Today, agents are under more pressure than ever to make profitable risk submissions to underwriters, despite unpredictable weather patterns making property proposals more difficult to predict.
2022 was a challenging year for the property-casualty sector. In total, 18 weather disasters each caused more than $1 billion in damage, making it difficult for insurers to turn a profit. Meanwhile, insurance agents are also struggling because the absence of reliable risk trends is hiding the true extent of risk.
Data has always been an essential part of every step of the insurance process—from agents making submissions to underwriters pricing policies. However, climate change and the fast-changing nature of natural catastrophes mean that decisions based on historical data may no longer reflect the full risk.
Today, agents are under more pressure than ever to make profitable risk submissions to underwriters, despite unpredictable weather patterns making property proposals more difficult to predict. The effects of climate change are systemic and their repercussions are likely to stress local economies and cause market failures that affect both customers and insurers.
We have already seen the Florida insurance market faltering under the pressures of an ever-changing risk landscape as bets are hedged against who and where is next to fall. With climate risks projected to escalate and the industry's long-term viability at stake, agents need to find new ways to assess risk.
One way agents are gathering rich, up-to-date property data is by using artificial intelligence to extract insights about the risk associated with their customers' properties. Here are three of the benefits:
1) No time wasted. Collecting data for property assessments can be a tedious and time-consuming process that involves an agent traveling to the property. By utilizing aerial imagery, agents can view properties from the comfort of their own office or home. This approach allows AI to extract key data points from the visual imagery which can then be analyzed to provide valuable insights.
For example, the roof condition of a property is a critical underwriting attribute. Using AI and aerial visuals, the shape, gradient, and material of a roof can be determined. Information about the age of the roof and its overall surface area can also be quickly extracted, building an accurate and complete picture of the roof's state and structural properties.
A roof condition needs to be measured with precision for agents to pose valid risk submissions. Agents who know how to apply this data in their daily practices will save their underwriter's time, as well as their own. This data can be seamlessly integrated into an insurer's workflow with the use of application programming interfaces (APIs). This integration allows rapid and efficient incorporation of property assessment data, enabling insurers to make better-informed decisions.
2) Provide a better service. It is essential that agents can clearly demonstrate their motivations and deciding factors to underwriters when filing their submissions.
By being aware of the specific risk conditions of each property, agents can understand how policies affect the policyholder, underwriter and carrier. Agents can gain customer trust, demonstrating their knowledge of the homeowner's property with confidence before the initial consultation.
To assist with this, large bulk data platforms which collate data gathered by advanced technology allow agents to be specific with their property hunting. For example, search engines can differentiate properties by attributes, filtering hundreds of thousands of properties so agents can drill into specific residences.
This collaboration between AI, aerial visuals and databases gives agents access to in-depth property overviews and customer insights.
3) Growing commission. Using detailed data collection, agents can work towards increasing their commission by better matching the right premium to the customer. This approach enables underwriters to offer them an accurate and competitive price, providing a full analysis of risky and complex properties and simultaneously minimizing the likelihood of a bad risk submission.
Extremely high-risk properties, such as those with tarp coverings or unsafe roof structures that would result in unattainably expensive premiums can be avoided, while properties that present more profitable insurance factors can be targeted. This allows agents to optimize their efforts, grow their commission and ensure that customers receive the best possible coverage at a fair price.
An Agent's Biggest Competition Is Climate Change
As the insurance industry becomes more competitive, many agents are starting to recognize the importance of up-to-date information about clients and detailed property intelligence. In 2023, agents actively looking for high-quality data will gain a competitive edge as the resources provided by some carriers are proving to be ineffective in the face of the changing climate and resulting catastrophes.
Utilizing this quality data, agents will be able to provide better offers, choose profitable properties to put forward to underwriters, and gain access to a clear profile of commercial properties. Climate change makes it imperative that agents have access to up-to-date, high-quality data to support their risk management strategies, policy renewals, and claims tracking.
Izik Lavy is a p-c insurance expert and CEO at GeoX.