The proposed project “Risk Assessment and Underwriting Software”, is for developing software to help insurance underwriters properly evaluate policy applications, assess available risk information of an applicant, and appropriately determine coverage levels and premiums.
The idea for the project was to automate and bring advanced analytics into the underwriting process so that the underwritten policy/contract is profitable, the risk is also mitigated in a manner that makes underwriting competitive in the insurance market. Thus, to gain profitability and competitiveness, the development will include risk analysts, data scientists, software developers, and insurance professionals coming together to develop and advance the project with data analytics and actuarial predictive analytics.
Week 1-2: Initial Planning and Requirement Analysis
Define high-level objectives, scope, and requirements of the project.
Collection of data and resources needed to be initiated.
Week 3-5: Data Collection and Preprocessing Phase
Collect and preprocess historical policy and claims data.
Analyze data to identify relevant risk factors.
Week 6-8: Model Development and Training Phase
Developing and training machine learning models and actuarial models for risk assessment.
Validate the model's accuracy and performance using historical data.
Week 9-10: Software Integration and Testing Phase
Integrate the risk assessment and underwriting software with the existing insurance systems.
Test and refine the software based on user feedback and performance metrics.
Week 11-12: Deployment and Monitoring Phase
Deploy the software in the insurance environment.
Monitor software performance and make necessary adjustments.
