Finance
33 columns
200 rows
8 formats

Finance Peer-to-Peer Lending Data

This dataset provides detailed, transaction-level records from a peer-to-peer lending platform, including loan terms, borrower and investor attributes, credit scores, repayment history, and loan performance indicators. It is ideal for credit risk modeling, investor analytics, and financial platform optimization, supporting both operational and research applications in alternative lending.

last updated 20 Aug 2025
by GoMask

The brief that made it

Credit scoring and risk modeling for alternative lending

Sample rows

preview · 8 of 200 rows · all 33 columns

loan_idstring	borrower_employment_statusstring	borrower_ageinteger	default_flagboolean	borrower_address_countrystring	borrower_idstring	investor_idstring	loan_amountfloat	funded_amountfloat	interest_ratefloat	loan_term_monthsinteger	loan_statusstring	application_datedate	funded_datedate	disbursement_datedate	maturity_datedate	borrower_credit_scoreinteger	borrower_incomefloat	borrower_address_streetstring	borrower_address_citystring	borrower_address_statestring	borrower_address_postal_codestring	investor_typestring	investor_address_streetstring	investor_address_citystring	investor_address_statestring	investor_address_postal_codestring	investor_address_countrystring	repayment_schedulestring	total_repaidfloat	last_payment_datedate	late_payments_countinteger	purposestring
LN00001	employed	29	false	USA	BR00001	IV00001	8500.25	8500.25	8.75	36	active	2022-03-22	2022-03-24	2022-03-25	2025-03-25	712	51000	126 Willow Lane	Houston	TX	77002	individual	501 Main St	Dallas	TX	75201	USA	monthly	3200.1	2023-12-15	0	debt_consolidation
LN00002	retired	68	false	Australia	BR00002	IV00002	42000	42000	6.2	84	completed	2016-10-15	2016-10-19	2016-10-20	2023-10-20	812	168000	45 Forest Dr	Melbourne	VIC	3000	institutional	89 Queen St	Sydney	NSW	2000	Australia	quarterly	42000	2023-10-20	0	home_improvement
LN00003	student	20	false	France	BR00003	IV00003	1800	1800	19.8	9	active	2023-05-05	2023-05-08	2023-05-09	2024-02-09	451	8000	2 Rue de Paris	Paris	Ile-de-France	75002	individual	19 Av. des Champs	Paris	Ile-de-France	75008	France	monthly	1200	2024-02-01	1	education
LN00004	employed	58	false	UK	BR00004	IV00004	127500	127500	3.6	96	active	2021-12-01	2021-12-10	2021-12-13	2029-12-13	799	220000	81 King Road	Birmingham	West Midlands	B1 1AA	institutional	100 City Square	London	Greater London	EC1A 1BB	UK	quarterly	37000	2023-12-30	0	home_improvement
LN00005	student	19	false	UK	BR00005	IV00005	950	950	14.7	2	active	2024-01-05	2024-01-08	2024-01-09	2024-03-09	388	2300	23 University Rd	Leeds	West Yorkshire	LS2 9JT	individual	9 Market Street	Liverpool	Merseyside	L1 1AA	UK	lump-sum	475	2024-02-09	0	education
LN00006	employed	37	false	Canada	BR00006	IV00006	30000	30000	9.8	60	active	2021-07-11	2021-07-13	2021-07-15	2026-07-15	689	57000	420 Elm St	Toronto	ON	M5G 2C3	individual	17 Yonge St	Toronto	ON	M5E 1W7	Canada	monthly	16800	2023-12-13	1	debt_consolidation
LN00007	unemployed	25	false	Germany	BR00007	IV00007	700	0	21.4	6	pending	2024-02-01	blank	blank	blank	522	15000	32 Market Ave	Berlin	Berlin	10117	institutional	18 Alexanderplatz	Berlin	Berlin	10178	Germany	monthly	0	blank	0	medical
LN00008	employed	34	false	USA	BR00008	IV00008	15800	15800	7.2	48	active	2022-07-30	2022-08-02	2022-08-04	2026-08-04	738	85000	79 Oakwood St	Chicago	IL	60616	individual	201 Lakeview Dr	Springfield	IL	62701	USA	monthly	7200	2024-01-31	0	business
LN00009	self-employed	42	false	USA	BR00009	IV00009	28000	28000	10.5	60	late	2021-05-14	2021-05-16	2021-05-18	2026-05-18	631	46000	118 Cypress Rd	Miami	FL	33101	individual	33 Palm Ave	Orlando	FL	32801	USA	monthly	12500	2023-11-28	2	business
LN00010	employed	39	false	USA	BR00010	IV00010	35000	35000	7.8	60	active	2021-08-19	2021-08-22	2021-08-23	2026-08-23	749	93000	58 Pine St	Seattle	WA	98101	individual	410 Rainier Ave	Seattle	WA	98104	USA	monthly	17660	2024-01-10	0	debt_consolidation
LN00011	unemployed	24	false	South Africa	BR00011	IV00011	6800	6800	17.5	18	active	2023-04-06	2023-04-07	2023-04-08	2024-10-08	568	22800	101 Market St	Cape Town	Western Cape	8001	institutional	56 Long St	Cape Town	Western Cape	8001	South Africa	monthly	4200	2024-01-24	1	medical
LN00012	retired	75	false	USA	BR00012	IV00012	150000	150000	3.9	120	active	2018-09-09	2018-09-13	2018-09-14	2028-09-14	835	700000	77 Bayview Ave	San Diego	CA	92101	institutional	900 Ocean Blvd	Los Angeles	CA	90001	USA	quarterly	101000	2023-12-31	0	home_improvement
LN00013	self-employed	46	false	China	BR00013	IV00013	51000	51000	8.2	60	active	2020-05-01	2020-05-07	2020-05-10	2025-05-10	701	122000	14 Maple St	Shanghai	Shanghai	200002	institutional	28 Nanjing Rd	Shanghai	Shanghai	200001	China	monthly	36000	2023-12-14	0	business
LN00014	student	18	false	New Zealand	BR00014	IV00014	1200	900	27.9	1	funded	2024-02-10	2024-02-11	blank	blank	390	500	9 Alley Rd	Auckland	Auckland	1010	institutional	29 Queen St	Auckland	Auckland	1010	New Zealand	lump-sum	0	blank	0	education
LN00015	unemployed	21	false	Brazil	BR00015	IV00015	3400	3400	12.4	12	active	2023-03-03	2023-03-04	2023-03-05	2024-03-05	602	21000	55 Beach Rd	Rio	RJ	20000-000	individual	41 Avenida	São Paulo	SP	01000-000	Brazil	monthly	1100	2024-02-20	0	medical
LN00016	retired	80	false	USA	BR00016	IV00016	200000	200000	4.2	120	active	2017-11-18	2017-11-23	2017-11-27	2027-11-27	845	1200000	12 Ocean Dr	San Francisco	CA	94103	institutional	600 Broadway	New York	NY	10001	USA	quarterly	156000	2023-12-31	0	other
LN00017	employed	32	false	New Zealand	BR00017	IV00017	9700	9700	11.9	24	active	2022-10-10	2022-10-12	2022-10-13	2024-10-13	671	48000	82 Hillside Dr	Auckland	Auckland	1010	individual	5 Victoria St	Wellington	Wellington	6011	New Zealand	monthly	3700	2024-01-15	0	debt_consolidation
LN00018	retired	91	false	Canada	BR00018	IV00018	310000	310000	5.4	120	completed	2014-02-12	2014-02-21	2014-02-22	2024-02-22	822	800000	600 Riverside Dr	Vancouver	BC	V6A 2T3	institutional	700 Burrard St	Vancouver	BC	V6C 3L6	Canada	quarterly	310000	2024-02-22	0	other
LN00019	unemployed	22	false	Singapore	BR00019	IV00019	4500	4500	23.6	5	late	2023-11-03	2023-11-07	2023-11-09	2024-04-09	312	7000	41 1st Ave	Singapore	Central	049213	institutional	77 Raffles Place	Singapore	Central	048616	Singapore	monthly	900	2024-02-28	2	medical
LN00020	employed	56	false	Canada	BR00020	IV00020	57500	57500	4.9	84	active	2019-11-01	2019-11-04	2019-11-06	2026-11-06	798	310000	312 Highland Ave	Calgary	AB	T2P 1K9	institutional	800 5th St SW	Calgary	AB	T2P 3T6	Canada	quarterly	38900	2023-12-31	0	home_improvement

What the 200 rows show

from the 200-row sample

Retired (borrower employment status) stands out: mean borrower_age is 72.2, against 30.3 for the rest.

4%default_flag = true
30median borrower_age
2investor types
3repayment schedules
6loan statuses
6purposes

Mean borrower_age by borrower_employment_status200 rows

borrower_age200 rows, in bands of 10

Median 30, from 18 to 91.

borrower_address_country200 rows · top 10 of 21 values

USA53
UK31
Canada27
Australia19
South Africa18
France11
New Zealand7
Brazil6
Germany5
China4

33 columns by typefrom the column list below

string 18
integer 4
float 5
date 5
boolean 1

Columns

33 columns in four groups

blueprint · 33 columns
column	type	description	example
Text 18 columns
`loan_id`	string	Unique identifier for each loan issued on the platformunique	LN00001
`borrower_id`	string	Unique identifier for the borrower requesting the loan	BR00001
`investor_id`	string	Unique identifier for the investor funding the loan	IV00001
`loan_status`	string	Current status of the loan6 values	active
`borrower_employment_status`	string	Employment status of the borroweremployed · self-employed · unemployed · retired · student	employed
`borrower_address_street`	string	Street address of the borroweroptional	126 Willow Lane
`borrower_address_city`	string	City of the borrower's addressoptional	Houston
`borrower_address_state`	string	State or province of the borrower's addressoptional	TX
`borrower_address_postal_code`	string	Postal code of the borrower's addressoptional	77002
`borrower_address_country`	string	Country of the borrower's addressoptional	USA
`investor_type`	string	Type of investor (individual or institutional)individual · institutional	individual
`investor_address_street`	string	Street address of the investoroptional	501 Main St
`investor_address_city`	string	City of the investor's addressoptional	Dallas
`investor_address_state`	string	State or province of the investor's addressoptional	TX
`investor_address_postal_code`	string	Postal code of the investor's addressoptional	75201
`investor_address_country`	string	Country of the investor's addressoptional	USA
`repayment_schedule`	string	Repayment schedule type (monthly, quarterly, etc.)monthly · quarterly · lump-sum	monthly
`purpose`	string	Purpose of the loan (e.g., debt consolidation, home improvement)6 values	debt_consolidation
Numbers 9 columns
`loan_amount`	float	Total principal amount requested for the loan0.01 or more	8500.25
`funded_amount`	float	Amount actually funded by investors for the loan0 or more	8500.25
`interest_rate`	float	Annual interest rate applied to the loan (percentage)0.01 to 100	8.75
`loan_term_months`	integer	Duration of the loan in months1 to 120	36
`borrower_credit_score`	integer	Credit score of the borrower at the time of application300 to 850	712
`borrower_income`	float	Annual income of the borrower in local currency0 or more	51000
`borrower_age`	integer	Age of the borrower at the time of application18 to 100	29
`total_repaid`	float	Total amount repaid by the borrower to date0 or more	3200.1
`late_payments_count`	integer	Number of late payments made by the borrower0 or more	0
Dates and times 5 columns
`application_date`	date	Date when the borrower submitted the loan application	2022-03-22
`funded_date`	date	Date when the loan was fully fundedoptional	2022-03-24
`disbursement_date`	date	Date when the loan funds were disbursed to the borroweroptional	2022-03-25
`maturity_date`	date	Scheduled date for loan maturity (final repayment due)optional	2025-03-25
`last_payment_date`	date	Date of the most recent payment made by the borroweroptional	2023-12-15
True or false 1 column
`default_flag`	boolean	Indicates whether the loan has defaulted	false

Use it for

A finance dashboard
The default_flag rate, borrower_age by borrower_employment_status and a breakdown of borrower_address_country. Excel, Power BI or Tableau.
Why do the 26 retired rows have a mean borrower_age of 72.2?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Loans200
LN0000129employed
LN0003919student
LN0004023unemploy…
A software demo
Believable loans with borrower_id, investor_id and loan_amount to fill a screen in front of a buyer.

This dataset200 rows33 columns

Yours1,000 rows33 columnsborrower_address_street: UK only

blueprint · finance-peer-to-peer-lending-data

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 33 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 borrower and investor profiles
Track loan repayment status
Segment by loan type
Flag defaults and late payments

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-peer-to-peer-lending-data

What should your data show?

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Sample rows

What the 200 rows show

Columns

Use it for

A finance dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Finance

What should your data show?