Use Case · Claims analysts, actuarial teams, underwriting leaders
Best Power BI Visuals for an Insurance Claims Dashboard
The best Power BI visuals for insurance claims — severity distributions, pipeline Sankeys, catastrophe event heatmaps, reserve waterfalls.
Insurance claims dashboards live at the meeting of actuarial data (severity, frequency, reserves, IBNR) and operational data (cycle time, adjuster workload, subrogation recovery). The analytical demands are distributional (severity tails) and flow-based (claim lifecycle from notification to close) — both weak points of native Power BI visuals.
VizForge generates claims-appropriate visuals: violin plots for severity distributions, Sankey for claim-status flow, heatmaps for event × line-of-business matrices, waterfall for reserve development. Below is the cut list.
Recommended visuals
Typical DAX measures
Loss Ratio
Loss Ratio =
DIVIDE(
SUM( Claims[Incurred] ),
SUM( Premium[Earned] )
)Cycle Time (days, report to close)
Cycle Time =
AVERAGEX(
FILTER( Claims, Claims[Close Date] <> BLANK() ),
DATEDIFF( Claims[Report Date], Claims[Close Date], DAY )
)Claim Severity (mean, median, P99)
Severity Mean = AVERAGE( Claims[Incurred] )
Severity Median = MEDIAN( Claims[Incurred] )
Severity P99 = PERCENTILE.EXC( Claims[Incurred], 0.99 )Example VizForge prompts
Example VizForge prompt
Violin plot of claim severity by line of business (auto, home, liability, workers comp). Log-scale x-axis. Box plot overlay with median and P95.
Example VizForge prompt
Sankey diagram of claim flow over the quarter: reported → assigned → investigating → paid / denied / subrogated / pending. Thickness by claim count.
Example VizForge prompt
Waterfall of reserve development for accident year 2024: initial reserves → 3 quarterly adjustments → case payments → current ultimate estimate. Green for releases, red for strengthenings.
Free plan: 3 visuals per month. No credit card required.
FAQ
Can the visuals show reserve development triangles?
Yes — prompt for 'loss development triangle heatmap, rows = accident year, columns = development year, cells = cumulative paid or incurred'.
How do I handle catastrophe events that skew the data?
Use a slicer to toggle 'include cat events' vs. 'exclude cat events'. Or generate two dashboard pages — one with cats, one without. VizForge visuals respect slicers.
Can the Sankey respect confidentiality requirements?
Claim-level data is aggregated by status; no individual claim details are rendered. For adjuster-level workload views, apply Power BI RLS.
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