AI in Property Insurance: Two Letters, One Massive Impact

Employing artificial intelligence in the real estate industry begins with good property data

With the rise of Chat GPT – the sophisticated chatbot developed by OpenAI – artificial intelligence (AI) has exploded into public consciousness over the last year. It has also changed the way people live and work across all industries, including the property insurance industry.

As we learned at INTRCONNECT 2024, AI is poised to transform processes across the industry over the coming years. But just because technological change is coming doesn’t mean people should fear AI. The technology won’t replace professionals across the property insurance ecosphere. 

Instead, AI will enhance jobs and allow people to concentrate more on the human component of their work. It will allow them to focus on the lives behind the buildings they are insuring, protecting, and restoring. 

Many processes that are integral to the property insurance ecosystem, such as bulk processing claims to look for anomalies or filling out forms in the field, can now be expedited thanks to AI. This not only helps insurance and reconstruction professionals  efficiently make accurate, objective, data-driven decisions, but it reapportions time commitments so that professionals can spend their days on uniquely human tasks like empathizing with policyholders that have suffered a loss event or combing through cases that merit additional scrutiny. 

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AI technologies will continue to streamline claims processing and determine repair costs by assessing property damage photos. It will drive more accurate risk assessments for underwriters to improve their rate determinations.  AI can also analyze data to predict certain natural hazard risks so insurers can better prepare their policyholders to weather storms with resilience . 

With AI-driven insights derived from customer data analysis, insurers can also develop personalized products. Organizations can use AI capabilities to understand the emotional context of customer conversations and help employees better guide their responses to policyholders.

At the same time, AI is not an all-or-nothing proposition. There are ways to manage its influence within an organization. 

Find an AI Investment That Fits

Depending on the needs of your business and its customer, there are different levels at which a company can invest in AI.

When it comes to the implementation of this technology, an “investment” refers to both the time and money that is required for the AI technology to operate as intended. Typically, the larger the role AI plays in a company’s digital ecosystem, the larger the financial investment. More substantial commitments to AI will require programmers and other professionals to spend more time training and preparing AI models to work autonomously.

Conversely, a lower-level investment in AI may involve implementing tools that do not directly impact customers. For example, systems with lower degrees of AI are limited to functionalities that automate, streamline, and optimize workflows without a decision-making process. Decisions at this level of AI investment remain with the humans who are “in the loop.”.

According to the Harvard Business Review, “human-in-the-loop” AI models involve humans making decisions, with the machine limited to decision support. This process is also known as “intelligence amplification.”

These lower-level AI solutions are simply designed to make users more efficient in their day-to-day operations, which indirectly benefit policyholders.

On the other hand, higher-level investment in AI involves technologies that play a more active role in decision-making that can directly impact policyholders.

Common AI solutions that require higher-level investment are considered “human-on-the-loop.” In these AI models, the software makes most of the decisions and human users ideally only interfere with workflows when they disagree with a decision or if the AI has failed.  

In the property insurance world, leveraging AI to a higher degree directly impacts a policyholder’s pricing, coverage, and rating. Therefore, using AI to such an extent requires programmers to teach AI models to “think” with unbiased, comprehensive sets of data. 

Property Data Is the Key to Success

AI is only as good as the data it is trained on, which is why it is important to use complete, accurate data to program this real estate technology. It’s the only way AI will make fair, legal decisions. 

Nevertheless, the greater the investment, the greater potential there is for reward. With higher levels of AI adoption, insurance companies and restoration contractors can expand their opportunities to focus on the lives beyond the buildings. 

Regardless of how your organization is looking to approach AI, CoreLogic has you covered. We recognize that taking incremental steps toward adopting AI is valuable, that is why CoreLogic solutions contain both lower and higher degrees of AI to allow organizations to have a wide spectrum of innovative options for their digital strategies. Learn more about our AI-driven solutions today.

The CoreLogic statements and information in this blog post may not be reproduced or used in any form without express written permission. While all the CoreLogic statements and information are believed to be accurate, CoreLogic makes no representation or warranty as to the completeness or accuracy of the statements and information and assumes no responsibility whatsoever for the information and statements or any reliance thereon. CoreLogic® and Marshall & Swift® are the registered trademarks of CoreLogic, Inc. and/or its subsidiaries.

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