How to reduce the cost of property claims

By Joseph Artgole - February 21, 2022

Last year saw insured losses from global natural disasters total $130billion in 2021 (Aon). Two of the most expensive disasters were Hurricane Ida and Storm Uri in the United States. As events become more frequent and severe, the cost of claims rises alongside the required capacity of claims teams.

The key to making higher frequency events manageable and less costly is to reduce total claims processing times. Technology is making this possible, delivering the following benefits:

  • Insurer gets visibility of loss before customer and can automate first notification of loss (FNOL)
  • Higher proportion of loss can be resolved through desk adjustments
  • On-site loss adjustment can cover all necessary properties in one site visit
  • Clear data is available to check for fraudulent claims
  • Mitigates exposure to inflation from materials and contractors in high demand

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Graphic 1: simplified stages of the property claims process, from alert to resolution

Knowing when loss occurs

When a catastrophe occurs, property insurers are dependent on the insured for first notification of loss (FNOL). This means that claims are processed on an ad hoc basis. With natural catastrophes affecting the insured at scale, the same process is repeated each time an FNOL is received. This dependency means the insurer cannot address claims at scale, increasing costs.

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Graphic 2: displaced claims process where alerts occur at different times.

Claims teams need to know the severity of loss before the insured so they can initiate the claims process. Controlling the start of the claims process for all affected accounts within a portfolio means loss from the event can be considered in its entirety. Activities that were conducted on an individual claims basis can now be consolidated to save both time and cost.

How do you find out loss severity faster than the insured?

Aerial imagery is now advanced and accessible. It’s also the fastest way of viewing a site post-catastrophe. Independent satellite constellations, plane photography, and drone imagery offer high resolution images that aren’t locked within an ecosystem.

Today, some claims teams source aerial imagery to run analysis in-house. However, it’s a long and manual task which requires a specialist. The value of this data may therefore not be realised before the insured reports on damage severity.

Artificial intelligence (AI) uses algorithms to determine the severity of loss post-catastrophe. Concirrus’ damage severity algorithms deduce the loss of individual properties post catastrophe in a matter of hours. The difference between a manual and automated method of damage assessment, from days to hours, is a significant time and cost reduction. This allows claims teams to understand loss severity at scale ahead of the insured, shortening the first step of the claims process

 

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Graphic 3: using AI, claims teams can see post-event damage severity for their portfolio, fast. This means they can inform and support customers without delay.

What does this mean for customers?

The benefits of using AI go beyond operations. Claims teams are the customer–facing side of a property insurer and deal with customers when they are most vulnerable. A customers opinion of their provider is influenced by their experience of the recovery process. Ensuring customers remain informed and receive entitled financial aid quickly helps them get their lives back on track.

How do we know automation maintains accuracy?

An experienced head of claims will often want to clarify the accuracy of any system considered for inclusion in their business. Machine Learning (ML), a subset of AI, is often a new variable for claims teams to consider.

Machine learning algorithms can learn continuously. The outcomes of an algorithm depends on the volume and quality of data made available to it. The damage assessment algorithms used in Quest Property have been continuously learning from high quality data for over three years. This makes them mature algorithms. When matched with quality imagery from new events, mature algorithms provide more reliable outcomes for businesses to use in decision making.

The application of a mature algorithm is sustainable because processing outcomes from new catastrophe data also trains the algorithm, meaning outcomes remain relevant.

Hurricane Ida Report (2)

How are these outcomes made simple to understand?

Looking at the image below, you can see the loss severity of different properties post Hurricane Ida. There are four damage ratings depending on the type of loss that has occurred. A claims manager can interpret these results and make clear decisions on desk adjustments or which route would need to be taken by on-site adjusters to review the most critical losses.

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Optimising adjustments

The process of adjustments becomes more economical with detailed insight of all claims. Claims teams can resolve a higher percentage of claims through desk adjustments due to a deeper understanding of loss. On-site adjusters can understand which properties require attention in advance and plan to view all properties in one visit. This leads to a significant administration time and costs savings. The relative impact depends on the claims team’s existing process.

At this point, claims teams also have the detailed insight they need to reference potential fraudulent claims and mitigate harmful acts.

Recovery and resilience

Accelerating claims notification and adjustment ultimately means recovery can begin sooner. Early acquisition of materials and contractors reduces exposure to inflation, reducing the potential cost of claims. The added customer service benefits distinguish one provider from another, providing a competitive advantage for the organisation employing AI based assessments.

Between 2021 and 2040, weather-related catastrophe losses will see an estimated 33-41% increase in global property premiums. The time and cost benefits gained from the deployment of AI based assessments shortens the claims process at scale. This leads to a more resilient business given more frequent and severe events. 76% of top performing insurance organisations are leveraging advanced analytics solutions, will you be one of them?

Contact us for more on how we can help your property insurance business today.

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