Data is a powerful tool. For decades, insurance companies have been using the data available to them to measure risk and determine pricing. But as technology evolves, so do the data practices insurers use to optimize pricing and risk. Machine learning is a new tool that goes beyond what an actuary can craft, and the impact it will have on what you pay for insurance is becoming noticeable.
Understanding Machine Learning
Machine learning enables computers to learn without human intervention. The computer acquires data and predicts outcomes without manual input. As machine learning gains more data and adapts to the past, its future predictions become more accurate.
In insurance, machine learning can act like an underwriter. As a novice underwriter, you need loads of data to make a decision. As you gain data and analyze outcomes over time, you become better at assessing risk, predicting losses and calculating premiums. Machine learning in insurance is a tool that will help the underwriter make decisions with more precision.
Optimization of Premium Dollars
In 2017, the insurance industry accounted for 3.1 percent of the U.S. Gross Domestic Product (GDP), contributing more than $600 billion to the economy. With so much at stake, optimizing premium is pivotal. With machine learning, insurance companies can analyze immense amounts of data to create the ideal premium for each consumer.
Think about your own personal auto insurance policy. There are many factors that impact your premium, including:
- Your car’s make, model and year
- The number of miles you drive
- Where you live
- Your history of accidents
- Your age
- The number of years you’ve had a driver’s license
Machine learning can collect this data on millions of drivers and use it to recognize patterns and assess risks, which helps insurers craft tailored premiums for each consumer.
Decreasing Premiums, Improving Combined Ratio
Insurance companies are always working to improve their “combined ratios.” While this term may sound like industry jargon, it simply compares the amount of an insurance company’s payouts and expenses to the amount they brought in via premiums. For instance, if a company with a combined ratio of 99 percent, it means they earn $1 in profit for every $100 in premium their customers pay. A combined ratio of over 100 percent means they lose money on each dollar of premium. The goal of machine learning in insurance is to offer customers competitive premiums, while simultaneously decreasing the loss and expense ratios.
The Impact on the Consumer
To insurance companies, data is golden. The more data they’re able to collect, the more accurately they can assess your risk, and thus, your policy premium. What’s more, machine learning can help implement these changes with a lower personnel cost, which could allow them to offer customers a lower premium. So, if you have good driving habits, machine learning could mean a reduction in your premium. If you are high risk, insurance companies may be more likely to increase your premium charge, as they’ll be able to more accurately assess the risk exposure you present.
As insurance providers gain more data, so do consumers. Technology like augmented reality may soon fill up the windshield of a consumer’s vehicle. Powering the consumer with information overlays may help drivers become more aware of their own driving habits, which could reduce the risk of accidents. Say you are a driver that, based on historical data, tends to push the speed limit a bit. An augmented reality overlay could alert you to current speed limits, encouraging you to lay off the gas a bit. The combination of this data in front of you, as well as the stream of data being fed back and forth between your car and your insurance carrier, could lead to fewer accidents, more accurate pricing and potentially lower premiums.
Machine learning is a powerful movement in the insurance industry. Thanks to real-time smartphone applications that monitor driving habits, insurers are putting the power to save money in all of our hands. As data expands, so do the opportunities machine learning presents. This technology is likely to change the insurance industry, and consumers will see the impact where it matters most — in their pocketbooks.
Authored by: Haden Kirkpatrick
Haden Kirkpatrick is the head of marketing strategy and innovation at Esurance. Haden is constantly thinking about how IoT, blockchain and machine learning, and he shares his predictions by writing about how these technologies will impact the car insurance industry. Learn more about Esurance’s car insurance policies here.
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