MSME Microinsurance and Convolutional Neural Network Skills
A significant portion of the world does not have formal identification for financial services. Some of these populations have small businesses or work as independent contractors and do not have insurance. In terms of insurance, there is often a lack of data for determining pricing and forecasting claims. Some small home based businesses creating crafts and other small items may have owners who are migrants without proper identification. Collecting data for property insurance can consume time and energy. Along with the above, there can be obstacles to providing microinsurance services as a solution.
The proposed solution is a microinsurance program for micro, small, and medium enterprises (MSMEs) that also provides an education resource for communities by means of the machine learning techniques used in forecasting. Identification of the business and the owner can be generated by means of completing the policy. The MSMEs will have insurance in event of a general claims as well as for unexpected weather from climate change. The business owner provides information on the business as well as on the construction methods of the business, which may be the home of business owner, and related data, which helps the insurer maintain data for managing risk. A pre-paid credit card is provided to the insured which can only be used for claims.
With what is microinsurance, the insurer will need to forecast pricing and claims. With insurance for businesses, there are a variety of features that may be unique to particular regions of the world.
Methods in artificial intelligence are able to process the image data of business client locations with computer-based visual processing, find features in the data for forecasting future trends in possible claims. The main technique envisioned is by means of the use of convolutional neural networks (CNN), of which is the focus for this solution. A program like this of applying artificial intelligence to analytics can introduce IT skills to staff as well as to the community. Multiple microinsurance programs can pool data in order to create large datasets.
The proposed solution is applied by means of a free online course that philanthropic organizations can use for the application of microinsurance and microfinance program for poor communities around the world.
Population with lack of access to financial services and working in low-income businesses.
The idea appears to be innovative and affordable. The developer of the program has 20 years of experience with property and health insurance.
- Help gather, synthesize, or use relevant data to inform the design of insurance products tailored to populations at greater risk of facing shocks such as climate disasters, health-related shocks, and unstable markets
- United States
- Prototype: A venture or organization building and testing its product, service, or business model, but which is not yet serving anyone
It is an online course.
None at this moment.
The solution could readily help many people.
It is providing resources to existing microinsurance and microfinance programs by means of assisting the professionals working in the programs as well as the communities that they serve in terms of the application of the skills for forecasting to information technology skills.
- 3. Good Health and Well-being
- 5. Gender Equality
- 8. Decent Work and Economic Growth
- 9. Industry, Innovation, and Infrastructure
- 10. Reduced Inequalities
The measure of progress is actually how well staff in the microinsurance and microfinance programs are learning the technology mentioned in this presentation. There is also a secondary measure of how familiar the community being served is familiar with the said technology.
The core technology is neural network technology for finding features in the datasets that exist as well as those that will be generated.
- A new application of an existing technology
- Artificial Intelligence / Machine Learning
- Not registered as any organization
- Individual consumers or stakeholders (B2C)