AUM Data Dictionary
API reference:
client.aum
Five sub-modules — each section below corresponds to one AMFI AUM page.
1. Average AUM
financial_years() — Available financial years
| Field | Type | Example | Description |
|---|---|---|---|
id |
int |
1 |
Use as fy_id in periods() and data calls |
financial_year |
str |
"April 2025 - March 2026" |
Human-readable label |
periods() — Quarters within a financial year
| Field | Type | Example | Description |
|---|---|---|---|
financial_year |
str |
"April 2025 - March 2026" |
Financial year label |
periods |
list |
[{...}] |
List of quarter records |
Each periods entry
| Field | Type | Example | Description |
|---|---|---|---|
id |
int |
1 |
Use as period_id in data calls |
period |
str |
"January - March 2026" |
Quarter label |
average_aum_fundwise() — Fund-wise Average AUM
One row per AMC.
| Field | Type | Example | Description |
|---|---|---|---|
Sr_No |
str |
"1" |
Serial number |
MutualFundName |
str |
"Aditya Birla Sun Life Mutual Fund" |
AMC name |
averageAUM |
dict |
{"Equity":12345.67,...} |
AUM by scheme category (₹ crore) |
average_aum_schemewise() — Scheme-wise Average AUM
| Field | Type | Example | Description |
|---|---|---|---|
Category |
str |
"Equity Scheme" |
SEBI scheme category |
Sub_Category |
str |
"Flexi Cap Fund" |
SEBI sub-category |
MF_Name |
str |
"HDFC Mutual Fund" |
AMC name (when filtered by mf_id) |
Scheme_Name |
str |
"HDFC Flexi Cap Fund - Direct - Growth" |
Scheme name |
AAUM |
str |
"28456.32" |
Average AUM for the quarter (₹ crore) |
2. AUM–AAUM Disclosure
disclosure_by_category() / disclosure_by_geography() — Quarterly disclosure
Each record provides a quarter's AUM disclosure file links.
| Field | Type | Example | Description |
|---|---|---|---|
Period |
str |
"October - December 2025" |
Quarter label |
pdfURL |
str |
"https://..." |
PDF disclosure file URL |
excelURL |
str |
"https://..." |
Excel disclosure file URL |
Download with client.publications.download_file(url) or httpx.get(url).content.
3. Age-wise / Folio Data
agewise_folio() — Flat DataFrame (as_df=True)
as_df=True flattens the nested ageWiseAUM → classifications structure.
| Column | Type | Example | Description |
|---|---|---|---|
schemeTypeName |
str |
"Open Ended" |
Scheme type (outer grouping) |
ageGroup |
str |
"18-30" |
Investor age band |
noOfFolios |
str |
"1234567" |
Number of folios in this age group |
AUM |
str |
"45678.90" |
AUM for this age group (₹ crore) |
Raw response (as_df=False) also contains investorClassification — investor type breakdown (Individuals, NRI, HUF, etc.).
4. Classified Average AUM
statewise() — State-wise AUM
| Field | Type | Example | Description |
|---|---|---|---|
State |
str |
"Maharashtra" |
State name |
B30Cities |
str |
"12345.67" |
AUM from Beyond 30 cities (₹ crore) |
T30Cities |
str |
"98765.43" |
AUM from Top 30 cities (₹ crore) |
Total |
str |
"111111.10" |
Total AUM for the state (₹ crore) |
scheme_catwise() — Scheme-category-wise AUM
| Field | Type | Example | Description |
|---|---|---|---|
Category |
str |
"Equity Scheme" |
SEBI scheme category |
T30 |
str |
"456789.12" |
Top 30 cities AUM (₹ crore) |
B30 |
str |
"23456.78" |
Beyond 30 cities AUM (₹ crore) |
Total |
str |
"480245.90" |
Total AUM (₹ crore) |
Date format: "01-mon-yyyy" — lowercase month, always day=01. E.g. "01-apr-2026".
5. Bifurcation of AUM (Direct Plan)
bifurcation() — Direct Plan AUM split
One record per date requested.
| Field | Type | Example | Description |
|---|---|---|---|
Month_Date |
str |
"31-Mar-2026" |
Month-end date |
TotalAAUMunderDirectPlan |
str |
"987654.32" |
Total Average AUM under Direct Plans (₹ crore) |
AAUMunderRegisteredAdvisers |
str |
"456789.10" |
Portion managed via SEBI-registered advisers |
AAUMunderPMS |
str |
"234567.89" |
Portion managed via Portfolio Management Services |
AAUMunderDIYclients |
str |
"296297.33" |
Portion invested directly by retail clients (DIY) |