Pricing of insurance premiums has been very straightforward. You have a mortality table which is age and gender specific. In general men are charged more because historical data shows that more claim payouts are done for males. And why is this so? Because the historical data has not been re-analyzed for quite some time now. Men have in the past been in jobs where the probability of death was higher. More men fought in wars, more men were involved in high risk jobs like mining, construction and hence more death claims payouts for men. And this gender bias still continues today.
Health insurance is the opposite. Generally it is believed that more health claims related payouts will be done for females as compared to males. Again this is because of the past experience which is not true now. Should a re-anlaysis be done on the past 10 years data rather than past 50 years data. There has been sufficient adavances in health services. More people now have access to better doctors and health facilities. If there are diseases which affect women then there are diseases which affect men more as well. And further to this what about people in the same age group. Why two people in the same age group are considered to be the same.
Today with Artificial Intelligence and smart devices (IOT) we have the capability to decide what is the right premium for health insurance for each individual. We can use wearable device to collect key vital data like Heart Rate, SpO2, ECG, PPG, Blood Pressure and Activity details and the use AI and ML to analyze this data to work out a health score for each individual. In addition each individual can be advised on what exercise plan works for him and what is the best diet for him. As you gather more information and from a much larger pool, within a short time we can have a highly accurate predictable model which helps to ascertain each individuals health score. Thus allowing you to price the same health insurance policy differently for each individual. In addition continuous monitoring allows you to give benefits to people who improve their health score, so that they get discounts on premiums because their health scores have improved. This model actually allows you to adjust premium on a monthly, weekly or even daily basis. Thus a true dynamic insurance pricing based on health score.
cover2protect has integrated with high grade wearable and their AI program is able to provide a health score. As the machine learns and cross analysis data from different user segments with different lifestyles and super imposes this with each individuals social footprint the health score accuracy will be as high as 90 to 95%. A unique model which allows an insurer to work on real time data and real time analysis. A model which does not baseline individuals on simple statistics but on actual health score. Continous monitoring allows for dynamic adjustments of premiums so that the risk is covered by the correct dollar amount.
A step into the future of insurance has already been taken. A step which uniquely identifies each individual and charges based upon the real risk and not assumptive risk.
As we say prevention is good but prediction is better.