u/Amy165

Hi! I worked with a frequency vs severity scatter plot in Power BI, using a categorical field in the legend to create multiple groups.

The issue is that Power BI assigns a different color to each category, and since I have quite a few groups, the visual becomes quite noisy and hard to interpret.

If I want to simplify it (for example, keep everything in the same color or just highlight a few key segments), it seems I have to change the colors one by one manually, which is not very practical.

Is there a better way to handle this?

Also, I’m not sure if I’m mixing things up with Tableau, but I remember using something like a “Details” field to separate points without affecting the colors. Is there an equivalent in Power BI, or am I misremembering?

I’ve been working on a Power BI project analyzing a vehicle insurance portfolio, mainly focusing on pricing and performance.

I picked a dataset from Kaggle because I wanted to explore something related to insurance, but it was more challenging than expected. Some fields were not clearly defined, so part of the work was figuring out what the data actually represented. I decided to continue anyway.

For the pricing analysis, I normalized everything per year (using exposure) to make comparisons more meaningful. It became quite clear that some segments were underpriced, especially in earlier years.

I also explored frequency vs severity, and noticed that the most underpriced segments tend to deviate from the general pattern, which made them stand out even more from a risk perspective.

I also tried some basic risk prediction models, and for the first time used Python scripts inside Power BI to improve the visualization of the confusion matrix.

First time sharing something like this here and I’d really appreciate any feedback 🙂

 - How do you usually approach pricing or risk-related analysis in Power BI? 

- Any suggestions on how to better structure these kinds of visuals?