Artificial intelligence in all departments of insurance companies

-

 There are many departments in insurance company like product development, underwriting, risk management, claim settlement, premium collection, marketing, accounts, human resource, information technology, law, planning and development, procurement, and others. Artificial intelligence can help of all departmental operations. Artificial intelligence helps in taking and analyzing the driver's data that helps to charge the customized premium as per need of driver for one day or hours or month. This customization and facilitation introduced usage base insurance concept. Artificial intelligence helps to analyse the data of policyholders to predict and categorize the high or low or medium risky profiles of different policyholders.

Accordingly it helps in charging the premium rate. This helps in cutting the cost spent on actuary and human error and time. Artificial intelligence helps to automize the accounting operations in calculating the all transactions. Artificial intelligence helps in marketing the insurance products by chatbot. It helps in maintaining and storing and analyzing the digital data of claim and premium collection from all policyholders. It helps in detecting the fraud and managing the risk. There are also alot of benefits. We can make regulation and plan to implement this technology with the help of trained and motivated staff.

Comments

Post a Comment

Please do not enter any spam link in comment box.

Popular posts from this blog

Machine Learning Algorithms in Agriculture Insurance

-
Machine learning has emerged as a valuable tool in the field of agriculture insurance, offering numerous applications to enhance risk assessment, improve productivity, and streamline processes. Here are some key areas where machine learning is being utilized in agriculture insurance:   Risk Assessment: Machine learning algorithms can analyze historical data on weather patterns, soil conditions, and crop performance to assess the risk associated with insuring agricultural operations. By identifying patterns and correlations in the data, these algorithms can estimate the likelihood of crop failures, diseases, pests, and other risks, helping insurers determine appropriate coverage and premiums.   Crop Yield Predictions: Machine learning models can utilize satellite imagery, weather data, soil information, and historical crop yield data to predict crop yields accurately. These predictions can assist insurers in setting coverage levels and pricing premiums based on expected production
Read more

IoT Timeline in Morocco and Insurance Sector

-
Image
  The use of IoT technology in Morocco is still in its early stages, but there have been some notable developments in recent years:   2017: The Moroccan government launched a national plan to develop IoT technology and promote its use in various sectors, including agriculture, industry, and smart cities.   2018: The Moroccan startup scene began to embrace IoT, with companies such as DataCare and Nectarin developing IoT-based solutions for healthcare and agriculture, respectively.   2019: In partnership with the French company Sigfox, the Moroccan telecom operator Inwi launched an IoT network covering more than 80% of the population, making it one of the largest IoT networks in Africa.   2020: The Moroccan government continued to invest in IoT technology, launching initiatives such as the "Smart Agri" program, which aims to use IoT to improve agricultural productivity and sustainability.   Overall, while IoT adoption in Morocco is still relatively low compa
Read more

Machine learning models in Pakistan agricultural data

-
Machine learning model can be applied on agriculture data to facilitate farmers in increasing the productivity. Pakistan is an agricultural country which has major portion in GDP. There is huge gap in this sector which can be fulfilled by adopting technology. Machine learning model can be applied on agriculture relating data to predict the disease or health of crops and to predict the climate change and to examine the impacts of other factors. This model can automate the processing of agriculture productivity. This model will also help the insurance sector to facilitate the farmers timely in case of tragedy or calmity. We need to train our youth in machine learning roles to increase the share of agriculture sector in GDP and economy.
Read more