With the Philippines dealing with an ever-increasing number of severe weather occurrences such as tornadoes, hail, and high winds, it’s more crucial than ever for insurers to be able to manage their losses. When people experience substantial damage to their houses, the first thing they do is make a claim with their property insurer and try to repair their homes as soon as possible. These are make-or-break occasions for carriers to engage with their customers in a positive way.

Severe Storms

Fortunately, insurers’ primary care can meet the needs of their clients while also limiting claim costs during severe convective storms thanks to modern technology, enhanced quality control, and better client relationship management. While consumer satisfaction with the property and casualty insurance process is at an all-time high, some policyholders are nevertheless unhappy with premium hikes, the perception of extra effort, and unnecessary claims delays.

The key to ensuring client satisfaction while decreasing losses is to optimize the time and resources required in the claims process. Here are some examples of areas where this can be accomplished:

  1. By maximizing the claims resource deployment during severe storms, insurers can reduce costs by streamlining the first notification of loss process. During natural disasters, insurers are frequently overburdened, and there aren’t enough adjusters to reach all policyholders in a timely manner. 

There is an optimal approach to deploying claims resources because certain policyholders will be more adversely harmed by storms than others. Traditional procedures (sending an adjuster in person) can be employed for individuals with the most severe effects, while those with less severe impacts can be offered the choice to file their claim digitally. This lowers the cost of handling while also improving response time and customer satisfaction.

  1. Technology that validates claims quickly; another aspect of this puzzle that can be improved with modern technologies is claim validation. By combining geographic information systems (GIS) with claims, an adjuster can quickly confirm a claim or determine whether further investigation is required. Weather verification technology can assist in preventing fraud and expediting the adjusting process. 

Claims processing becomes much easier when hail data is granular enough to establish what size hail fell at what time on what precise parcel(s).

  1. Using a triage system to improve scoping another strategy to cut expenses is to limit the amount of time and resources needed for scoping. For a relatively easy claim, an insurer’s most experienced adjuster may not be the most efficient option. This can be accomplished by employing a triage method that takes into account the kind of loss, severity, location, insured type, and field adjuster availability. 

The carrier can then determine whether to dispatch a staff adjuster, utilize a third-party solution, combine a desk-adjustment solution with a third-party solution, or ask the policyholder to use self-service scoping technology.

  1. Increasing the precision of scoping and estimations It’s also possible to keep claim repair costs under control. This is accomplished by increasing the accuracy of the scope and costs used in the repair or replacement estimate. 

Exterior and interior measurements may be obtained using technology, and conformity can be maintained throughout all claim estimates. To ease negotiation and eventual settlement, local material, labor, and equipment costs might be examined and broken down by components. Of course, this information should be backed up by industry experts, and insurable interest making it dependable and long-term if price spikes occur during major storms.



Although you can’t control the weather, you can limit your property exposure and loss adjustment costs by leveraging existing data and analytics. You may simply measure your risk exposure in a certain region by using different techniques such as GIS (Geographical Information System) and Triage System. 

Property rules can therefore be used to restrict new policies from being developed in areas where you believe you’d be overexposed in the event of a disaster.

You may use location-specific weather analytics to cut loss adjustment costs and speed up claims processing. You can access near-real-time high-resolution information on dangers like hail and rain. 

For example, you may find out the quantity of the hail, the storm’s exact trajectory, and which of your policies were within the track right after a hailstorm. With this data, you can forecast the number of claims you’ll get, optimize your adjuster deployment, and spot potentially fraudulent hail claims.

The uncertainty of severe weather affects all property insurers. You’ll be better able to understand and reduce the risk if you use GIS technology and weather analytics. You’ll be able to deliver better claims-handling service to your consumers while lowering your processing costs.

In the age of global climate change, different types of insurance is essentially a two-sided bet. In the first instance, the gamble involves insurers and reinsurers making a series of (partially) informed wagers on the frequency, intensity, and consequences of natural disaster events, and financial losses, a task that is laden with complexity and puzzle in and of itself. 

In the second case, global climate change has the potential to throw our existing knowledge of the causes and effects of extreme weather occurrences into disarray. If the outcome of this element of the dual gamble is adverse for insurers, it may signify the need for future significant changes in how these risks are perceived, assessed, and handled.

The global climate system is well acknowledged to be standard chaotic, which effectively eliminates the ability of accurate short- to medium-term extreme weather forecasts, as well as precision estimation of critical weather-related components (e.g., humidity, rain, atmospheric and sea-surface temperatures, and wind activity). The chaotic micro-scale dynamics of climate produce “emergent self-similar” large-patterns with “bounded uncertainty” about the climate variables under consideration.

Though efforts to arrive at reliable predictions of long-term climate-related events at very small scales such as rainfall, pressure, and temperature continue to improve, efforts to arrive at reliable predictions of long-term climate-related events at very small scales such as rainfall, pressure, and temperature are still characterized by high levels of “nonreducible” uncertainty, owing to the chaotic nature of such variables. For more info about purchasing insurance visit our site one of the insurance agencies located in Las Piñas City. Purchasing our insurance premium will almost certainly provide you with greater advantages in the unlikely event of an unforeseen event.