17 Patrik D

The world we live in is changing. We live in a society of statistics. Companies don’t go out on a limb anymore, trusting their initial gut feeling. The law of large numbers helps major corporations understand more fully the decisions they are to make and paths they are to pursue. Insurance is no different. Insurance is an intangible product and is based on unforeseeable circumstances. It’s no wonder they attempt to determine a price by a statistical model that’s reliable. A fairly new variable in this model is a person’s credit score, which has been seen as an accurate indicator. But it comes at a cost. As with most decisions in life, this comes with a series of pros and cons. The pros include being able to better rate for drivers as a whole and avoiding adverse selection. The cons include possibly incorrectly rating for a specific individual and loss of business for a company.

Pro: A General Better Rate

Insurance is a statistical game. Insurance companies pay millions of dollars to have the most up-to-date statistics. Having a correct predictive model helps you understand how much money a company will need to pay out all their claims, which leads to the company knowing how much premium they should charge in order to match those claims and make a profit. Companies base their information on relative data. There is a direct correlation to several things: how old a driver is, gender, how many past accidents they have, how many tickets they’ve received, etc. This is very helpful to the firm, but one of the statistics that a company will trust heavily is person’s actual history with the company. If few claims are made, a company is much more trusting of this individual and can apply a very accurate premium. The opposite is true as well. The company will track this individual and gain invaluable data, which leads to the most accurate pricing. However, when a new customer wishes to get a quote, the company has no history of this individual. They’re basing their analysis on a few key characteristics and that’s about it. They’re taking on a lot of risk. However, a person’s credit score is a history of how this individual has performed. Insurance companies have shown that how bad a person’s credit has a positive correlation with how many claims are made. And that is the key; the people who’d produce more claims deserve to pay more to avoid making the company going insolvent.

Pro: Avoid Adverse Selection

Adverse selection is the key to insurance’s success. Adverse selection is avoiding high-risk clients who’d be unprofitable to the firm. A company will quickly go under if it’d keep selling insurance for $100 a month to people who make three to five claims of $1,000 each that same year. The principle of insurance is to be there for when your clients fall, but pick the people who are less likely to fall to begin with. Credit scores provide this additional information of people less likely to fall. If a person has a good record, the company can assume that the person is a responsible individual that won’t become a liability to the company. A person with a bad credit score is statistically someone who carries higher risk. Not only that, but this is a person who will most likely miss paying their bills on time and may eventually lapse off their insurance, which will cost the insurance in the end. A person has the right to cancel insurance off at any point and aren’t obligated to pay, due to insurance being a one-sided contract. In the end, if the insurance company picks the people with a good credit score they’re choosing less risk hanging over their heads.

Con: Individual Circumstances

As can be seen, there are multiple benefits to the insurance company, which leads to benefits to people with good credit. However, there are plenty of low-risk drivers who lie outside of the statistical norm. On a general basis, people with poor credit scores have that score correlate with their driving mannerisms. However, there’s many people whose driving ability are in-no-way related to their financial circumstances. These people can understand if a person had to pay higher for a past ticket, but the fact they’re unable to pay off debt on a credit card is requiring them to pay more because they’re “high-risk”? It’s very apparent why people would be upset with this methodology.

Con: Loss Business

As stated previously, there’s plenty of low-risk drivers that also bear a low credit score. Many times, an ideal client with a good driving record gets a quote with a company who charges higher than their competitors, driving their business elsewhere. In this process of enhancing their sifting process, companies are also weeding out good prospects as well. Are they putting too many variables in the equation? That’s a question for each company to answer.

Conclusion

There’s much controversy over this topic and both sides have valid points. Only time and practice will tell which method is most ideal for all parties.

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