You might be surprised to know that ‘how you drive’ is not even considered when your car insurance premium is calculated. Imagine your future employer hires you based on your marriage success and not your competencies for the job
When it comes to cars, insurance companies are generally clueless about how safely and responsibly you really drive. It’s purely a technological shortcoming of the industry that makes them use century old methods to estimate how risky it is to cover you and your car. In the current industry practice, other factors rather than how you drive are statistically analyzed to estimate your risk.
But if ‘how you drive’ is not considered relevant for estimating the risk of your driving, then what is? Here is a list of factors about you that are currently considered relevant for calculating your driving risk:
Address, gender, marital status, bank credit score, job, age and your level of education.
If you feel that these factors are absurd and discriminatory, you are not alone. the Consumer Federation of America (CFA), has found that such practices penalize lower-income, lower educated drivers compared to their peers with greater education and higher net worth.
According to CFA research, good drivers of lower economic status consistently pay more for car insurance than higher economic status drivers, even when they have perfect driving records. All of this is happening because the most important part of the puzzle, ‘how a driver actually drives’ is completely discarded. But what is the solution?
Compared to the traditional approach, factors derived from driver behaviour have far more significance, even to the insurance underwriters themselves. A research conducted in Taiwan showed that auto insurance experts find driver’s dangerous maneuvers more relevant than age, sex etc. According to their analysis, the top twenty underwriting data from the most important to the least important are: (1) rapid acceleration, (2) daily number of drives, (3) time of the ride, (4) hard braking, (5) fast lane change, (6) hard cornering, (7) insurance score, (8) miles driven, (9) the weather, (10) number and types of cars, (11) driver’s education, (12) driver’s age, (13) where the vehicle is driven, (14) individual driving record, (15) airbag deployment, (16) traffic information, (17) marital status, (18) territory, (19) gender, and (20) the use of the auto.
Smartphone-based telematics solutions and other similar technologies provide a direct way of quantifying and integrating driver’s behaviour and skills into the process of insurance premium calculation. Such systems are capable of analysing smoothness and safety of the driver, without being intrusive or disclosing privacy of the driver.
In order to improve the effectiveness of the underwriting decision making, insurance companies need to take advantage of IoT and telematics to collect more helpful underwriting data as well as adjust their underwriting policy accordingly. By relying on data that actually matters about the driver, unwanted discriminatory factors lose their importance in deciding premium rates of auto insurance.
ـــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــــ
References:
http://www.actuarialpost.co.uk/article/telematics-as-an-underwriting-tool-7454.htm
https://www.moneycrashers.com/factors-affect-car-insurance-rates/
https://www.insurancequotes.com/auto/study-how-poor-credit-double-auto-insurance-rates-82218
https://www.carinsurancecomparison.com/how-job-affects-car-insurance
https://www.carinsurancecomparison.com/car-insurance-occupation/
https://www.thezebra.com/auto-insurance/driver/profession/
https://ecarinsuranceprices.org/surprise-job-can-affect-car-insurance-rates/
https://ideas.repec.org/a/spt/admaec/v7y2017i1f7_1_2.html
A Comparison of Underwriting Decision Making Between Telematics-Enabled UBI and Traditional Auto Insurance: Link
