Commercial Lines Premium by Industry Segment
This dataset provides detailed commercial insurance premium and exposure data broken down by SIC/NAICS industry codes, economic sectors, and portfolios over time. It enables in-depth analysis of business mix, industry concentration, and portfolio diversification, supporting risk management and strategic decision-making for insurers and analysts.
Sample rows
preview · 8 of 800 rows · all 13 columns| record_idstring | written_premiumfloat | sic_codestring | naics_codestring | industry_namestring | economic_sectorstring | policy_yearinteger | exposurefloat | business_mix_percentagefloat | industry_concentration_percentagefloat | portfolio_idstring | data_sourcestring | last_updateddatetime |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| REC00000001 | 5200000.54 | 2752 | blank | Commercial Printing Services | Manufacturing | 2017 | 84000000.23 | 8.23 | 7.95 | PORT001 | MarketScan USA | 2017-06-15T10:34:05 |
| REC00000002 | 230000 | blank | 541612 | Human Resources Consulting | Services | 2020 | 1500000 | 1.41 | 1.52 | PORT002 | GlobalData Direct | 2020-09-21T14:08:20 |
| REC00000003 | 740000.45 | 5999 | blank | Miscellaneous Retail Stores | Retail | 2019 | 12100000 | 2.21 | 2.18 | PORT001 | InsureNet | 2019-02-12T11:19:53 |
| REC00000004 | 1250000 | blank | 212112 | Bituminous Coal Underground Mining | Mining | 2016 | 8000000 | 2.67 | 2.44 | PORT004 | IndustryRisk | 2016-12-08T09:05:15 |
| REC00000005 | 320000.3 | 8211 | blank | Elementary and Secondary Schools | Government | 2021 | 8000000 | 0.79 | 1.01 | PORT003 | PolicyDataHub | 2021-03-27T16:46:32 |
| REC00000006 | 1800000.7 | blank | 722513 | Limited-Service Restaurants | Hospitality | 2018 | 25000000 | 4.15 | 3.97 | PORT004 | MarketScan USA | 2018-07-18T17:42:50 |
| REC00000007 | 2100000.11 | 1521 | blank | General Contractors - Residential Buildings | Construction | 2022 | 24000000 | 5.27 | 4.91 | PORT002 | GlobalData Direct | 2022-01-11T13:12:37 |
| REC00000008 | 50000 | blank | 111120 | Cotton Farming | Agriculture | 2015 | 650000 | 0.11 | 0.19 | PORT005 | AgriInsure | 2015-10-05T08:25:29 |
| REC00000009 | 6500000 | 4922 | blank | Natural Gas Transmission | Utilities | 2018 | 50000000 | 8.02 | 7.81 | PORT003 | EnergyRisk | 2018-05-02T15:57:04 |
| REC00000010 | 7100000 | blank | 524126 | Direct Property and Casualty Insurance Carriers | Finance | 2019 | 90000000 | 9.18 | 8.97 | PORT001 | InsureNet | 2019-06-23T10:13:59 |
| REC00000011 | 2800000 | 4512 | blank | Air Transportation Scheduled | Transportation | 2020 | 32000000 | 4.24 | 3.87 | PORT002 | GlobalData Direct | 2020-07-19T18:34:12 |
| REC00000012 | 1450000 | blank | 511210 | Software Publishers | Information | 2017 | 21000000 | 3.01 | 2.88 | PORT005 | TechInsure | 2017-04-03T12:28:47 |
| REC00000013 | 8700000 | 6011 | blank | Federal Reserve Banks | Finance | 2021 | 100000000 | 11.37 | 10.89 | PORT003 | PolicyDataHub | 2021-11-02T11:22:15 |
| REC00000014 | 3500000 | blank | 334413 | Semiconductor and Related Device Manufacturing | Manufacturing | 2022 | 50000000 | 4.82 | 5.11 | PORT004 | MarketScan USA | 2022-03-11T16:59:05 |
| REC00000015 | 195000 | 8732 | blank | Commercial Physical Research | Professional Services | 2016 | 1800000 | 0.63 | 0.81 | PORT005 | TechInsure | 2016-08-13T08:47:20 |
| REC00000016 | 1100000 | blank | 621111 | Offices of Physicians | Health Care | 2018 | 12000000 | 2.49 | 2.76 | PORT003 | HealthDataSource | 2018-10-27T09:12:33 |
| REC00000017 | 1300000 | 5411 | blank | Grocery Stores | Retail | 2019 | 18000000 | 3.12 | 3.25 | PORT001 | InsureNet | 2019-04-17T18:28:23 |
| REC00000018 | 1600000 | blank | 484121 | General Freight Trucking, Long-Distance | Transportation | 2017 | 21000000 | 2.74 | 2.85 | PORT004 | MarketScan USA | 2017-08-21T12:10:49 |
| REC00000019 | 950000 | 5141 | blank | Wholesale Groceries | Wholesale | 2020 | 16000000 | 2.05 | 2.13 | PORT002 | GlobalData Direct | 2020-02-27T15:33:32 |
| REC00000020 | 600000 | blank | 621210 | Offices of Dentists | Health Care | 2015 | 9000000 | 1.36 | 1.41 | PORT005 | HealthDataSource | 2015-06-22T17:02:51 |
What the 800 rows show
from the 800-row sample- 2,200,000median written_
premium - 49economic sectors
- 144data sources
- 179portfolios
- 52,490,000median exposure
- 3.0median business_
mix_ percentage
Median 2,200,000, from 50,000 to 75,000,000.
- string 7
- integer 1
- float 4
- datetime 1
Columns
13 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 7 columns | |||
record_id | string | Unique identifier for each premium recordunique | REC00000001 |
sic_code | string | Standard Industrial Classification code representing the industry segmentoptional | 2752 |
naics_code | string | North American Industry Classification System code representing the industry segmentoptional | 541612 |
industry_name | string | Descriptive name of the industry segment | Cotton Farming |
economic_sector | string | Economic sector to which the industry belongs (e.g., Manufacturing, Services, Agriculture) | Manufacturing |
portfolio_id | string | Identifier for the insurance portfolio or book of business | PORT001 |
data_source | string | Source system or provider of the premium and exposure dataoptional | MarketScan USA |
| Numbers 5 columns | |||
policy_year | integer | Year for which the premium and exposure data is reported1,900 to 2,100 | 2017 |
written_premium | float | Total written premium amount for the industry segment in the given year (in USD)0 or more | 5200000.54 |
exposure | float | Exposure value for the industry segment (e.g., payroll, sales, units insured)0 or more | 84000000.23 |
business_mix_percentage | float | Percentage of total portfolio premium represented by this industry segment0 to 100 · optional | 8.23 |
industry_concentration_percentage | float | Percentage of total portfolio exposure represented by this industry segment0 to 100 · optional | 7.95 |
| Dates and times 1 column | |||
last_updated | datetime | Timestamp when this record was last updatedoptional | 2017-06-15T10:34:05 |
Use it for
An insurance dashboard
Written_
premium. Excel, Power BI or Tableau. What pattern can you find in 800 rows?
A class exercise
Hand out the rows and one question. Everyone works from the same 800 rows.
- Records800REC000000015200000.54REC00000002230000REC00000003740000.45
A software demo
Believable records with sic_
code, naics_ code and industry_ name to fill a screen in front of a buyer.
blueprint · commercial-lines-premium-by-industry-segment
Behind this dataset
Same schema. As many rows as you need.
These 800 rows came out of a blueprint — 13 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.
- SIC (Standard Industrial Classification) codes
- NAICS (North American Industry Classification System)
- Industry group aggregations
- Premium by industry segment
- Policy count by industry
- Industry concentration limits
- Economic sector diversification
- Cyclical industry exposure
1 credit per row. New accounts start with 25 free credits.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- commercial-lines-premium-by-industry-segment