On this page
A tidy JSON response can still describe the wrong fund, the wrong unit or an incorrectly read table. Financial report extraction needs a controlled path between the source evidence and the facts an application is allowed to use.
ILovePSX's report pipeline separates raw extraction, deterministic validation, staging, canonical matching and production promotion. Here is what those boundaries are intended to protect, which implemented checks matter, and what a developer should still verify in the returned data.
The useful part, upfront.
- AI extraction produces candidate facts; it does not directly publish them.
- Numeric parsing and canonical identity checks address different failure modes.
- Production facts retain period, source and availability context; validation is not an accuracy guarantee.
Preserve the boundary between extraction and publication#
The pipeline begins with a source document and page evidence. A transcript-based workflow produces focused profile, performance and portfolio candidates, which are merged into raw extraction. Deterministic validation then normalizes selected values and records issues before rows enter staging.
The current Phase 1 workflow first reviews page transcription and identity evidence before later extraction proceeds. An accepted transcription alone creates neither raw extracted facts nor staging or production rows. That review gate must not be presented as a completed production import.
Staging is an intermediate layer. A staged report still needs to be associated with the correct canonical fund and satisfy promotion conditions. The public API reads active promoted production facts, rather than exposing raw AI output or treating every extracted page as a verified customer result.
This separation matters when one page contains several funds or sub-funds. A correction should be traceable to its source and ownership, without promoting all of the page's candidates merely because one table looks plausible. Source evidence remains useful even when an individual candidate cannot safely become a production fact.
References: ILovePSX Fund Manager Reports API guide · ILovePSX public API reference
Validate values and labels before matching identity#
The implemented validator checks whether extracted dates and numeric fields can be interpreted, and it records field-level issues. Its checks include malformed NAV values, invalid return percentages, invalid holding percentages and suspicious rating text. Missing labels and some incomplete fields can generate warnings that preserve the need for review.
A value that parses as a number is not automatically a correct financial fact. Units and field ownership still matter. The pipeline keeps raw values and review context so an operator can investigate a candidate that does not fit the typed field. A report month without an exact NAV day should not acquire an invented day just to satisfy a date column.
These checks reduce known failure modes; they do not prove that every published row is correct. The implementation does not justify an accuracy percentage, independent audit certification or universal completeness claim. Developers should retain enough response context to validate the facts important to their own workflow.
References: ILovePSX Fund Manager Reports API guide
Two failures that a clean-looking response could conceal#
Consider a synthetic holding table with a market value of PKR 250,000,000 beside a percentage column. If extraction copies the amount into the percentage field, a simple JSON parser will accept it. The implemented holding-range check can identify an implausible typed percentage, preserve the raw candidate and leave the invalid typed value unset for correction.
Now consider a synthetic report that names 'Example Income Fund — Plan B' while the nearest registry candidate is Plan A. Normalizing punctuation may help find candidates, but it should not erase the plan distinction. Canonical matching uses more than a tidy display name, and ambiguous or conflicting identities need review rather than an arbitrary first match.
Both examples are illustrations, not claims about a particular AMC or a measured production error rate. They show why numeric validation and identity resolution need separate gates. A correct percentage attached to the wrong fund is still the wrong dataset.
The values and fund names above are synthetic. They demonstrate failure modes and do not represent a current fund holding or a production incident.
References: ILovePSX Fund Manager Reports API guide
Work through a synthetic review checklist#
The rows below are synthetic review examples, not public API approval statuses or claims about a measured production incident. The final column describes a suitable consumer or reviewer action. It does not claim that the ingestion pipeline automatically implements every check listed here.
A pair of allocation values can add to 100 while still being incomparable. For example, 60% of total assets and 40% of net assets use different bases. Likewise, a missing value stays missing even when another table totals correctly. A tidy sum should never override a conflicting denominator, unknown field or ambiguous fund identity.
| Synthetic candidate | What can go wrong | Suitable review action |
|---|---|---|
| Holding percentage: 250000000 | A PKR amount was copied into a percentage field | Preserve raw evidence; correct the field instead of clipping the number |
| Allocation A: 60% of total assets; B: 40% of net assets | The arithmetic sum is 100 but the denominators differ | Keep the bases separate; do not form one pie chart |
| minimum_initial_investment_pkr: null | A UI substitutes zero for an unknown term | Display unavailable; retain null in the dataset |
| Same-basis allocation rows: 60.00% and 39.99% | A small gap may reflect rounding or an incomplete table | Check source scope and rounding; do not silently normalize the values |
| Source says Example Income Fund — Plan B; candidate says Plan A | A similar name hides conflicting plan ownership | Resolve identity with source evidence before attaching the facts |
References: ILovePSX public API reference · ILovePSX Fund Manager Reports API guide
Match the source report to a canonical fund#
The implemented matcher first resolves the staged AMC and checks it against the source document's AMC. A mismatch cannot be fixed merely by a similar fund name. Candidate funds are then evaluated within that AMC using name variants and aliases together with available identity signals such as launch date, plan context and Shariah classification.
Matching also considers ambiguity between candidates. A high similarity score is a workflow signal rather than proof of identity, particularly when related products share much of their name. Unresolved AMC context, conflicting details or insufficient separation between candidates can send a row to review.
The customer API exposes canonical public identity, not these private candidate tables or operator controls. For your own application, use the returned fund identity and preserve source-reported labels where supplied. If those labels seem inconsistent, report the fund slug and source period rather than constructing a private replacement join based on guesses.
References: ILovePSX public API reference · ILovePSX Fund Manager Reports API guide
Inspect the provenance of promoted facts#
A complete report response keeps the report_date, data_version and public fund identity alongside profile and fund-size context. Expanded sections can include reported returns, holdings, allocations, ratings and other report facts where available. Source entries identify report fragments and can include the original document URL and page number.
A single period can be assembled from more than one report fragment. Do not assume source is one object or that every child row came from the first source entry. Preserve the source array and the report identifiers used to connect the supplied rows to their evidence.
For reproducible analysis, record the explicit report period and returned version instead of saving only 'latest.' Revisions and available history have documented operations. A later correction should not silently rewrite the assumptions of an earlier analysis without any record of which data version was used.
References: ILovePSX public API reference
Keep the consumer's checks in place#
Inspect section availability before interpreting a table. An empty returned holdings section means there are no available production holding rows in that response; it does not prove the fund holds nothing. An omitted expansion is not the same as an empty expanded section. Request include=all or the relevant focused operation before deciding that a portfolio view is unavailable.
For each fact you display, keep the fund or sub-fund scope, report period, source label and units. Preserve null values and exact decimal strings. Do not normalize allocations into a 100% chart until you have established that the rows share a denominator and represent a complete, comparable distribution.
When something looks wrong, collect the canonical slug, report date, affected field, source reference and request ID. Send those details through the support channel without your API key. Validation makes the delivery path more controlled; careful consumption and a usable correction trail make the resulting application more trustworthy.
References: ILovePSX public API reference · Authentication, scopes and request conventions
Try a complete example.
Use these fictional records to prototype a full fund view: profile, reported returns, holdings, asset and sector allocations, credit quality, fees and ratings. Every name, identifier and number is invented. This is educational mock data, with no connection to a real fund, source document or agency opinion.
The JSON mirrors the public response structure. The complete FMR example includes all supported expansions; empty arrays and nulls demonstrate valid missing-data states. Your live integration must still request the sections it needs and check the returned coverage.
Inspect the complete FMR model
{
"success": true,
"data": {
"id": "00000000-0000-4000-8000-000000000101",
"report_ids": [
"00000000-0000-4000-8000-000000000101"
],
"fund": {
"id": "00000000-0000-4000-8000-000000000201",
"slug": "example-research-fund",
"name": "Example Research Fund",
"mufap_fund_id": null,
"amc": {
"id": "00000000-0000-4000-8000-000000000301",
"slug": "example-asset-management",
"name": "Example Asset Management"
}
},
"report_date": "2026-09-30",
"currency": "PKR",
"data_version": 1,
"identity": {
"fund_name_as_reported": "Example Research Fund",
"fund_short_name_as_reported": "ERF",
"parent_fund_name_as_reported": null,
"plan_name_as_reported": null,
"fund_type_as_reported": "Open-end",
"category_as_reported": "Illustrative mixed-asset category",
"risk_profile_as_reported": "Illustrative higher-risk profile",
"is_shariah_compliant": false,
"is_plan": false,
"is_pension_scheme": false,
"is_etf": false
},
"fund_size": {
"nav_per_unit": "100.500000",
"nav_date": "2026-09-30",
"offer_price": "100.500000",
"redemption_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"net_assets_pkr": "1005000000.0000",
"fund_size_pkr": "1005000000.0000",
"fund_size_including_fof_pkr": "1005000000.0000",
"fund_size_excluding_fof_pkr": "1005000000.0000",
"amount_invested_by_fof_pkr": "0.0000",
"units_outstanding": "10000000.000000"
},
"profile": {
"launch_date": "2025-01-01",
"inception_date": "2025-01-01",
"maturity_date": null,
"benchmark": "Example composite benchmark",
"old_benchmark": null,
"new_benchmark": null,
"benchmark_effective_date": null,
"risk_of_principal_erosion": "Principal may fluctuate; synthetic disclosure.",
"pricing_mechanism": "Forward pricing — illustrative",
"dealing_days": "Monday to Friday — illustrative",
"dealing_time": "09:00 to 14:00 Pakistan time — illustrative",
"cutoff_time": "14:00 Pakistan time — illustrative",
"settlement_period": "T+2 — illustrative, not an actual dealing policy",
"minimum_initial_investment_pkr": "5000.0000",
"minimum_subsequent_investment_pkr": "1000.0000",
"minimum_redemption_pkr": "1000.0000",
"unit_classes": [
"Illustrative standard units"
],
"leverage": "None in this synthetic example"
},
"report_fragments": [
{
"id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"schema_version": "fmr_page_v3",
"data_version": 1,
"promoted_at": "2026-10-08T08:00:00Z",
"report_date": "2026-09-30",
"report_month": "September 2026",
"page_type": "FUND_REPORT",
"extraction_mode": "PROFILE_PERFORMANCE_PORTFOLIO",
"amc_name_raw": "Example Asset Management",
"fund_name_raw": "Example Research Fund",
"fund_short_name_raw": "ERF",
"parent_fund_name_raw": null,
"plan_name_raw": null,
"fund_type_raw": "Open-end",
"category_raw": "Illustrative mixed-asset category",
"risk_profile_raw": "Illustrative higher-risk profile",
"risk_of_principal_erosion_raw": "Principal may fluctuate; synthetic disclosure.",
"is_shariah_compliant": false,
"is_plan": false,
"is_pension_scheme": false,
"is_etf": false,
"launch_date": "2025-01-01",
"inception_date": "2025-01-01",
"maturity_date": null,
"benchmark_raw": "Example composite benchmark",
"old_benchmark_raw": null,
"new_benchmark_raw": null,
"benchmark_effective_date": null,
"par_value": "100.000000",
"listing_raw": null,
"leverage_raw": "None in this synthetic example",
"nav_per_unit": "100.500000",
"nav_date": "2026-09-30",
"offer_price": "100.500000",
"redemption_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"net_assets": "1005000000.0000",
"fund_size": "1005000000.0000",
"fund_size_including_fof": "1005000000.0000",
"fund_size_excluding_fof": "1005000000.0000",
"amount_invested_by_fof": "0.0000",
"units_outstanding": "10000000.000000",
"currency": "PKR",
"pricing_mechanism_raw": "Forward pricing — illustrative",
"dealing_days_raw": "Monday to Friday — illustrative",
"dealing_time_raw": "09:00 to 14:00 Pakistan time — illustrative",
"cutoff_time_raw": "14:00 Pakistan time — illustrative",
"settlement_period_raw": "T+2 — illustrative, not an actual dealing policy",
"minimum_initial_investment": "5000.0000",
"minimum_subsequent_investment": "1000.0000",
"minimum_redemption": "1000.0000",
"unit_classes": [
"Illustrative standard units"
]
}
],
"sub_funds": [],
"reported_returns": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"period_label_raw": "1 year",
"period_key": "1Y",
"fund_return_percent": "12.00000000",
"benchmark_return_percent": "10.00000000",
"peer_return_percent": null,
"return_type": "ABSOLUTE",
"is_annualized": false,
"is_since_inception": false,
"calculation_basis_raw": "Synthetic cumulative return for the stated period"
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"period_label_raw": "Month to date",
"period_key": "MTD",
"fund_return_percent": "0.50000000",
"benchmark_return_percent": "0.40000000",
"peer_return_percent": null,
"return_type": "ABSOLUTE",
"is_annualized": false,
"is_since_inception": false,
"calculation_basis_raw": "Synthetic cumulative September return"
}
],
"allocations": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Equities",
"label_normalized": null,
"percent_of_total_assets": "60.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "603000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Cash",
"label_normalized": null,
"percent_of_total_assets": "20.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "201000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 3,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Government securities",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "150750000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 4,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "ASSET_ALLOCATION",
"label_raw": "Other assets",
"label_normalized": null,
"percent_of_total_assets": "5.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "50250000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 5,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Technology",
"label_normalized": null,
"percent_of_total_assets": "25.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "251250000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 6,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Fertilizer",
"label_normalized": null,
"percent_of_total_assets": "20.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "201000000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 7,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "SECTOR_ALLOCATION",
"label_raw": "Banks",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": "150750000.0000",
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 8,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "CREDIT_QUALITY",
"label_raw": "Government securities — illustrative bucket",
"label_normalized": null,
"percent_of_total_assets": "15.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": null,
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 9,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"allocation_type": "CREDIT_QUALITY",
"label_raw": "Unrated / no rating assigned in this example",
"label_normalized": null,
"percent_of_total_assets": "85.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"amount": null,
"current_period": null,
"previous_period": null,
"change_percent": null,
"bucket_start_days": null,
"bucket_end_days": null,
"bucket_start_years": null,
"bucket_end_years": null
}
],
"holdings": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 1,
"name_raw": "Example Technology Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Technology Company",
"security_name_raw": "Example Technology Company ordinary shares",
"symbol_raw": "EXTECH",
"sector_raw": "Technology",
"percent_of_total_assets": "18.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "180900000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "1000000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 2,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 2,
"name_raw": "Example Fertilizer Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Fertilizer Company",
"security_name_raw": "Example Fertilizer Company ordinary shares",
"symbol_raw": "EXFERT",
"sector_raw": "Fertilizer",
"percent_of_total_assets": "12.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "120600000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "800000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
},
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 3,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"holding_group": "TOP_HOLDINGS",
"rank": 3,
"name_raw": "Example Banking Company",
"holding_type": "EQUITY",
"asset_class": "Equities",
"issuer_name_raw": "Example Banking Company",
"security_name_raw": "Example Banking Company ordinary shares",
"symbol_raw": "EXBANK",
"sector_raw": "Banks",
"percent_of_total_assets": "8.000000",
"percent_of_net_assets": null,
"percent_of_gross_assets": null,
"percent_held": null,
"market_value": "80400000.0000",
"value_before_provisioning": null,
"provisioning_amount": null,
"value_after_provisioning": null,
"quantity": "500000.000000",
"units": "shares",
"credit_rating": null,
"rating_agency": null,
"instrument_type_raw": "Ordinary shares",
"coupon_rate": null,
"yield_percent": null,
"ytm_percent": null,
"issue_date": null,
"maturity_date": null,
"listed_or_unlisted": "Listed — illustrative",
"secured_or_unsecured": null,
"is_shariah_compliant": null,
"is_top_holding": true,
"is_non_compliant": null
}
],
"metrics": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"metric_key": "NUMBER_OF_HOLDINGS",
"label_raw": "Illustrative number of equity holdings",
"value": "12.00000000",
"unit": "count",
"period": "September 2026",
"benchmark_value": null
}
],
"fees": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"fee_type": "TOTAL_EXPENSE_RATIO",
"label_raw": "Illustrative annualized total expense ratio",
"value_percent": "2.000000",
"value_amount": null,
"currency": "PKR",
"period": "September 2026 — annualized illustration",
"with_government_levies": true,
"government_levy_percent": null,
"secp_fee_percent": null,
"is_actual_charged": true,
"is_maximum_allowed": false
}
],
"ratings": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"rating_type": "ILLUSTRATIVE",
"rating_raw": "Illustrative rating — not an agency opinion",
"rating_agency": "Example agency (fictional)",
"rating_date": null,
"outlook_raw": null
}
],
"parties": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"role": "FUND_MANAGER",
"name_raw": "Example Research Team",
"designation_raw": "Illustrative fund-management team",
"organization_raw": "Example Asset Management"
}
],
"special_terms": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"term_type": "INVESTMENT_OBJECTIVE",
"label_raw": "Illustrative investment objective",
"value_raw": "A fictional mixed-asset portfolio used only to demonstrate the response model.",
"value_numeric": null,
"value_percent": null,
"value_amount": null,
"value_date": null,
"currency": "PKR"
}
],
"compliance": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"compliance_type": "ILLUSTRATIVE_DISCLOSURE",
"name_raw": "Synthetic compliance disclosure",
"limit_type_raw": null,
"regulatory_limit_percent": null,
"actual_exposure_percent": null,
"excess_percent": null,
"gross_assets_percent": null,
"net_assets_percent": null,
"status_raw": "Illustrative only — no regulatory assessment has been performed"
}
],
"notes": [
{
"sub_fund_key": null,
"sub_fund_name_raw": null,
"row_order": 1,
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"note_kind": "NOTE",
"section_type": "PORTFOLIO",
"note_type": "ILLUSTRATIVE",
"text": "All figures and entities are synthetic. The three reported top holdings are a partial list. Sector percentages use total assets. Credit-quality labels and rating text are not agency opinions."
}
],
"source": [
{
"report_id": "00000000-0000-4000-8000-000000000101",
"page_number": 1,
"document": null,
"promoted_at": "2026-10-08T08:00:00Z",
"data_version": 1
}
],
"sections": {
"sub_funds": {
"status": "NOT_REPORTED",
"row_count": 0
},
"reported_returns": {
"status": "AVAILABLE",
"row_count": 2
},
"allocations": {
"status": "AVAILABLE",
"row_count": 9
},
"holdings": {
"status": "AVAILABLE",
"row_count": 3
},
"metrics": {
"status": "AVAILABLE",
"row_count": 1
},
"fees": {
"status": "AVAILABLE",
"row_count": 1
},
"ratings": {
"status": "AVAILABLE",
"row_count": 1
},
"parties": {
"status": "AVAILABLE",
"row_count": 1
},
"special_terms": {
"status": "AVAILABLE",
"row_count": 1
},
"compliance": {
"status": "AVAILABLE",
"row_count": 1
},
"notes": {
"status": "AVAILABLE",
"row_count": 1
},
"source": {
"status": "AVAILABLE",
"row_count": 1
}
},
"available_expansions": [
"allocations",
"compliance",
"fees",
"holdings",
"metrics",
"notes",
"parties",
"ratings",
"reported_returns",
"source",
"special_terms",
"sub_funds"
]
},
"meta": {
"request_id": "00000000000040008000000000000401",
"generated_at": "2026-10-08T08:00:00Z",
"data_as_of": "2026-09-30",
"data_freshness_days": 8
}
}Inspect the latest NAV model
{
"success": true,
"data": [
{
"fund_id": "00000000-0000-4000-8000-000000000201",
"fund_slug": "example-research-fund",
"fund_name": "Example Research Fund",
"mufap_fund_id": null,
"nav_date": "2026-09-30",
"nav": "100.500000",
"offer_price": "100.500000",
"repurchase_price": "100.500000",
"market_price": null,
"front_end_load_pct": "0.000000",
"back_end_load_pct": "0.000000",
"contingent_load_pct": null,
"nav_change_abs": null,
"nav_change_pct": null,
"currency": "PKR"
}
],
"meta": {
"request_id": "00000000000040008000000000000402",
"generated_at": "2026-10-08T08:00:00Z",
"data_as_of": "2026-09-30",
"data_freshness_days": 8
}
}Sources & further reading
Check the published contract for current fields and limits. Source documents describe reported facts; API availability still depends on promoted production coverage.
- ILovePSX public API reference
Endpoint names and response handling follow the current public contract.
- Authentication, scopes and request conventions
- ILovePSX Fund Manager Reports API guide
Put the guide to work.
Start with the documented contract, keep your key server-side, and make dates and missing data visible in your product.
Explore structured report data