Generate Late Charges Report

Receivables◆ Seeded · Receivables balances

Prints late charges raised on overdue or late-paid transactions by batch, with transaction number, due date, and overdue amount.

Sample build of the Generate Late Charges Report — reconciled, and rendered tool-neutral so it runs in Power BI, ThoughtSpot, or Tableau.

Sample build · illustrative

Filters

Period

FEB-26

Ledger

US Primary

Currency

USD

320

Charged transactions

$48K

Late charges

Disputed

Customer	Transaction	Due Date	Days Overdue	Late Charge
Acme Industrial	Sample	2026-04-30	Sample	Sample
Northwind Trading	—	2026-03-31	—	—
Globex Holdings	Sample	2026-02-28	Sample	Sample
Initech LLC	—	2026-01-31	—	—
Umbrella Corp	Sample	2025-12-31	Sample	Sample
Acme Industrial	Sample	2026-04-30	Sample	Sample

AI Analyst · active

reading

The report prints late charges raised on overdue transactions, by batch.

flag

14 late charges are disputed — charges customers are contesting, often where the original due date or terms were wrong.

root cause & next step

Verify terms before charging; a disputed late charge usually traces to a terms or grace-period setup error.

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.

●— fact → dimension join

Element	Type	Definition
RA_CUSTOMER_TRX_ALL	dimension	dimension
HZ_CUST_ACCOUNTS	dimension	dimension
Amount	measure	measure

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.

Table	Reporting columns	Subject areas
AR_PAYMENT_SCHEDULES_ALL	32	6
RA_CUSTOMER_TRX_ALL	58	16
HZ_CUST_ACCOUNTS	14	43

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 Late-charge policy varies by customer; teams usually externalize the rules and add a preview and approval step before charges post. Irvine rebuilds these on your data.