PRUDENTIALCOMPANYPOSITION

The prudential position of each company as at the datetime of a specific prudential run

Column Schema

COMPANY_ID

The company identifier

SQL Type: VARCHAR(20) Polars Type: pl.Categorical

This column is mandatory, and a primary key.

PRUDENTIAL_DATE

The prudential date

Warning

Despite what the name suggests, this is a datetime, not a date.

SQL Type: DATE Polars Type: pl.Datetime()

This column is mandatory, and a primary key.

Example: 2026/01/20 00:05:00

RUNNO

The run number for the prudential date

SQL Type: NUMBER(3) Polars Type: pl.UInt16

This column is mandatory, and a primary key.

CREDIT_SUPPORT

The Credit Support of the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

CURRENT_AMOUNT_BALANCE

The balance of the company for all unpaid billing weeks at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

DEFAULT_BALANCE

The balance of all defaults for the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

EARLY_PAYMENT_AMOUNT

The early payment amount deducted from Outstandings in the prudential run

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

EXPOST_REALLOC_BALANCE

The balance of all ex-post reallocations for the company that were calculated outside of billing runs at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

LASTCHANGED

The datetime that the record was last changed

For more information, see the dedicated documentation page.

SQL Type: DATE Polars Type: pl.Datetime()

This column is not mandatory.

Example: 2026/01/20 00:05:00

MCL

The Maximum Credit Limit of the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

OUTSTANDINGS

The total outstandings for the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

PERCENTAGE_OUTSTANDINGS

The percentage of outstandings calculated against the trading margin and prudential margin

SQL Type: NUMBER(18,8) Polars Type: pl.Float64

This column is not mandatory.

PRUDENTIAL_MARGIN

The prudential margin is the current value determined by AEMO for the registered participant. It represents the buffer below the value of credit support which is used to set the trading limit

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

SECURITY_DEPOSIT_BALANCE

The balance of all active security deposits at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

SECURITY_DEPOSIT_OFFSET

The sum of all active security deposit application amounts at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

SECURITY_DEPOSIT_PROVISION

The sum of all active security deposit provision amounts at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

TRADING_LIMIT

The Trading Limit of the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

TRADING_MARGIN

The trading margin for the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

TYPICAL_ACCRUAL

The typical accrual for the company at the time of the prudential run

SQL Type: NUMBER(16,6) Polars Type: pl.Float64

This column is not mandatory.

New Data Timing

Each prudential run

Code Examples

Polars

Casting is enums, categoricals etc is not essential, but may speed up parsing. Swapping int for pl.UInt16, pl.Int32 would also speed up parsing. However some of the datatypes are inferred, so they may be wrong.

This code deduplicates for you. Deduplication is normally only required across multiple months.

This code assumes that all columns are present, which may not be true for older files.

import polars as pl
import polars.selectors as cs

# e.g. "2029/03/15 00:05:00"
dt_s_fmt = "%Y/%m/%d %H:%M:%S"

csv_paths = ["SOMEFILE.CSV", "OTHERFILE.CSV"]

lf = (
    pl.concat(
        [
            pl.scan_csv(
                csv_path,  # must be unzipped beforehand
                skip_rows=1,  # skip the header
                infer_schema=False,  # much faster
            )
            .filter(cs.by_index(0) == "D")  # drop the footer
            .select(~cs.by_index(range(4)))  # drop metadata columns
            for csv_path in csv_paths
        ],
        how="diagonal_relaxed",
    )
    .with_columns(
        pl.col("PRUDENTIAL_DATE", "LASTCHANGED").str.strptime(pl.Datetime, dt_s_fmt),
    )
    .cast(
        {
            "COMPANY_ID": pl.Categorical,
            "RUNNO": int,  # or pl.UInt16
            "CREDIT_SUPPORT": pl.Float64,
            "CURRENT_AMOUNT_BALANCE": pl.Float64,
            "DEFAULT_BALANCE": pl.Float64,
            "EARLY_PAYMENT_AMOUNT": pl.Float64,
            "EXPOST_REALLOC_BALANCE": pl.Float64,
            "MCL": pl.Float64,
            "OUTSTANDINGS": pl.Float64,
            "PERCENTAGE_OUTSTANDINGS": pl.Float64,
            "PRUDENTIAL_MARGIN": pl.Float64,
            "SECURITY_DEPOSIT_BALANCE": pl.Float64,
            "SECURITY_DEPOSIT_OFFSET": pl.Float64,
            "SECURITY_DEPOSIT_PROVISION": pl.Float64,
            "TRADING_LIMIT": pl.Float64,
            "TRADING_MARGIN": pl.Float64,
            "TYPICAL_ACCRUAL": pl.Float64,
        }
    )
    # Deduplicate
    # We want one row per ['COMPANY_ID', 'PRUDENTIAL_DATE', 'RUNNO']
    # Tie-breaker: greatest value of ['LASTCHANGED']
    .sort(["LASTCHANGED"], descending=False)
    .unique(subset=["COMPANY_ID", "PRUDENTIAL_DATE", "RUNNO"], keep="last")
)

Nemosis

This table is not yet available in Nemosis.

Availability

Visibility: Private

This table is not available in the public monthly MMSDM archive. Is is only available to registered market participants over FTP inside a VPN.

Deduplication and PDR Loader Configuration

The primary keys are:

• COMPANY_ID

• PRUDENTIAL_DATE

• RUNNO

The transaction type is "insert", which means that you will usually not see duplicate data. If you do, you can deduplicate based on the primary keys, without sorting first. Rows from different files with the same primary keys should have the same values.

PDR Loader configuration is:

Report Name	Report Subtype	Version
PRUDENTIAL	COMPANY_POSITION	1

This means that the CSV files start with metadata columns:

I,PRUDENTIAL,COMPANY_POSITION,1,...
D,PRUDENTIAL,COMPANY_POSITION,1,...

Indexes

• LASTCHANGED

Links

This page as JSON (schema documented here, but may change)

Download a JSON Schema specification for this table.

Official AEMO schema documentation

Other Information

Package: PRUDENTIALS

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