Finance
18 columns
200 rows
8 formats

Finance AML Transaction Alerts

This dataset contains synthetic banking transactions annotated with anti-money laundering (AML) alert flags, detailed reason codes, and customer risk information. It is designed to support the development and evaluation of compliance models, enabling detection of suspicious activities and regulatory reporting. The dataset includes transaction details, alert triggers, and customer risk profiles for comprehensive AML analytics.

opened 5 times
last updated 29 Jul 2025
by GoMask

The brief that made it

Training and testing AML detection models

Sample rows

preview · 8 of 200 rows · all 18 columns

transaction_idstring	customer_risk_levelstring	transaction_amountfloat	alert_flagboolean	customer_countrystring	account_idstring	customer_idstring	transaction_datetimedatetime	currencystring	transaction_typestring	counterparty_account_idstring	counterparty_bank_namestring	transaction_descriptionstring	alert_labelstring	alert_reason_codestring	branch_idstring	is_internationalboolean	alert_reason_descriptionstring
TXN000001	unknown	0	false	US	ACC0001	CUST001	2022-12-31T00:00:01Z	USD	deposit	blank	blank	Micro-deposit for account verification	none	blank	BR001	false	blank
TXN000002	low	25.47	false	DE	ACC0002	CUST002	2023-01-15T09:12:15Z	EUR	withdrawal	blank	blank	ATM withdrawal	none	blank	BR002	false	blank
TXN000003	low	450	false	JP	ACC0003	CUST003	2023-02-01T16:45:03Z	JPY	payment	blank	blank	Online retail purchase	none	blank	BR003	false	blank
TXN000004	medium	2500	false	US	ACC0001	CUST001	2023-03-01T10:25:36Z	USD	transfer	ACC0005	Bank of Canada	Family support transfer	none	blank	BR001	true	blank
TXN000005	unknown	0.99	false	UK	ACC0004	CUST004	2023-04-10T12:22:10Z	GBP	deposit	blank	blank	Test micro-deposit	none	blank	BR004	false	blank
TXN000006	high	1250000	true	SG	ACC0005	CUST005	2023-05-15T23:59:59Z	SGD	transfer	ACC0010	HSBC Singapore	Business capital transfer	high-value	AML-HV-01	BR005	true	Transaction amount exceeds regulatory high-value threshold.
TXN000007	low	110.25	false	US	ACC0006	CUST006	2023-06-21T18:35:47Z	USD	payment	blank	blank	Utility bill payment	none	blank	BR001	false	blank
TXN000008	high	9999999.99	true	CH	ACC0007	CUST007	2023-07-04T11:11:11Z	CHF	transfer	ACC0011	Credit Suisse	Large international transfer	structuring	AML-STR-21	BR006	true	Multiple high-value transfers detected within short period.
TXN000009	low	78.5	false	DE	ACC0002	CUST002	2023-07-25T05:12:00Z	EUR	withdrawal	blank	blank	ATM withdrawal	none	blank	BR002	false	blank
TXN000010	medium	15000	false	US	ACC0008	CUST008	2023-08-13T19:45:23Z	USD	deposit	blank	blank	Salary deposit	none	blank	BR007	false	blank
TXN000011	low	0	false	AU	ACC0009	CUST009	2023-09-02T07:01:44Z	AUD	deposit	blank	blank	blank	none	blank	BR008	false	blank
TXN000012	medium	700	false	IN	ACC0010	CUST010	2023-09-14T15:55:32Z	INR	payment	blank	blank	Mobile recharge	none	blank	BR009	false	blank
TXN000013	medium	20000	true	IN	ACC0011	CUST011	2023-10-05T08:22:59Z	AED	transfer	ACC0015	Dubai Islamic Bank	Remittance to UAE	suspicious-country	AML-SC-03	BR010	true	Transfer to country on watchlist for AML risk.
TXN000014	low	150	false	US	ACC0012	CUST012	2023-10-18T22:11:01Z	USD	payment	blank	blank	Restaurant bill	none	blank	BR001	false	blank
TXN000015	medium	500	false	PH	ACC0013	CUST013	2023-11-11T11:11:11Z	PHP	deposit	blank	blank	Cash deposit	none	blank	BR011	false	blank
TXN000016	low	20	false	CA	ACC0014	CUST014	2023-12-24T23:59:59Z	CAD	withdrawal	blank	blank	ATM withdrawal	none	blank	BR012	false	blank
TXN000017	unknown	0.01	false	DE	ACC0015	CUST015	2024-01-01T00:00:01Z	EUR	deposit	blank	blank	Test micro-deposit	none	blank	blank	false	blank
TXN000018	low	65	false	UK	ACC0016	CUST016	2024-01-15T15:20:19Z	GBP	payment	blank	blank	Groceries	none	blank	BR013	false	blank
TXN000019	medium	8500	false	US	ACC0017	CUST017	2024-01-20T14:18:22Z	USD	transfer	ACC0020	Wells Fargo	Split bill payment	none	blank	BR014	false	blank
TXN000020	high	8000000	true	AE	ACC0018	CUST018	2024-01-27T06:12:30Z	AED	transfer	ACC0025	Mashreq Bank	Corporate remittance	high-value	AML-HV-07	BR015	true	Large transaction flagged for enhanced AML review.

What the 200 rows show

from the 200-row sample

High (customer risk level) stands out: 38 of its 38 rows have alert_flag = true, against 1 of 162 for the rest.

20%alert_flag = true
332.9median transaction_amount
5transaction types
5alert labels
11currencies

Alert flag rate by customer_risk_levelalert_flag = true

High (customer risk level)'s mean transaction_amount is 2,998,419, against 205.3 for low, 2,801 for medium and 0.29 for unknown.

transaction_amount200 rows, in bands of 1M

Median 332.9, from 0.0 to 10,000,000.

customer_country200 rows · top 10 of 14 values

US58
SG22
DE17
CA17
JP14
UK13
CH13
AU13
FR12
IN10

18 columns by typefrom the column list below

string 14
float 1
datetime 1
boolean 2

Columns

18 columns in four groups

blueprint · 18 columns
column	type	description	example
Text 14 columns
`transaction_id`	string	Unique identifier for the banking transactionunique	TXN000001
`account_id`	string	Unique identifier for the account involved in the transaction	ACC0001
`customer_id`	string	Unique identifier for the customer associated with the account	CUST001
`currency`	string	ISO 4217 currency code for the transaction (e.g., USD, EUR)11 currencies	USD
`transaction_type`	string	Type of transaction (e.g., deposit, withdrawal, transfer, payment)deposit · withdrawal · transfer · payment · other	deposit
`counterparty_account_id`	string	Identifier for the counterparty account (if applicable, e.g., for transfers)optional	ACC0005
`counterparty_bank_name`	string	Name of the counterparty bank (if applicable)optional	Bank of Canada
`transaction_description`	string	Free-text description or memo for the transactionoptional	ATM withdrawal
`alert_label`	string	Label or category of the AML alert (e.g., structuring, high-value, suspicious-country, none)6 values · optional	none
`alert_reason_code`	string	Detailed reason code for the AML alert, referencing compliance rulesoptional	AML-HV-01
`alert_reason_description`	string	Human-readable description explaining why the alert was triggeredoptional	Transaction amount exceed…
`branch_id`	string	Identifier for the bank branch where the transaction was initiatedoptional	BR001
`customer_country`	string	Country of the customer involved in the transactionoptional	US
`customer_risk_level`	string	Risk level assigned to the customer (e.g., low, medium, high)low · medium · high · unknown · optional	unknown
Numbers 1 column
`transaction_amount`	float	Monetary amount of the transaction0 or more	0
Dates and times 1 column
`transaction_datetime`	datetime	Date and time when the transaction occurred	2022-12-31T00:00:01Z
True or false 2 columns
`alert_flag`	boolean	Indicates whether the transaction triggered an AML alert	false
`is_international`	boolean	Indicates if the transaction is internationaloptional	false

Use it for

A finance dashboard
The alert_flag rate, transaction_amount by customer_risk_level and a breakdown of customer_country. Excel, Power BI or Tableau.
Why do 39 of 200 rows have alert_flag = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Transactions200
TXN0000010unknown
TXN0000061250000high
TXN0000089999999.99high
A software demo
Believable transactions with account_id, customer_id and transaction_datetime to fill a screen in front of a buyer.

This dataset200 rows18 columns

Yours1,000 rows18 columnsbranch_id: UK only

blueprint · finance-aml-transaction-alerts

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 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

High value and cross-border flagged
Alerts have reason code and severity
Linked transactions grouped by AML case
Account profiles anonymized

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-aml-transaction-alerts

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?