Insurance
22 columns
200 rows
8 formats

Finance Insurance Claim Features

This dataset provides a comprehensive view of insurance claim records, including financial details, claimant demographics, policy information, and process metrics. It is ideal for insurtech applications such as fraud detection, claims modeling, and operational efficiency analysis, supporting advanced analytics and machine learning workflows.

last updated 20 Aug 2025
by GoMask

The brief that made it

Fraud detection and risk modeling

Sample rows

preview · 8 of 200 rows · all 22 columns

claim_idstring	claim_typestring	num_documents_submittedinteger	fraud_flagboolean	claimant_countrystring	policy_idstring	claimant_idstring	claim_datedate	incident_datedate	claim_statusstring	claim_amountfloat	approved_amountfloat	deductible_amountfloat	payout_datedate	adjuster_idstring	processing_time_daysinteger	claimant_ageinteger	claimant_genderstring	policy_typestring	policy_start_datedate	policy_end_datedate	incident_descriptionstring
C-100001	auto	3	false	United States	P-AUTO-001	CLM-00001	2023-02-14	2023-02-13	approved	8500.75	7900	600.75	2023-02-22	ADJ-101	8	29	male	comprehensive-auto	2022-05-01	2024-05-01	Rear-ended at traffic signal resulting in bumper and trunk damage.
C-100002	health	2	false	Canada	P-HLTH-144	CLM-00002	2023-07-09	2023-07-07	under_review	3200	blank	0	blank	ADJ-102	blank	34	female	medical-indemnity	2022-06-15	2024-06-15	Hospital admission due to acute appendicitis and surgical intervention.
C-100003	property	8	false	United Kingdom	P-PROP-789	CLM-00003	2022-10-28	2022-10-25	closed	125000	98000	1500	2022-11-20	ADJ-103	23	56	male	full-cover-property	2021-11-01	2023-11-01	Fire damage to kitchen and adjacent rooms due to electrical fault.
C-100004	travel	2	false	Australia	P-TRAV-003	CLM-00004	2023-04-20	2023-04-18	approved	1800	1700	100	2023-04-25	ADJ-104	5	42	female	travel-basic	2023-03-01	2023-09-01	Lost luggage during connecting flight at international airport.
C-100005	life	5	false	Germany	P-LIFE-021	CLM-00005	2022-12-02	2022-11-30	approved	750000	750000	0	2022-12-11	ADJ-105	9	68	male	term-life	2016-01-15	2026-01-15	Policyholder deceased due to cardiac arrest at home.
C-100006	property	14	true	Nigeria	P-PROP-656	CLM-00006	2023-08-17	2023-08-15	fraud_suspected	22000	0	500	blank	ADJ-106	blank	48	female	nano-property	2022-09-01	2024-09-01	Flood damage claimed in non-flood zone, inconsistent paperwork provided.
C-100007	auto	2	false	Mexico	P-AUTO-002	CLM-00007	2023-05-04	2023-05-02	approved	3500	3200	300	2023-05-10	ADJ-107	6	27	male	third-party-auto	2021-10-01	2023-10-01	Single vehicle collision with roadside barrier, minor injuries reported.
C-100008	health	4	false	United Kingdom	P-HLTH-155	CLM-00008	2022-11-19	2022-11-17	approved	12000	11700	300	2022-11-27	ADJ-108	8	23	female	premium-health	2022-01-01	2024-01-01	Emergency surgery for accidental bone fracture sustained during soccer game.
C-100009	travel	1	false	India	P-TRAV-141	CLM-00009	2023-06-12	2023-06-08	submitted	850	blank	100	blank	blank	blank	36	other	custom-travel	2023-05-15	2023-11-15	Flight delayed, missed connecting train, requesting reimbursement for tickets.
C-100010	life	11	false	South Africa	P-LIFE-059	CLM-00010	2023-01-20	2023-01-19	closed	25000000	20000000	0	2023-02-11	ADJ-109	22	92	female	whole-life-premium	2000-01-01	2025-01-01	Policyholder deceased, documentation provided for beneficiary payout.
C-100011	other	1	false	Singapore	P-OTHR-321	CLM-00011	2023-03-27	2023-03-26	submitted	400	blank	0	blank	blank	blank	1	unknown	pet-insurance	2022-11-01	2023-11-01	Pet accident insurance claim for veterinary treatment.
C-100012	auto	5	false	Brazil	P-AUTO-005	CLM-00012	2023-09-03	2023-09-02	closed	14500	13500	1000	2023-09-16	ADJ-110	13	45	female	comprehensive-auto	2022-02-01	2024-02-01	Multi-car collision on highway, moderate vehicle damage.
C-100013	health	1	false	United States	P-HLTH-162	CLM-00013	2023-05-10	2023-05-08	submitted	600	blank	0	blank	blank	blank	24	female	basic-health	2022-04-01	2024-04-01	Prescription medication reimbursement following injury.
C-100014	property	2	false	France	P-PROP-854	CLM-00014	2022-12-17	2022-12-15	rejected	1500	0	1600	blank	blank	blank	38	male	property-essential	2022-01-01	2023-12-31	Minor water damage reported, deductible exceeds claim amount.
C-100015	auto	4	false	Japan	P-AUTO-006	CLM-00015	2023-03-09	2023-03-08	under_review	7800	blank	950	blank	ADJ-111	blank	31	male	third-party-auto	2021-09-01	2023-09-01	Hit-and-run incident at night, police report attached.
C-100016	other	0	false	Greenland	P-OTHR-322	CLM-00016	2023-07-01	2023-06-30	rejected	0	0	0	blank	blank	blank	44	unknown	nano-policy	2022-03-01	2024-03-01	Claim submitted with no supporting documentation.
C-100017	property	7	false	Spain	P-PROP-855	CLM-00017	2023-03-23	2023-03-21	approved	18500	17000	1500	2023-04-02	ADJ-112	10	52	female	property-premium	2022-01-01	2023-12-31	Burglary with forced entry, valuables and electronics stolen.
C-100018	auto	3	false	United Arab Emirates	P-AUTO-007	CLM-00018	2023-08-01	2023-07-31	closed	9400	9100	300	2023-08-11	ADJ-113	10	26	male	comprehensive-auto	2022-03-01	2024-03-01	Car sideswiped in parking lot, paint and glass repair required.
C-100019	health	3	false	Sweden	P-HLTH-188	CLM-00019	2022-08-29	2022-08-27	closed	5300	5000	300	2022-09-06	ADJ-114	8	21	female	medical-indemnity	2021-05-01	2023-05-01	Emergency room treatment for allergic reaction.
C-100020	travel	2	false	Singapore	P-TRAV-179	CLM-00020	2023-03-13	2023-03-10	under_review	420	blank	60	blank	blank	blank	37	other	travel-basic	2022-01-01	2023-12-31	Medical expenses incurred during trip, receipts submitted.

What the 200 rows show

from the 200-row sample

Property (claim type) stands out: mean num_documents_submitted is 8.1, against 3.4 for the rest.

5%fraud_flag = true
3median num_documents_submitted
4claimant genders
6claim statuses
41policy types
3,700median claim_amount

Mean num_documents_submitted by claim_type200 rows

num_documents_submitted200 rows, in bands of 2

Median 3, from 0 to 18.

claimant_country200 rows · top 10 of 18 values

United States24
United Kingdom20
Canada14
Australia14
Nigeria13
France13
Brazil12
Spain12
Sweden11
Germany10

22 columns by typefrom the column list below

string 10
integer 3
float 3
date 5
boolean 1

Columns

22 columns in four groups

blueprint · 22 columns
column	type	description	example
Text 10 columns
`claim_id`	string	Unique identifier for the insurance claimunique	C-100001
`policy_id`	string	Unique identifier for the insurance policy associated with the claim	P-AUTO-001
`claimant_id`	string	Unique identifier for the claimant (person or entity submitting the claim)	CLM-00001
`claim_type`	string	Type of insurance claim (e.g., auto, property, health, life)6 values	auto
`claim_status`	string	Current status of the claim6 values	approved
`adjuster_id`	string	Unique identifier for the claim adjuster assignedoptional	ADJ-101
`incident_description`	string	Detailed description of the incident leading to the claimoptional	Rear-ended at traffic sig…
`claimant_gender`	string	Gender of the claimantmale · female · other · unknown · optional	male
`claimant_country`	string	Country of residence of the claimantoptional	United States
`policy_type`	string	Type of insurance policy (e.g., comprehensive, third-party, term-life)optional	comprehensive-auto
Numbers 6 columns
`claim_amount`	float	Total amount claimed by the claimant0 or more	8500.75
`approved_amount`	float	Amount approved by the insurer for payout0 or more · optional	7900
`deductible_amount`	float	Deductible amount applicable to the claim0 or more · optional	600.75
`num_documents_submitted`	integer	Number of supporting documents submitted with the claim0 or more · optional	3
`processing_time_days`	integer	Number of days taken to process the claim from submission to closure0 or more · optional	8
`claimant_age`	integer	Age of the claimant at the time of claim submission0 to 120 · optional	29
Dates and times 5 columns
`claim_date`	date	Date the claim was submitted	2023-02-14
`incident_date`	date	Date the incident occurred	2023-02-13
`payout_date`	date	Date the claim payout was madeoptional	2023-02-22
`policy_start_date`	date	Start date of the insurance policyoptional	2022-05-01
`policy_end_date`	date	End date of the insurance policyoptional	2024-05-01
True or false 1 column
`fraud_flag`	boolean	Indicates if the claim is flagged for potential fraud	false

Use it for

An insurance dashboard
The fraud_flag rate, num_documents_submitted by claim_type and a breakdown of claimant_country. Excel, Power BI or Tableau.
Why do the 47 property rows have a mean num_documents_submitted of 8.1?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Claims200
C-1000013auto
C-10000614property
C-10003316property
A software demo
Believable claims with policy_id, claimant_id and claim_date to fill a screen in front of a buyer.

This dataset200 rows22 columns

Yours1,000 rows22 columnsclaimant_country: UK only

blueprint · finance-insurance-claim-features

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 22 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.

Rules it was built with

Include claim type and amount
Segment by approval status
Track time to resolution
Flag disputed claims

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

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: finance-insurance-claim-features

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

An insurance dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Insurance

What should your data show?