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Insurance Pricing: Determination & New Methods in 2024

Cem Dilmegani
Updated on Feb 14
5 min read
Insurance Pricing: Determination & New Methods in 2024Insurance Pricing: Determination & New Methods in 2024

According to Accenture, getting the best price is the top priority for 52% of auto insurance customers, 50% of home insurance customers and 38% of life insurance customers. Study implies that although there are other criteria for customers, determining the optimal price is the biggest competitive advantage for insurance companies. As the KPMG study shows, for B2B buyers and SMEs the best price is the also top priority.

What is insurance pricing?

Any company aims to set prices to maximize its profits. This is also referred to as optimal pricing. It is not different in the insurance sector. Ideal pricing (or premium in insurance terminology) must cover:

  • Variable costs
  • Operating expenses
  • Profits

Setting an optimal price depends on understanding costs, price elasticities, consumer preferences, and the strategic actions of competitors.

Why is optimal insurance pricing important?

Setting an optimal premium price provides a competitive advantage for the firms.

As in any industry, the price is subject to the law of demand and supply. Since getting the best price is the top priority for insurance customers, even a small percentage change in premium prices causes many customers to switch providers. Therefore, optimal pricing in the insurance sector enables profit maximization by allowing operators to gain market share in segments of their choice (e.g. more profitable segments).

McKinsey’s study supports this argument. As the below chart demonstrates, average profit distribution in the insurance sector varies significantly. McKinsey argues that the most profitable insurance companies use technology-enabled underwriting processes to effectively set premiums.

Image shows that only the top 5% of insurance companies can make significant economic profit.
Source: McKinsey

Top 6 ways of achieving optimal insurance pricing

As mentioned earlier, determining the optimal premium involves minimizing variable costs, operating costs, and optimizing the desired profit margin. For insurance practice, this means:

  1. Increase the efficiency of the underwriting process (minimizing variable costs).
  2. Detecting fraudulent claims more effectively (minimizing variable costs).
  3. Minimizing the customer service, rent and other expenses.
  4. Realizing the realistic profit margin that does not lead to a reduction in the customer satisfaction. (Respect the law of supply and demand).

Minimizing Variable Costs

1. Minimizing the cost of risk bearing service (more effective underwriting)

The most important variable cost for insurance companies is the determination of the cost of risk.

Each insurance policy can be described as an exchange of risk for money. Thus, each realized claim represents the variable cost of the insurance sector, which is difficult to determine compared to the variable costs of other sectors. For example, in the case of manufacturers, the variable costs, such as raw materials, are fairly certain, which makes it easier to minimize it. In the insurance sector, on the other hand, variable costs are a probabilistic distribution. Therefore, it is challenging to minimize it.

In order to evaluate the risk, insurers check some statistical data about the person or company applying for the insurance (subject variables) or about the object to be insured (object variables). For example, in car insurance, insurers evaluate variables such as the segment of the car, the age of the policyholder, the mileage and previous penalties of the policyholder, etc. The idea is that there is a relationship between these variables and the expected damage that would cost the insurance company.

Before AI/ML algorithms, primitive risk assessment models like linear regression and generalized linear model (GLM) were used for interpreting statistics. Nowadays, AI based underwriting assesses risk with more sophisticated analytics. Also, data was scarce before the growth of IoT devices. Therefore, insurers can assess risk more precisely today. Uncertainty of variable cost diminishes for the companies that adopt new technologies effectively. Such a progress makes it easy to determine optimal prices for insurance companies and provides a competitive advantage.

Image demonstrates the relationship between optimal insurance pricing and effective risk assessment and underwriting by using exponential data and technologies like AI/Ml models.
Source: Deloitte

2. Detecting Fraudulent Claims

According to the Coalition Against Insurance Fraud, fraudulent claims cost the U.S. $80 billion per year. 

Fraud is a factor that increases the costs for insurance companies and thus increases the premium prices. Therefore detecting fraudulent claims more effectively can be used either to increase profits or market share. Fraud detection may be enhanced by using AI/ML models:

  • Using behavioral analytics increases the probability of foreseeing some fraudulent claims before they occur. For instance, analyzing customers’ habits, companies can determine whether their behavior is consistent or not. If there is any suspicion, companies can investigate further.
  • Automation of claim processing with chatbots that direct policyholders to capture streaming video of damage can reduce fraudulent claims by providing evidence to support the claimant’s description

Using NLP and computer vision technologies to detect fraud more efficiently. For example fraudulent documents can be identified using computer vision techniques

For more, you can check our article on insurance fraud detection.

Minimizing the operating expenses

Various business expenses such as customer service, rent and other expenses can be decreased thanks to technological advancements. This can help insurers give more flexibility in pricing. Some examples of operational efficiency improvements include:

3. Optimizing customer service

Insurance chatbots and omnichannel engagement with clients can significantly reduce customer service-related expenses and increase customer satisfaction due to:

Also, predictive analytics, can assist insurance companies to prioritize their customers who need immediate claims processing, which in turn lowers operating expenses.

4. Reducing rent expenses

Millennials and urbanites generally demand less physical interaction, and this process has accelerated following the Covid 19 pandemic. Thanks to digital technologies and applications insurance companies and brokers can benefit from this recent trend and reduce the number of branches. This means lower expenses and more room for maneuver in terms of pricing strategy.

5. Reducing other operating expenses

One of the cost drivers in commercial insurance is inspections. Plants and equipment need to be inspected for validating their current status and identifying relevant risks. Companies can outsource these inspections, lowering their costs.

6. Determine a realistic profit margin

Jeff Bezos famously said “Your margin is my opportunity”. This is definitely relevant in the insurance industry as identified in surveys. Venture funded companies are embracing that paradigm to set aggressive prices and gain market share. Their goal would be to dominate the market and set more profitable prices in the future when they have achieved substantial scale.

Therefore, insurers need to take multiple factors in the account while pricing:

  • Competitors’ pricing, including some irrational moves by competitors.
  • The fact that market is mature.
  • High price elasticity.

It is important to note that while price is the greatest priority, it is not the only important factor that pulls the customers. Claims processing speed and effectiveness, customer service, consumer friendly digital interfaces etc. are all important factors for consumers picking an insurer. Therefore, success in these areas may help charge a higher profit margin for your products.

Further readings

You can check our selection of 3 articles on the use of digital technologies in the insurance sector:

You can also check our top insurance suites and top pricing software lists.

If you need more information regarding the latest in insurtech and identify top vendors, we can help.

Find the Right Vendors

This article was drafted by former AIMultiple industry analyst Görkem Gençer.

Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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