Finance
17 columns
201 rows
8 formats

ATM Transaction Usage Patterns

This dataset provides daily aggregated cash withdrawal and deposit activity for each ATM, including transaction counts, total and average amounts, unique card usage, and a flag for suspicious activity. The data is ideal for analyzing ATM usage patterns, forecasting cash demand, and monitoring for potential fraud across different locations. Detailed location fields enable geographic and branch-level insights.

opened 13 times
last updated 12 Jul 2025
by GoMask

The brief that made it

ATM cash demand forecasting and optimization

Sample rows

preview · 8 of 201 rows · all 17 columns

atm_idstring	total_withdrawal_amountfloat	suspicious_activity_flagboolean	location_countrystring	location_idstring	location_street_addressstring	location_citystring	location_statestring	location_postal_codestring	transaction_datedate	total_withdrawal_countinteger	total_deposit_countinteger	total_deposit_amountfloat	unique_card_countinteger	average_withdrawal_amountfloat	average_deposit_amountfloat	notesstring
ATM001	27389.5	false	USA	LOC1001	100 Main St	Chicago	IL	60601	2024-06-03	96	12	3422.15	87	285.31	285.18	Busy weekday in downtown business district
ATM002	9650	false	Canada	LOC1002	45 Queen St	Toronto	ON	M5H 2N2	2024-06-01	32	5	1225	28	301.56	245	Steady weekend flow, tourist area
ATM003	14560	false	USA	LOC1003	200 Market Lane	Boston	MA	02110	2024-06-07	57	11	2970	54	255.44	270	University area, start of month
ATM004	7740	false	UK	LOC1004	17 High Road	London	ENG	N12 8TP	2024-06-08	24	2	520	20	322.5	260	Busy Saturday, city center
ATM005	121800	true	USA	LOC1005	88 Sunset Blvd	Los Angeles	CA	90028	2024-06-01	210	2	1840	200	580	920	Concert event nearby, extremely high withdrawals
ATM006	640	false	USA	LOC1006	12 Riverbank Ave	St. Louis	MO	63101	2024-06-02	4	1	110	4	160	110	Low activity at night
ATM007	2860	false	Australia	LOC1007	55 Harbor Street	Sydney	NSW	2000	2024-06-04	13	2	270	10	220	135	Bilingual display tested, steady weekday
ATM008	32940	false	USA	LOC1008	9 Elm Place	Houston	TX	77002	2024-06-05	122	14	4732	110	270	338	Payday, high activity in business area
ATM009	4320	false	Ireland	LOC1009	4 Lakeview Drive	Dublin	blank	D02 Y006	2024-06-07	18	0	0	13	240	0	Tourist area, Friday evening
ATM010	1050	false	USA	LOC1010	27 Mountain Rd	Boulder	CO	80302	2024-06-06	7	1	90	6	150	90	Suburban ATM, low midweek activity
ATM011	49700	false	USA	LOC1011	3 Pine Lane	Miami	FL	33101	2024-06-02	140	29	8710	120	355	300.34	Busy weekend in tourist area
ATM012	0	false	USA	LOC1012	14 Maple Ave	New York	NY	10001	2024-06-08	0	0	0	0	0	0	ATM not yet activated
ATM013	1800	false	Austria	LOC1013	6 Bridge Rd	Innsbruck	TIR	6020	2024-06-07	8	1	150	7	225	150	Tourist ATM, moderate weekend activity
ATM014	14756	false	USA	LOC1014	19 Willow Way	Dallas	TX	75201	2024-06-05	53	9	2400	49	278.41	266.67	Business district, steady weekday flow
ATM015	840	false	USA	LOC1015	16 Cherry Ln	San Francisco	CA	94105	2024-06-03	4	0	0	4	210	0	Low activity, weekday morning
ATM016	4860	false	China	LOC1016	blank	Shenzhen	GD	518000	2024-06-01	18	3	570	14	270	190	Steady traffic, commercial district
ATM017	9680	false	Canada	LOC1017	21 Grove St	blank	QC	H2Y 1C6	2024-06-06	40	7	1680	36	242	240	Morning shift, bilingual display
ATM018	39780	false	USA	LOC1018	11 Birch Rd	Austin	TX	73301	2024-06-07	105	24	6500	97	379.81	270.83	Start of month, university area
ATM019	150	false	USA	LOC1019	8 Oak Hill	Philadelphia	PA	19107	2024-06-02	1	0	0	1	150	0	Test transaction after repair
ATM020	0	false	N/A	LOC1020	blank	N/A	blank	blank	2024-06-03	0	0	0	0	0	0	ATM offline for maintenance

What the 201 rows show

from the 201-row sample

5%suspicious_activity_flag = true
5,520median total_withdrawal_amount
44location states
22median total_withdrawal_count
4median total_deposit_count
1,125median total_deposit_amount

total_withdrawal_amount201 rows, in bands of 100k

Every row with total_withdrawal_amount of 100k or more has suspicious_activity_flag = true. None below it.

location_country201 rows · top 10 of 15 values

USA104
Canada19
UK18
Australia12
Ireland9
N/A9
China8
Austria7
France4
Switzerland3

17 columns by typefrom the column list below

string 8
integer 3
float 4
date 1
boolean 1

Columns

17 columns in four groups

blueprint · 17 columns
column	type	description	example
Text 8 columns
`atm_id`	string	Unique identifier for the ATM machine.	ATM001
`location_id`	string	Unique identifier for the ATM's location.	LOC1001
`location_street_address`	string	Street address of the ATM location.optional	100 Main St
`location_city`	string	City where the ATM is located.optional	Chicago
`location_state`	string	State or province where the ATM is located.optional	IL
`location_postal_code`	string	Postal code of the ATM location.optional	60601
`location_country`	string	Country where the ATM is located.optional	USA
`notes`	string	Free-text notes or comments related to the ATM's activity for the given date.optional	Low activity at night
Numbers 7 columns
`total_withdrawal_count`	integer	Total number of withdrawal transactions at the ATM on the given date.0 or more	96
`total_withdrawal_amount`	float	Total amount withdrawn from the ATM on the given date.0 or more	27389.5
`total_deposit_count`	integer	Total number of deposit transactions at the ATM on the given date.0 or more	12
`total_deposit_amount`	float	Total amount deposited into the ATM on the given date.0 or more	3422.15
`unique_card_count`	integer	Number of unique cards used at the ATM on the given date.0 or more · optional	87
`average_withdrawal_amount`	float	Average amount per withdrawal transaction at the ATM on the given date.0 or more · optional	285.31
`average_deposit_amount`	float	Average amount per deposit transaction at the ATM on the given date.0 or more · optional	285.18
Dates and times 1 column
`transaction_date`	date	Date for which the transaction data is aggregated.	2024-06-03
True or false 1 column
`suspicious_activity_flag`	boolean	Indicates if suspicious or potentially fraudulent activity was detected for this ATM on the given date.optional	false

Use it for

A finance dashboard
The suspicious_activity_flag rate, total_withdrawal_amount and a breakdown of location_country. Excel, Power BI or Tableau.
Why do 11 of 201 rows have suspicious_activity_flag = true?
A class exercise
Hand out the rows and one question. Everyone works from the same 201 rows.
Atms201
ATM00127389.5false
ATM005121800true
ATM023999999.99true
A software demo
Believable atms with location_id, location_street_address and location_city to fill a screen in front of a buyer.

This dataset201 rows17 columns

Yours1,000 rows17 columnslocation_id: UK only

blueprint · atm-transaction-usage-patterns

Behind this dataset

Same schema. As many rows as you need.

These 201 rows came out of a blueprint — 17 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

ATM ID, timestamp, and transaction type required
Include transaction amount and location type
No customer-level identifiers
Simulate various cash denominations

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: atm-transaction-usage-patterns

What should your data show?

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Sample rows

What the 201 rows show

Columns

Use it for

A finance dashboard

A class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

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