Payables Cash Requirement Report

Payables◆ Seeded · Payments

Forecasts immediate cash needs for invoice payments.

Sample build of the Payables Cash Requirement 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

$8.40M

Due next 7 days

$120K

Discounts available

1 acct

Shortfall risk

Pay Date	Bank Account	Due Amount	Discountable	Currency
2026-04-30	1000-2100-000	$1,240,500.00	Sample	USD
2026-03-31	1000-5400-000	$842,150.75	—	USD
2026-02-28	1000-1410-000	$96,400.00	Sample	USD
2026-01-31	2000-2100-000	$1,005,233.10	—	USD
2025-12-31	1000-6300-000	$58,720.40	Sample	USD
2026-04-30	1000-2100-000	$1,240,500.00	Sample	USD

AI Analyst · active

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The report forecasts immediate cash needs for upcoming invoice payments.

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One bank account's scheduled payments exceed its projected balance — a funding shortfall before the run.

root cause & next step

Fund or re-sequence payments on that account; a cash-requirement shortfall is a missed payment or an overdraft if not caught.

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
AP_INVOICES_ALL	dimension	dimension
CE_BANK_ACCOUNTS	dimension	dimension
Due 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.

Payables 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
AP_PAYMENT_SCHEDULES_ALL	21	2
AP_INVOICES_ALL	63	15
CE_BANK_ACCOUNTS	9	12

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 The seeded forecast is a fixed horizon; treasury wants a rolling forecast with discount-optimization and bank-account grouping. Irvine rebuilds these on your data.