Analytics Catalog/Oracle Fusion ERP/Receivables/Create Automatic Receipt Write-offs Execution Report
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Seeded report · Receipts

Create Automatic Receipt Write-offs Execution Report

Receivables◆ Seeded · Receipts

Reports the process that writes off small unapplied amounts on receipts, by currency, customer, receipt number, amount, and date.

Sample build of the Create Automatic Receipt Write-offs Execution Report — reconciled, and rendered tool-neutral so it runs in Power BI, ThoughtSpot, or Tableau.

Create Automatic Receipt Write-offs Execution Report
Sample build · illustrative
Filters
Period
FEB-26
Ledger
US Primary
Currency
USD
210
Write-offs
$18K
Written off
7
Over tolerance
CustomerReceiptCurrencyWrite-off AmountDate
Acme IndustrialSampleUSD$1,240,500.002026-04-30
Northwind Trading—USD$842,150.752026-03-31
Globex HoldingsSampleUSD$96,400.002026-02-28
Initech LLC—USD$1,005,233.102026-01-31
Umbrella CorpSampleUSD$58,720.402025-12-31
Acme IndustrialSampleUSD$1,240,500.002026-04-30
AI Analyst · active
reading

The report reports the process that writes off small unapplied amounts on receipts.

flag

Seven write-offs exceed the small-balance tolerance — larger amounts cleared as if they were rounding.

root cause & next step

Review write-offs above tolerance individually; an oversized auto-write-off can hide a real short-payment dispute.

Illustrative data. The live interactive version — drill-through, filters, export, and the AI Analyst — runs on your warehouse. See it live →

This is the report's BI Publisher data model — the SQL data set BI Publisher runs against Oracle tables to produce the output. The same SQL becomes a dbt model in your warehouse, so one definition drives both the formatted report and the analytics layer.

Data sources

How it interconnects: this data set reads the physical tables above. Those same tables surface in OTBI as subject areas and in BICC as PVOs — three lenses on one source. Open any table to trace its subject areas and View Objects.
The SQL data set is authored to this report's exact spec during the build and ships as the BI Publisher data model plus a matching dbt model — one definition, both layers.

The data-warehouse model — one fact surrounded by conformed dimensions (what you slice by) and measures (what you aggregate), expressed as dbt so it migrates with you. Grain: one row per source transaction.

AR_RECEIVABLE_APPLICATIO…dimensionAR_CASH_RECEIPTS_ALLfact · one row per source transactionWrite-off Amount
●— fact → dimension join
ElementTypeDefinition
AR_RECEIVABLE_APPLICATIONS_ALLdimensiondimension
Write-off Amountmeasuremeasure
Runs on your cloud warehouse — Snowflake, BigQuery, Redshift, or Synapse on AWS, Google Cloud, Azure, or any provider. Reconciled to the source control total — 0% variance by design. You own the code, the model, and the data.
How the data gets here: a BICC bulk extract of the source tables above, on the same pattern for every report. See the extraction pattern & data flow →
See the complete model
How this report's fact and dimensions fit the full picture, via conformed keys.
Receivables data model →Enterprise model →

Every source object behind this report. Each linked table has its own page with full column descriptions, drawn from the Oracle BICC lineage and articulated for practitioners.

TableReporting columnsSubject areas
AR_CASH_RECEIPTS_ALL259
AR_RECEIVABLE_APPLICATIONS_ALL352
Reporting columns = fields the report selects that are exposed as analytics attributes; subject areas = the OTBI subject areas the table appears in. Setup and configuration tables (master data, ledger and book setup, lookups) are referenced by the report's joins but aren't exposed as analytics columns or subject areas — that's expected, not a gap.

Customization note  Write-off thresholds and approvals are policy-driven; the build adds a controlled approval trail. Irvine rebuilds these on your data.