Finance
27 columns
200 rows
8 formats

Finance Personal Savings Patterns

This dataset provides a detailed view of personal savings patterns, combining customer demographics, income, and account activity with monthly savings breakdowns and product preferences. Financial institutions can leverage this data to design tailored savings products, predict customer retention, and identify at-risk customers for targeted engagement.

last updated 20 Aug 2025
by GoMask

The brief that made it

Designing targeted savings products based on customer patterns

Sample rows

preview · 8 of 200 rows · all 27 columns

customer_idstring	account_statusstring	retention_scorefloat	churn_riskboolean	address_countrystring	full_namestring	date_of_birthdate	genderstring	emailstring	phone_numberstring	address_streetstring	address_citystring	address_statestring	address_postal_codestring	account_idstring	account_typestring	account_open_datedate	average_monthly_balancefloat	total_deposits_last_12_monthsfloat	total_withdrawals_last_12_monthsfloat	primary_income_sourcestring	annual_incomefloat	employment_statusstring	risk_profilestring	preferred_savings_productsstring	last_product_engagement_datedate	monthly_savings_patternstring
CUST_001A	active	0.89	false	US	Martin Stevens	1987-03-14	male	martin.stevens87@finmail.com	+1-312-555-0193	127 Oak Grove Lane	Chicago	IL	60614	ACC_001A	regular	2018-04-05	7420.49	32200	17600	salary	82000	employed	medium	Regular Savings, Travel Fund, High-Yield	2024-05-16	{"Jan":2700,"Feb":2900,"Mar":3100,"Apr":3200,"May":3300,"Jun":3400,"Jul":3500,"Aug":3600,"Sep":3700,"Oct":3800,"Nov":3900,"Dec":4000}
CUST_002B	active	0.93	false	India	Priya Kothari	1996-11-22	female	priya.kothari96@inmail.co	+91-22-555-0907	19 Sarvodaya Marg	Mumbai	MH	400021	ACC_002B	high-yield	2021-09-10	12540.85	48500	21000	salary	115000	employed	high	High-Yield, Travel Fund	2024-06-01	{"Jan":3800,"Feb":4050,"Mar":4100,"Apr":4200,"May":4250,"Jun":4300,"Jul":4400,"Aug":4450,"Sep":4600,"Oct":4700,"Nov":4750,"Dec":4800}
CUST_003C	active	0.92	false	Germany	Sven J. Koenig	1970-06-02	male	sven.koenig70@gmx.de	+49-30-555-6721	44 Berliner Platz	Berlin	BE	10115	ACC_003C	fixed-deposit	2013-02-12	76350.25	210000	19000	business	324000	self-employed	medium	Fixed Deposit, High-Yield	2024-03-22	{"Jan":18000,"Feb":19500,"Mar":17500,"Apr":18000,"May":17000,"Jun":18000,"Jul":18500,"Aug":19000,"Sep":19500,"Oct":20000,"Nov":20500,"Dec":21000}
CUST_004D	active	0.82	false	UK	Heather McCarthy	1966-02-18	female	heather.mccarthy66@ukmail.net	+44-20-555-8811	12 Baker Street	London	ENG	NW16XE	ACC_004D	retirement	2010-08-13	26340.7	7100	8400	pension	23800	retired	low	Retirement, Regular Savings	2024-01-12	{"Jan":600,"Feb":700,"Mar":800,"Apr":700,"May":600,"Jun":500,"Jul":400,"Aug":300,"Sep":200,"Oct":100,"Nov":100,"Dec":100}
CUST_005E	active	0.63	false	China	Mei X. Zhang	2002-07-25	female	mei.zhang02@chmail.cn	+86-21-555-3298	88 Huaihai Road	Shanghai	SH	200031	ACC_005E	regular	2022-05-20	1150.45	3650	1800	other	1200	student	medium	Teen Savings, Regular Savings	2024-05-07	{"Jan":300,"Feb":350,"Mar":280,"Apr":290,"May":310,"Jun":340,"Jul":360,"Aug":390,"Sep":400,"Oct":420,"Nov":430,"Dec":450}
CUST_006F	active	0.87	false	UAE	Ahmed Y. Al-Farsi	1981-09-10	male	ahmed.alfarsi81@uaemail.ae	+971-2-555-2021	23 Sheikh Zayed Rd	Abu Dhabi	AD	00041	ACC_006F	high-yield	2017-01-24	18800.32	61200	34000	salary	142000	employed	medium	High-Yield, Regular Savings	2024-05-30	{"Jan":4900,"Feb":5000,"Mar":5100,"Apr":5200,"May":5300,"Jun":5400,"Jul":5500,"Aug":5600,"Sep":5700,"Oct":5800,"Nov":5900,"Dec":6000}
CUST_007G	active	0.52	false	India	Jasmine Patel	2006-12-01	female	jasmine.patel06@inmail.co	blank	5 Sardar Road	Ahmedabad	GJ	380009	ACC_007G	regular	2023-09-11	410.23	850	650	other	0	student	medium	Teen Savings, Regular Savings	2024-05-16	{"Jan":45,"Feb":55,"Mar":65,"Apr":70,"May":75,"Jun":80,"Jul":85,"Aug":90,"Sep":95,"Oct":100,"Nov":105,"Dec":110}
CUST_008H	active	0.85	false	France	Lucas N. Moreau	1990-02-27	male	lucas.moreau90@frmail.fr	+33-1-555-5588	77 Rue Lafayette	Paris	IDF	75009	ACC_008H	regular	2019-08-07	10650.9	28700	10500	salary	68000	employed	medium	Regular Savings, High-Yield	2024-06-02	{"Jan":2200,"Feb":2100,"Mar":2300,"Apr":2350,"May":2400,"Jun":2450,"Jul":2500,"Aug":2550,"Sep":2600,"Oct":2650,"Nov":2700,"Dec":2750}
CUST_009I	dormant	0.28	true	UAE	Fatima Al-Mansouri	1954-04-18	female	fatima.mansouri54@uaemail.ae	+971-4-555-3344	254 Al Wasl Road	Dubai	DU	00022	ACC_009I	retirement	2002-05-23	3200.11	0	1200	pension	16000	retired	low	Retirement, Regular Savings	2023-09-02	{"Jan":100,"Feb":100,"Mar":100,"Apr":100,"May":100,"Jun":100,"Jul":100,"Aug":100,"Sep":100,"Oct":100,"Nov":100,"Dec":100}
CUST_010J	active	0.91	false	US	Emily R. Thompson	1985-10-08	female	emily.thompson85@usmail.com	+1-718-555-1124	6412 Willow Ave	Brooklyn	NY	11220	ACC_010J	high-yield	2020-03-12	15800.77	55200	29000	salary	98000	employed	medium	High-Yield, Regular Savings	2024-06-03	{"Jan":4100,"Feb":4200,"Mar":4300,"Apr":4400,"May":4500,"Jun":4600,"Jul":4700,"Aug":4800,"Sep":4900,"Oct":5000,"Nov":5100,"Dec":5200}
CUST_011K	active	0.96	false	Russia	Tatiana V. Smirnova	1978-12-30	female	tatiana.smirnova78@runet.ru	+7-495-555-7788	11 Prospekt Mira	Moscow	MOW	129110	ACC_011K	fixed-deposit	2014-07-10	115900.34	325500	31000	investment	640000	self-employed	high	Fixed Deposit, High-Yield	2024-05-29	{"Jan":26000,"Feb":26500,"Mar":27000,"Apr":27500,"May":28000,"Jun":28500,"Jul":29000,"Aug":29500,"Sep":30000,"Oct":30500,"Nov":31000,"Dec":31500}
CUST_012L	active	0.86	false	Brazil	Ana M. Ribeiro	1989-05-16	female	ana.ribeiro89@brmail.br	+55-11-555-2289	99 Rua Augusta	São Paulo	SP	01305-000	ACC_012L	regular	2018-11-21	9342.12	31200	14200	salary	61000	employed	medium	Regular Savings, Travel Fund	2024-05-27	{"Jan":2100,"Feb":2200,"Mar":2300,"Apr":2400,"May":2500,"Jun":2600,"Jul":2700,"Aug":2800,"Sep":2900,"Oct":3000,"Nov":3100,"Dec":3200}
CUST_013M	dormant	0.13	true	India	Rakesh K. Sharma	1957-01-23	male	rakesh.sharma57@inmail.co	blank	12 Nehru Road	Delhi	DL	110001	ACC_013M	retirement	2005-04-15	1700.44	0	700	pension	12000	retired	low	Retirement, Regular Savings	2023-12-16	{"Jan":50,"Feb":60,"Mar":70,"Apr":80,"May":90,"Jun":100,"Jul":110,"Aug":120,"Sep":130,"Oct":140,"Nov":150,"Dec":160}
CUST_014N	active	0.81	false	South Korea	Sophia P. Lee	1999-10-12	female	sophia.lee99@krmail.kr	+82-2-555-9987	203 Gangnam-daero	Seoul	SEO	06254	ACC_014N	high-yield	2022-02-14	13500.12	42000	21000	salary	92000	employed	medium	High-Yield, Regular Savings	2024-06-03	{"Jan":3500,"Feb":3600,"Mar":3700,"Apr":3800,"May":3900,"Jun":4000,"Jul":4100,"Aug":4200,"Sep":4300,"Oct":4400,"Nov":4500,"Dec":4600}
CUST_015O	closed	0.04	true	US	George F. Harris	1948-11-19	male	george.harris48@usmail.com	+1-305-555-0842	900 Ocean Drive	Miami	FL	33139	ACC_015O	retirement	2000-03-03	0	0	0	pension	9000	retired	unknown	Retirement	2023-02-11	blank
CUST_016P	active	0.83	false	Italy	Chiara De Santis	1983-04-05	female	chiara.desantis83@itmail.it	+39-06-555-3311	15 Via Appia Nuova	Rome	RM	00183	ACC_016P	regular	2019-09-16	6200.67	21600	9400	salary	58000	employed	medium	Regular Savings, Travel Fund	2024-05-24	{"Jan":1500,"Feb":1550,"Mar":1600,"Apr":1650,"May":1700,"Jun":1750,"Jul":1800,"Aug":1850,"Sep":1900,"Oct":1950,"Nov":2000,"Dec":2050}
CUST_017Q	active	0.89	false	Russia	Olga I. Petrov	1974-08-14	female	olga.petrov74@runet.ru	+7-812-555-4412	21 Nevsky Prospect	St Petersburg	SPE	191025	ACC_017Q	fixed-deposit	2012-04-11	54500.42	158000	14000	business	226000	self-employed	medium	Fixed Deposit, High-Yield	2024-05-18	{"Jan":12500,"Feb":13000,"Mar":13500,"Apr":14000,"May":14500,"Jun":15000,"Jul":15500,"Aug":16000,"Sep":16500,"Oct":17000,"Nov":17500,"Dec":18000}
CUST_018R	active	0.41	true	Japan	Hiroshi Tanaka	2005-03-03	male	hiroshi.tanaka05@jpmail.jp	blank	3-17 Shibuya	Tokyo	TKY	150-0002	ACC_018R	regular	2023-04-21	560.18	960	750	other	0	student	medium	Teen Savings, Regular Savings	2024-05-11	{"Jan":60,"Feb":70,"Mar":80,"Apr":90,"May":100,"Jun":110,"Jul":120,"Aug":130,"Sep":140,"Oct":150,"Nov":160,"Dec":170}
CUST_019S	active	0.91	false	Germany	Nina S. Lorenz	1980-07-08	female	nina.lorenz80@gmx.de	+49-89-555-6532	21 Sonnenstraße	Munich	BY	80331	ACC_019S	high-yield	2016-06-22	17850.23	53000	26000	salary	124000	employed	medium	High-Yield, Regular Savings	2024-06-02	{"Jan":4200,"Feb":4300,"Mar":4400,"Apr":4500,"May":4600,"Jun":4700,"Jul":4800,"Aug":4900,"Sep":5000,"Oct":5100,"Nov":5200,"Dec":5300}
CUST_020T	active	0.9	false	China	Li Wei	1972-12-15	male	li.wei72@chmail.cn	+86-10-555-2198	102 Chang'an Avenue	Beijing	BJ	100005	ACC_020T	fixed-deposit	2011-05-18	64900.16	175000	16000	business	204000	self-employed	medium	Fixed Deposit, High-Yield	2024-05-21	{"Jan":13500,"Feb":14000,"Mar":14500,"Apr":15000,"May":15500,"Jun":16000,"Jul":16500,"Aug":17000,"Sep":17500,"Oct":18000,"Nov":18500,"Dec":19000}

What the 200 rows show

from the 200-row sample

Dormant (account status) stands out: 16 of its 16 rows have churn_risk = true, against 15 of 184 for the rest.

16%churn_risk = true
0.82median retention_score
3genders
4employment statuses
4risk profiles
5account types

Churn risk rate by account_statuschurn_risk = true

Dormant (account status)'s mean retention_score is 0.16, against 0.80 for active and 0.04 for closed.

retention_score200 rows, in bands of 0.1

Median 0.82, from 0.02 to 0.96.

address_country200 rows · top 10 of 32 values

US42
India17
Russia15
Germany11
UK11
China11
Spain10
UAE9
France9
South Korea9

27 columns by typefrom the column list below

string 18
float 5
date 3
boolean 1

Columns

27 columns in four groups

blueprint · 27 columns
column	type	description	example
Text 18 columns
`customer_id`	string	Unique identifier for each customerunique	CUST_001A
`full_name`	string	Customer's full legal name	Martin Stevens
`gender`	string	Customer's gender identitymale · female · other · prefer_not_to_say · optional	male
`email`	string	Customer's email addressunique	sven.koenig70@gmx.de
`phone_number`	string	Customer's primary phone numberoptional	+1-312-555-0193
`address_street`	string	Street address of the customeroptional	127 Oak Grove Lane
`address_city`	string	City of the customer's addressoptional	Chicago
`address_state`	string	State or province of the customer's addressoptional	IL
`address_postal_code`	string	Postal or ZIP code of the customer's addressoptional	60614
`address_country`	string	Country of the customer's addressoptional	US
`account_id`	string	Unique identifier for the customer's savings accountunique	ACC_001A
`account_type`	string	Type of savings accountregular · high-yield · fixed-deposit · retirement · other	regular
`account_status`	string	Current status of the savings accountactive · dormant · closed · suspended	active
`monthly_savings_pattern`	string	Monthly breakdown of savings activity (e.g., deposits, withdrawals, balance) for the past 12 months as a JSON objectoptional	{"Jan":2700,"Feb":2900,"M…
`primary_income_source`	string	Main source of the customer's incomesalary · business · investment · pension · other · optional	salary
`employment_status`	string	Customer's current employment status6 values · optional	employed
`risk_profile`	string	Customer's risk tolerance profile as assessed by the banklow · medium · high · unknown · optional	medium
`preferred_savings_products`	string	List of savings products the customer is interested in or currently uses, stored as a JSON array of product namesoptional	High-Yield, Travel Fund
Numbers 5 columns
`average_monthly_balance`	float	Average monthly balance maintained in the savings account over the past 12 months0 or more	7420.49
`total_deposits_last_12_months`	float	Total amount deposited into the savings account in the last 12 months0 or more	32200
`total_withdrawals_last_12_months`	float	Total amount withdrawn from the savings account in the last 12 months0 or more	17600
`annual_income`	float	Customer's annual income in local currency0 or more · optional	82000
`retention_score`	float	Score indicating likelihood of customer retention, calculated by the bank (0-1)0 to 1 · optional	0.89
Dates and times 3 columns
`date_of_birth`	date	Customer's date of birth	1987-03-14
`account_open_date`	date	Date when the savings account was opened	2018-04-05
`last_product_engagement_date`	date	Date of last engagement with any savings product (e.g., inquiry, application, transaction)optional	2024-05-16
True or false 1 column
`churn_risk`	boolean	Indicates if the customer is at risk of leaving the bankoptional	false

Use it for

A finance dashboard
The churn_risk rate, retention_score by account_status and a breakdown of address_country. Excel, Power BI or Tableau.
Why do 31 of 200 rows have churn_risk = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Customers200
CUST_001A0.89active
CUST_009I0.28dormant
CUST_013M0.13dormant
A software demo
Believable customers with full_name, date_of_birth and gender to fill a screen in front of a buyer.

This dataset200 rows27 columns

Yours1,000 rows27 columnsaddress_street: UK only

blueprint · finance-personal-savings-patterns

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 27 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

Track monthly savings deposits
Segment by age group
Include account balance history
Flag inactive accounts

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

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: finance-personal-savings-patterns

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?