabled people with the digital process, tools & technology
- Real-time easy access to structured and unstructured data through one platform
- Increased Customer base by 10 times with the implementation of new architecture and ML
- Document rejection due to wrong field capture decreased by 18%
- Saved development efforts by 20%