Climate-related issues dominated The Global Risk Report released by the 2020 World Economic Forum. It highlighted that climate change is still a threat globally for humans and businesses. At the same time, the pandemic may have taken all the attention in the last few years. But the devastating effects of climate change remain.
Traditionally insurers' concerns have centered around individual catastrophic events. Now other issues need to be taken into consideration. The interactions between human systems and the global climate have added fuel to the fire. Predictive analytics risk management is the next go-to solution to alleviate climate-related risks.
Future Climate Change Implications For Insurers
It is second nature for insurers to use annual policy cycles to understand evolving risks. This information helps organizations rearrange and reprice their portfolios. This practice allows insurers to avoid exposure in the long term to significant climate events. However, this old system is no longer practical due to global climate change.
Out With The Old And In With The New
This heavy reliance on historical data to calculate future risks could be the downfall for insurers. There is now a realization that traditional models and past loss experiences are no longer reliable. The transition to move to more innovative solutions is more critical than ever.
How To Use Predictive Analytics as a Risk Manager
There are so many types of analytics, but predictive analytics is by far one of the most exciting ones for risk management. Its simplest form uses data analytics to make future predictions based on the data. The whole predictive analytics process combines analysis, statistics, and machine learning techniques.
Predictive analytics can help you identify behaviors and trends by examining patterns in the data. It’s a bit like having a personal risk genie in a bottle. The information predictive analytics gives you is cutting edge. It can help you make better risk decisions throughout the organization, ultimately saving you money.
Using Data To Create Predictive Models
As a risk manager, you can use predictive analytics to create predictive models that forecast future events. Predictive modeling can predict an outcome for a future state or time. There is lots of flexibility using modeling. You can change the model’s output, depending on your data input and what information you request from it.
When you set up your modeling, it is essential to understand what you want to achieve. You can ask yourself these questions to set it up correctly. The answers to these questions will help you see the value that predictive analytics gives more to your business.
- What are you trying to model?
- What are the main questions you would like answered?
- What events or outcomes do you want to predict?
You can refine the process by developing predictivity using a training data set. This process allows you to test and validate it to determine its accuracy. Ventiv’s detailed white paper, Brave New World, explains how analytics can help risk managers gain and retain clients in the insurance industry.
Leveraging Real-Time Date to Anticipate Risk
Your ability to anticipate risk is crucial in risk management. Using predictive models gives you access to real-time data and improves your risk management strategy. Your risk management becomes far more proactive. Anything you can do to counter the impact of climate change will make a notable difference in your business. You can also achieve many strategic objectives when you use these types of analytics. Here is a list of a few of them, so you can see how powerful predictive analytics can be for your business:
- Gain a competitive advantage over your competitors by being informed of their business moves concerning global climate change.
- Improved marketing and sales tactics can help to reduce costs and increase sales. There are also more opportunities to retain and gain customers.
- Level up your business intelligence, as predictive analytics gives conclusive, actionable information.
It can also positively affect how you interact with your customers. The real-time data that feeds machine learning systems can adjust the algorithms used to make business decisions. For example, depending on the information given, you know what news items to show on your website or which products to recommend to customers.
Predictive analytics can also help identify insurance claims that might unexpectedly become high-cost losses. You can review previous claims for similar issues when you use analytical tools. You can also send alerts to claim specialists. This advance notice helps them reduce their potential losses.
The Advantages Of Predictive Analytics Risk Management
With the devastating impact of climate change, more and more insurance companies turn to these specialized analytics to help their business. This article by Ventiv goes into more detail on how predictive analytics is helping to achieve better outcomes in insurance claims.
Solving Complex Problems With Geospatial Analytics
Geospatial analytics is another critical technology, due to its ability to help solve complex problems. It is a crossover between geography and mapping. It is ideal for industries that want to monitor global climate change. Geospatial data is related to events, features, or objects on or near the surface of the earth.
You can use geospatial analytics to anticipate and prepare for changes due to spatial conditions or location-based events. Using this technology, you can access geospatial imagery for disaster response management and examine climate conditions. Both are crucial areas for the insurance industry.
Predictive Analytics Risk Management Is The Future
Now more than ever, action needs to be taken to counter potential disasters. For risk managers, the pressure is on. Predictive analytics is vital for risk management to handle the ever-changing environment. Coupled with geospatial capabilities you can predict and act fast before any major climate event.
Contact Ventiv today and find out how you can release your risk genie. Get ready to access better risk data to protect your business.
