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Case Study

Integrated Motor Insurance Data System (IMIDS)

Case Study

Integrated Motor Insurance Data System (IMIDS)

SwiftAnt designed and implemented an industry first, motor vehicle industry data aggregation and analytics platform for Kenya.

Digital C-A-R-E Methodology

CREATE |New business capabilities can be created

AVOID |Manual/redundant operations can be avoided/eliminated

REDUCE |Operational overheads/ manual tasks can be reduced

ENHANCE |Business capabilities can be enhanced

  • 37 Insurance companies (including multinational and large businesses like AIG, Allianz) sharing underwriting data and claims data in their own unique formats.
  • Addressed stringent data privacy and protection concerns through granular field level data access design and deep audit capabilities.
  • More than 650 users currently use the system
  • Several Millions of records dating back to 2013 are now available for search, reporting and analysis at the user’s finger tips & system tested for scalability.
  • Future ready architecture to ensure that the system will scale with the data growth (Cloud ready tested architecture).

Client Background

The Association of Kenya Insurers (AKI) was established in 1987 as an independent non-profit making consultative and advisory body for insurance industry. AKI's Vision is to be the leader in championing insurance growth and excellence in Kenya and beyond. AKI’s Mission is to champion and enabling environment for its members and promote growth and provide excellence in the insurance industry.

AKI has 37 Motor Vehicle Insurance companies as their members and AKI Secretariat sets the processes and best practise standards for the Motor Vehicle Industry in Kenya.


One of the big challenges is while the Motor Vehicle Industry is growing its revenues, the profits are being adversely impacted due to fraudulent claims To address this challenge and with several other objectives in mind, AKI initiated the IMIDS project. The proposed solution, “IMIDS” must be secure, able to handle large volume of data, remain stable, allow use by multiple users concurrently and have auto-backup and recovery and restore features. The overall objectives of the project are as follows:

  • Promote best practices through use of standard formats for processing underwriting and claims information across the industry;
  • Facilitate information sharing to assist members reduce risks and avoid losses through access to complete and accurate data;
  • Mitigation of fraud within the Motor Insurance Sector;
  • Promote good governance through compliance of regulatory issues.
  • Identify and detect fraud in the motor sector through centralization of underwriting and claims data;
  • Provide AKI members with a databank where they can make enquiries and references; and
  • To provide information on motor insurance which can be shared with the government and nongovernmental organizations.

IT Solution

Technical Solution overview ➜ Solution involves ETL processes for large data handling, Data warehouse, Customizable business rules, workflows for fraud-watch alerts & secure API interfaces with several 3rd party systems.

SwiftAnt team’s role ➜ Coordinate with all member companies deliver the design own the end to end implementation, collaboration with all stakeholders for requirements gathering & work with KPMG for Quality and Risk Management. The biggest challenge is managing 37-member companies, which are separate legal entities (outside AKI) and still stay within the time constraints.

Project Constraint(s) ➜ Solution must be implemented in 6 months as fully operational system with its members. System must be designed for high availability, scalability and guaranteed data security.

Solution Approach ➜ After brainstorming, SwiftAnt team recommended below 2 design considerations and they proved to be quintessential success factors:

  • Instead of forcing a standard of interface, with all the 37-member companies, every member company can provide the data in their custom formats. This will avoid programming changes in all 37 companies and they can push the data in their current formats. This significantly reduced the risk of external dependencies with 37-member companies.
  • Architecturally, adopt micro-services architecture (vs traditional monolithic design) such that development times can be significantly reduced & several parallel teams can have focused and limited scope. This lead to be a significant advantage in managing the scope, and effectively utilizing the Client subject matter expert’s time.

Client’s involvement ➜ The entire solution was presented as “UX Prototype”, in the first 4 weeks such that, client personnel do not have to go through textual descriptions to understand the to-be system. This led to effective involvement of the Client personnel. With agile development, Client was continually involved in the project & involved its members continually. The system integrations were delivered in agile manner.


Quality Results :

  • Average Immoderated Score : 95%
  • Average Moderated Score : 97%

Timeline results : The project was delivered with 5 weeks delay even after 11 weeks of not a very conducive environment due to Kenyan elections and associated disturbances and additionally the year end vacation times. AKI and SwiftAnt teams coordinated very well during the 11 weeks of elections time.

Additional Information

  • This project is a classic example of “Pay after Delivery” model. SwiftAnt team invoiced AKI incrementally only after member company data integration was successfully integrated and system testing was signed off (in agile manner in 6 iterations).
  • Post the project go-live, SwiftAnt team has continually analysed the data quality and made actionable recommendations to each of the member company, to improve effectiveness of the system results.
  • SwiftAnt team has presented the solution in CEO forum in Kenya and Uganda (demonstrating the Business-Technology outlook of SwiftAnt).