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3 Technologies That Enhance Insurance Risk Assessment (2024)

Cem Dilmegani
Updated on Jan 13
4 min read

Insurers trade the potential financial harm of their customers for a premium price. Therefore, it is critical for them to estimate the likelihood of a claim arising correctly. This is known as risk assessment, and it accounts for a significant amount of the premium price clients pay.

The difficulty is that the best pricing is a key priority for both commercial (business) and non-commercial insurance consumers, which indicates:

Figure 1: Distribution of economic profit of insurance companies

Only the top quintile of insurance companies are highly profitable.
Source: McKinsey

In this article we present 3 technologies that improve risk assessment. By using these technologies insurers can reduce safety margins and costs thanks to efficient risk assessment. 

1. Video chat platforms improve site specific risk assessment 

Generic risk assessment strategies that employ data and responses to questionnaire forms to evaluate certain metrics are beneficial for measuring work-related risks in certain industries. However, when it comes to risk assessment, categorisation might be misleading because each factory has its own set of employees, location, equipment, and infrastructure.

On the other side, depending on your customer portfolio, site specific risk assessment using traditional approaches can be expensive. Many businesses, for example, have facilities or factories in distant areas (even different countries).

Today, there are video chat capabilities which allow risk engineers to assess risk remotely. Remote site specific risk assessment capabilities bring insurance companies following benefits:

  • It reduces the cost of traveling expenses.
  • It speeds up risk assessment since risk engineers do not lose time on the road.
  • It reduces corporate greenhouse gas emissions.
  • Because risk scoring combines both objective and subjective assessments, it lowers biases. When insurance firms must underwrite a business with several sites, subjective judgment may vary from expert to expert. Remote assessment, on the other hand, ensures that a single risk engineer may analyze several locations in a short amount of time.

2. IoT devices improve data availability

Smart devices (IoT) such as smartphones, watches, automobiles, and factories are all around us, providing real-time data from their surroundings. Therefore, insurers can gain a greater understanding of their clients and the health of their insured assets, and use this knowledge to:

  • Perform more precise risk assessment.
  • Transforming risk assessment from a static process to dynamic one and nudging their customers to act responsively as a loss prevention strategy. 

Table 1 compares insurer data availability before and after the IoT. Take, for example, health insurance. Insurers can get personal information about their customers via smartphones and wearables, such as daily exercise data, sleep quality data, and heartbeat data. Surely, availability of such data improves risk assessment. 

Furthermore, the availability of such data opens up the possibility of adjusting premium prices based on client behavior. Some health insurance firms, for example, offer lower premiums if their customers exercise more. Similarly, several auto insurers offer discounts to customers who drive more cautiously. Because such behavioral changes imply less claims for insurance companies.  

Table 1: Comparison of pre-IoT/post-IoT period variables.

Pre-IoT variablesPost-IoT variables added on Pre_IoT variables
Health Insurance
1) Age of Insured 2) Answers to the questionnaire 3) Doctor report
1) Daily exercise data 2) Sleep quality data 3) Heartbeat data
Automobile Insurance
1) Segment of car 2) Previous accidents/ Police reports 3) Driver's age
1) Number of full breakes per mile 2) Miles Driven 3) Location of driving and average speed
Commercial Property Insurance1) Answers to the questionnaire
2) Industry
1) Heat of equipments used
2) Frequency of equipments used

3. AI models improve conducting quantitative risk assessment 

Various of AI models are effective solutions for interpreting data and automating risk assessment process as follows:

  • Advanced Analytics: Each variable (such as driving speed, driving location, age, gender, and so on) is related to risk in a certain way. When compared to manual methods, advanced analytics are useful tools for obtaining parameter values for each variable and making quick computations.
  • Optical character recognition (OCR): Is a subset of natural language processing that aids insurers in automating underwriting. According to Accenture, underwriters spend half of their time on repetitive duties like data entry. Information can be extracted from digital documents using OCR. As a result, insurers can use OCR to extract data from medical reports, questionnaire forms, and other documents.
  • Chatbots: Chatbots can conduct with insureds to interview with customers to derive information. 

It is important to note that low/no code platforms can ease the deployment of AI models for insurance companies.

You can also read our AI in Underwriting: Data-driven Insurance Operations article to learn more about use of AI in underwriting and risk assessment. 

How can insurance companies speed up their digital transformation process?

Collaboration with insurtech startups is the simplest and most cost-effective approach for insurance companies to accelerate their digital transformation journey. According to IBM, more than 80% of incumbents have purchased, merged, or partnered with insurtechs in order to use technology in their operations.

Many insurtech companies create cloud computing solutions to help incumbents improve their claims processing, underwriting, fraud detection, and customer service skills. Numerous insurtechs promote their platforms as “insurance as a service,” implying that incumbents must pay a monthly subscription price to use cloud computing services. AIMultiple considers this strategy is a reasonable one if incumbents cooperate with a suitable insurtech.

You can read our “Top 7 Innovative Insurtech Companies of 2023: Detailed Guide” article to get inspired by the groundbreaking methods of insurtechs.  

You can also use our sortable/filterable insurance underwriting platforms and top insurance suites lists to find a suitable insurtech company that helps you on your digital transformation journey.

If you need further information about risk assessment or underwriting in general we can help:

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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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