The insurance industry is changing with the use of big data and technology. This started in the consumer market and is slowly becoming a reality in commercial markets, as those same consumers seek the agility and flexibility for their business operations that they get in their private lives.

But how about flipping this?

How can commercial fleet operators better use their own fleet data to show their risk profile situation and improvement to their insurers? And by doing so, combat the rise in auto premiums and secure better insurance rates?

Read on to discover how can you use your fleet data to prove you’re a lower risk.

The Problem with Traditional Insurance Methods

While change is happening, the traditional insurance method still dominates commercial fleet insurance. That is, your fleet’s insurance is calculated on the basis of what sector you are in, how big your fleet is, your prior claims history, your operating times and where you operate.

While this has been the accepted way of doing things, it isn’t necessarily a good indicator of your specific risk, considering it’s essentially based on years of averages from loads of commercial fleets – and not your fleet’s specific situation.

You may also still be paying for issues that happened three years ago, which you’ve addressed and successfully mitigated across your driver population.

Using Fleet Data to Prove You’re a Lower Insurance Risk

How can you change the model and use your fleet data to have a better discussion with your insurer about your premiums?

Your Fleet’s Risk Profile

Using the data from your fleet risk management system, you can show how your risk profile has changed (normalized for changes in mileage, driver and vehicle numbers) over time.

With this, you can detail how your five biggest or most common risk factors have changed. Plus, you can highlight what steps you’ve taken to achieve this.

This can be taken down to the driver level to demonstrate both how much data you have, but also how you can use it to target problem areas at a very precise level.

Driver Engagement

You can use driver engagement as a metric to demonstrate how you’ve supported your analysis and insight with action.

For example, with your fleet risk management data, you can show how many touch points – such as management interventions or training sessions – you have had with your drivers to help them become more aware of their risk factors.

With such data, you can then show how drivers, both new and established, have improved over a three-month period due to this management and training investment.

Claims

FNOL (first notification of loss) is a key driver in claims cost management. The faster an incident is reported, the faster management resources can be deployed and the better the resulting control of related costs. Over time, this improved claim cost management will lead to better premiums.

However, this goes further. The more information that you can provide to your insurer for individual incident claims, the better they can work to reduce claim severity from their point of view. Savings for your insurer, derived from your actions, should then benefit you.

Of course, doing this a few times is not enough. To have an impact, the data needs to be of good quality and in the quantity of 70%+ of your claims supported by it to be of value in demonstrating your control of the situations to your insurer.

Challenge Your Insurer

This approach might be foreign to your insurer or broker, why not challenge them? Turn the discussion around by using your fleet data to back up your situation and answer your case for better insurance rates.

Ultimately, you’ve got nothing to lose by doing it. Also, you’ll be demonstrating additional value for the time and energy you’ve invested into fleet risk management and the collection and use of the associated data.

To learn more about how companies can mitigate driver risk to effectively decrease their commercial auto premiums, download our white paper, How Continuous Monitoring Transforms Driver Risk Management.