Artificial Intelligence and Machine Learning Help Insurers Develop Responsive Coverage Solutions 

For most Property & Casualty (P&C) insurance companies, the COVID-19 pandemic prompted several strategic and operational changes complicating an already challenging business environment. To facilitate these operational changes and overcome subsequent challenges, insurers are now leveraging Artificial Intelligence (AI) and Machine Learning (ML). Specifically, the combination of AI and ML can help insurance carriers digitally transform outdated methods and develop responsive coverage solutions to meet the ever-changing customer needs and stay ahead of the competition. 

AI and ML: Why Are They Critical in the Insurance Industry?

AI and ML offer the intelligence and data comprehension capabilities not possible with the human mind due to the expansive amount of data and processing power required to perform such tasks. The technology collates and analyzes a range of data sets to find trends, answer questions, and provide insights that help insurers make informed and data-driven decisions about different areas of their businesses. Importantly, leveraging the power of smart technologies can help the insurance industry to:

  • Increase operational efficiency and cost-effectiveness
  • Mitigate risks by detecting waste, potential fraud, and unordinary activities
  • Accelerate growth through scalable solutions and meaningful innovations

What Is the Difference Between AI and ML in the Insurance Industry?

While AI mirrors human thinking, solving problems identified from analyzing enormous data-sets, ML learns and improves by carrying out practical aspects of the insurance process. Machine Learning enables the continuous refining of insurance processes so that services and coverage become more targeted. Using machine learning, insurance companies can offer more personalized services and customer experiences from insights learned from existing client data.  

How AI and ML Help Insurers Develop Responsive Coverage Solutions

Better Anticipation of Coverage Preferences

As the insurance sector marketplace heats up, companies are in a tight race to offer more innovative products and services to gain an edge over their competition. With so many options to choose from, people are becoming increasingly picky with their purchases. Insurers can leverage the solutions offered by AI and ML to better anticipate the coverage preferences of their existing customers and prospects and improve overall satisfaction. Claims and underwriting agents can leverage AI to predict needs and purchasing behaviors and communicate with prospects at the right time in their buying journey to recommend the products they are most likely to buy.

Enables Personalized and Accurate Policy Underwriting

Typically, there are four types of insurance coverage everyone needs. These include life insurance, health insurance, Long Term Disability insurance, and auto insurance. Customers looking for any of the products expect to receive personalized services that meet their needs, preferences, and lifestyle. Advanced analytics offered by Machine Learning can help insurers draw data about individual preferences, behaviors, lifestyles, and hobbies to create personalized products. Additionally, behavior-based machine learning models enable insurance companies to predict customer lifetime value (CLV) to assess the customer’s potential profitability and create a more personalized marketing offer.

More Sophisticated Rating

In the insurance industry, a rating is the heartbeat of sound underwriting decisions. Ideally, insurers can comfortably accommodate most risks, provided they find a good match in pricing. Unfortunately, most insurers still rely on traditional tools to evaluate risks. The result is that individual customers end up being assessed using outdated indicators such as credit score and loss history that don’t reflect on their actual risk level. Insurance agents can leverage machine learning to classify risks precisely and calculate more accurate predictive pricing models that suit individual customers based on their risk level.

What Are the Most Popular AI Applications in the Insurance Industry?

Some of the most popular Machine Learning applications that most industry leaders use includes:

Chatbots and AI assistants: These tools are used to respond to internal agent inquiries and in the provision of guidance on business protocols. They are not typical AI applications but they utilize this technology to maximize their efficiency.

Driver performance monitoring: Deep learning algorithms are applied to client data to help customize products for clients and meet their specific needs.

Insurance market analytics: Machine Learning algorithms are also used to interpret driver data for agents to monitor market trends and locate opportunities faster and more efficiently.

Are You Ready to Ride the Wave of AI and ML Efficiency?

Today, the insurance sector is undergoing a massive digital transformation thanks to the quick adoption of intelligent technologies. Insurers are leveraging the power of machine learning to enhance their efficiency, improve customer services, develop responsive coverage solutions and detect fraud. 

If you are eager to optimize your operations with AI and ML, OZ can help you identify the right prioritization for your business now. Contact us today.

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