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 BFSI
Business Requirements
- Client was using Genesis CRM since 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 scalability point of view but also for achieving higher availability. We hosted it over 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
Benefits:
- Average Insurance Selling increased by 50%
- Onboarding Process Time Improved by 50%
- Capture policy data without internet connection and Sync
- Business-ready system to accommodate exponential customer growth
- Digitally enabled people with the digital process, tool & technology
- Real-time easy access to structured and unstructured data through one platform
- Increased in 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%