Corporate Expense Reimbursement Analysis

This dataset provides comprehensive records of corporate expense reimbursements, including employee, approver, payment, and vendor details. It is designed to streamline finance operations, enable robust policy compliance monitoring, and support advanced fraud detection analytics for organizations of any size.

  • last updated 20 Aug 2025
  • by GoMask
The brief that made it

Automated expense processing and reimbursement tracking

Sample rows

preview · 8 of 200 rows · all 25 columns
reimbursement_idstringapproval_statusstringexpense_amountfloatfraud_flagbooleanpayment_methodstringemployee_idstringemployee_namestringdepartmentstringexpense_datedatesubmission_datedateapproval_datedateexpense_categorystringcurrencystringpolicy_compliance_flagbooleanapprover_idstringapprover_namestringpayment_datedatevendor_namestringvendor_street_addressstringvendor_citystringvendor_statestringvendor_postal_codestringvendor_countrystringexpense_descriptionstringrejection_reasonstring
RB2024010001Approved48.25falseDirect DepositEMP001Sarah LinFinance2024-01-052024-01-062024-01-08MealsUSDtrueMGR1001Carla Jimenez2024-01-10Midtown Cafe101 Main StNew YorkNY10001USAClient lunch at Midtown Cafe with finance teamblank
RB2024010002Approved325.99falsePayPalEMP002Jonas SchmidtEngineering2024-01-122024-01-132024-01-15Office SuppliesEURtrueMGR1002Mohammed Rizvi2024-01-17TechShop AG45 Berliner StrasseBerlinBE10715GermanyPurchase of monitors and keyboards for development teamblank
RB2024010003Pending580.5falseblankEMP003Maria FernandesMarketing2024-01-212024-01-22blankEntertainmentBRLfalseMGR1003Lucas OliveirablankRio Arena200 Avenida BrasilRio de JaneiroRJ22040-020BrazilTickets for product launch event at Rio Arenablank
RB2024010004Approved1350.25falseDirect DepositEMP004Emily ChenR&D2024-01-092024-01-102024-01-12TravelJPYtrueMGR1004Naoko Sato2024-01-15ANA Airlines2-3-2 Haneda AirportTokyoTK144-0041JapanFlight to Tokyo for research symposiumblank
RB2024010005Approved41.75falseDirect DepositEMP005Samuel OkoroSupport2024-01-172024-01-182024-01-20TransportationNGNtrueMGR1005Chinedu Umeh2024-01-23Lagos Taxi Co.58 Allen AvenueLagosLA101001NigeriaTaxi fare for client onsite support at Lagos officeblank
RB2024010006Submitted320falseblankEMP006Olga IvanovaLegal2024-01-112024-01-13blankOtherRUBtrueMGR1006Andrey PetrovblankMoscow Translations12 Tverskaya StMoscowMOW125009RussiaLegal document translation for compliance reviewblank
RB2024010007Approved405.5falseCheckEMP007David MartinezSales2024-01-222024-01-232024-01-26TravelMXNtrueMGR1007Andrea Ruiz2024-01-30Gran Hotel Reforma120 Paseo de la ReformaMexico CityCDMX06500MexicoHotel stay for sales conference in Mexico Cityblank
RB2024010008Approved5.45falseDirect DepositEMP008Kim Min-JungIT2024-01-272024-01-282024-01-30TransportationKRWtrueMGR1008Soo-Young Park2024-02-02Seoul Metro1 Jongno-guSeoulKR03154South KoreaSubway fare for attending IT training in Seoulblank

What the 200 rows show

from the 200-row sample

Rejected (approval status) stands out: 12 of its 25 rows have fraud_flag = true, against 0 of 175 for the rest.

  • 6%fraud_flag = true
  • 59.4median expense_amount
  • 7expense categories
  • 12departments
  • 12currencies
  • 13vendor countries
Fraud flag rate by approval_statusfraud_flag = true
0%50%100%0%Submitted0 of 290%Approved0 of 12448%Rejected12 of 250%Pending0 of 22

Rejected (approval status)'s mean expense_amount is 1,676, against 80.6 for Submitted, 163.3 for Approved and 107.7 for Pending.

expense_amount200 rows, in bands of 1,000
09519019050200000305,00010kexpense_amount →

Median 59.4, from 2.5 to 9,500.

payment_method124 rows with a value · 76 left blank
  1. Direct Deposit92
  2. PayPal13
  3. Check13
  4. Other6
25 columns by typefrom the column list below
  • string 18
  • float 1
  • date 4
  • boolean 2

Columns

25 columns in four groups
blueprint · 25 columns
columntypedescriptionexample
Text 18 columns
reimbursement_idstringUnique identifier for each expense reimbursement recorduniqueRB2024010001
employee_idstringUnique identifier for the employee submitting the reimbursementEMP001
employee_namestringFull name of the employeeSarah Lin
departmentstringDepartment to which the employee belongs12 departmentsFinance
expense_categorystringCategory of the expense (e.g., Travel, Meals, Office Supplies)7 valuesMeals
expense_descriptionstringDetailed description of the expensePurchase of HDMI cables
currencystringCurrency code for the expense amount (e.g., USD, EUR)12 currenciesUSD
approver_idstringUnique identifier for the manager or approveroptionalMGR1001
approver_namestringFull name of the manager or approveroptionalCarla Jimenez
approval_statusstringCurrent status of the reimbursement (e.g., Submitted, Approved, Rejected, Pending)Submitted · Approved · Rejected · PendingApproved
rejection_reasonstringReason for rejection if the reimbursement was not approvedoptionalExpense exceeds allowed m…
payment_methodstringMethod used for reimbursement payment (e.g., Direct Deposit, Check, PayPal)Direct Deposit · Check · PayPal · Other · optionalDirect Deposit
vendor_namestringName of the vendor or merchant associated with the expense, if applicableoptionalMidtown Cafe
vendor_street_addressstringStreet address of the vendoroptional101 Main St
vendor_citystringCity of the vendoroptionalNew York
vendor_statestringState or province of the vendoroptionalNY
vendor_postal_codestringPostal code of the vendoroptional10001
vendor_countrystringCountry of the vendoroptionalUSA
Numbers 1 column
expense_amountfloatAmount claimed for reimbursement0.01 or more48.25
Dates and times 4 columns
expense_datedateDate when the expense was incurred2024-01-05
submission_datedateDate when the reimbursement was submitted2024-01-06
approval_datedateDate when the reimbursement was approved (if applicable)optional2024-01-08
payment_datedateDate when the reimbursement was paid to the employeeoptional2024-01-10
True or false 2 columns
policy_compliance_flagbooleanIndicates if the expense complies with company policytrue
fraud_flagbooleanIndicates if the expense is flagged for potential fraudfalse

Use it for

  • fraud flag6%12 of 200 rowsmean expense amount b…80.6Subm…163.3Appr…1.7kReje…107.7Pend…

    A finance dashboard

    The fraud_flag rate, expense_amount by approval_status and a breakdown of payment_method. Excel, Power BI or Tableau.

  • Why do 12 of 200 rows have fraud_flag = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable reimbursements with employee_id, employee_name and department to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 25 columns, your size and your rules. See 20 rows before you pay.

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This dataset200 rows25 columns
Yours1,000 rows25 columnsvendor_street_address: UK only

blueprint · corporate-expense-reimbursement-analysis

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 25 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
  • Employee ID and expense details anonymized
  • Approval status captured
  • Expense type and amount tracked
  • Policy violations flagged
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
corporate-expense-reimbursement-analysis

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