> ## Documentation Index > Fetch the complete documentation index at: https://docs.methodfi.com/llms.txt > Use this file to discover all available pages before exploring further. # Portfolio Intelligence > Continuously monitor a borrower's liability profile after origination — balance trends, utilization shifts, and delinquency signals delivered via attributes and webhooks. Portfolio Intelligence (PI) gives lenders a continuous, real-time view of a borrower's full liability profile after origination. When you enroll an Entity in Portfolio Intelligence, Method directly pulls data from the entity's linked financial institutions and makes the full attribute set available — both at the entity level (aggregated across all accounts) and at the individual account level. This is distinct from on-demand attribute pulls. PI enrollment establishes an ongoing relationship: as balances change, payments post, and utilization shifts, those signals are captured and surfaced through the [Attributes](/2026-03-30/guides/additional-products/attributes) endpoint without requiring re-enrollment or repeat triggering. Portfolio Intelligence is a separately enabled product. Contact your Method CSM to enable `portfolio_intelligence` on your environment. ## How It Works Enrolling an entity in Portfolio Intelligence is a single API call: subscribe the entity to the `attribute` subscription and pass the `portfolio_intelligence` bundle name. The bundle expands to the full Portfolio Intelligence attribute set on the server — you don't need to list each attribute individually. Once enrolled, all accounts associated with that entity become eligible for attribute generation, so you don't need to enroll accounts separately. ```bash theme={null} curl https://production.methodfi.com/entities/ent_qKNBB68bfHGNA/subscriptions \ -X POST \ -H "Method-Version: 2026-03-30" \ -H "Authorization: Bearer sk_WyZEWVfTcH7GqmPzUPk65Vjc" \ -H "Content-Type: application/json" \ -d '{ "enroll": "attribute", "payload": { "attributes": { "bundles": ["portfolio_intelligence"] } } }' ``` For the full list of attributes the bundle expands to, see [Portfolio Intelligence](/2026-03-30/reference/entities/attributes/overview#portfolio-intelligence) in the reference. To enroll in the bundle plus additional individual attributes, combine `bundles` with `requested_attributes` in the same payload. ```json theme={null} { "id": "sub_Tm8qNnLx5RjWk", "name": "attribute", "status": "active", "payload": null, "latest_request_id": null, "created_at": "2026-04-09T17:00:12.218Z", "updated_at": "2026-04-09T17:00:12.218Z" } ``` Once `status` is `active`, Method begins pulling data directly from the entity's financial institutions and attribute generation begins. Entity-level attributes aggregate signals across all of the entity's accounts — a holistic view of the borrower's total debt burden, payment behavior, and utilization trajectory. As of `2026-03-30`, the Attributes endpoint is asynchronous and automatically computes all available attributes (no request body needed). Trigger a fresh computation with: ```bash theme={null} curl https://production.methodfi.com/entities/ent_qKNBB68bfHGNA/attributes \ -X POST \ -H "Method-Version: 2026-03-30" \ -H "Authorization: Bearer sk_WyZEWVfTcH7GqmPzUPk65Vjc" ``` The request returns immediately with `status: "in_progress"`: ```json theme={null} { "id": "attr_Qk9nPmRw3LjTx", "entity_id": "ent_qKNBB68bfHGNA", "status": "in_progress", "attributes": null, "error": null, "created_at": "2026-04-09T17:02:47.910Z", "updated_at": "2026-04-09T17:02:47.910Z" } ``` When processing completes, Method fires an `entity_attribute.update` webhook. Retrieve the completed attribute object via [GET /entities/\{ent\_id}/attributes/\{attr\_id}](/2026-03-30/reference/entities/attributes/retrieve). A completed response includes every attribute enrolled via `requested_attributes`. Attributes that could not be computed return `value: null` with an `error` object (e.g. `ENTITY_ATTRIBUTE_INSUFFICIENT_DATA`): ```json theme={null} { "id": "attr_Qk9nPmRw3LjTx", "entity_id": "ent_qKNBB68bfHGNA", "status": "completed", "attributes": { "revolving_credit_card_balance_total": { "value": 1420000, "error": null }, "credit_limit_total": { "value": 3800000, "error": null }, "credit_card_utilization": { "value": 37.4, "error": null }, "weighted_average_apr_credit_card": { "value": 22.1, "error": null }, "usage_pattern": { "value": "revolver", "error": null }, "next_payment_minimum_total_credit_cards": { "value": 35000, "error": null }, "payment_to_minimum_ratio_avg_credit_cards": { "value": 1.4, "error": null }, "revolving_credit_card_balance_change_30d": { "value": -185000, "error": null }, "revolving_credit_card_balance_change_60d": { "value": null, "error": { "type": "ENTITY_ATTRIBUTE_INSUFFICIENT_DATA", "sub_type": "ENTITY_ATTRIBUTE_INSUFFICIENT_DATA", "code": 27001, "message": "Insufficient data to compute this entity attribute." } }, "revolving_credit_card_utilization_trend_30d": { "value": "down", "error": null }, "revolving_credit_card_utilization_delta_30d": { "value": -1.2, "error": null }, "delinquency_flag_credit_cards": { "value": false, "error": null }, "mortgage_balance_total": { "value": 15586300, "error": null }, "installment_balance_total": { "value": 23605200, "error": null }, "overall_loan_amount_total": { "value": 32000000, "error": null }, "overall_utilization": { "value": 45.3, "error": null } }, "error": null, "created_at": "2026-04-09T17:02:47.910Z", "updated_at": "2026-04-09T17:04:35.220Z" } ``` A representative subset is shown above. Balance values are in cents; utilization is a percentage (`37.4` = 37.4%); deltas are percentage points; trends are enums (`up`, `down`, `flat`). In this example, the borrower is a revolver carrying \$14,200 in credit card debt against a \$38,000 limit — but the 30-day balance change of −\$1,850 and a declining utilization trend indicate active paydown. The `payment_to_minimum_ratio` of 1.4 confirms they are paying above the minimum, a positive behavioral signal. For drill-down analysis on a specific account, use the account-level attributes endpoint. This is useful for account-specific risk flags, targeted cross-sell logic, or when you need per-card detail rather than an aggregated entity view. Account-level attribute names are simplified (no type prefix) because the attributes returned depend on the account's liability type. ```bash theme={null} curl https://production.methodfi.com/accounts/acc_4m9amk4KFiaQX/attributes \ -X POST \ -H "Method-Version: 2026-03-30" \ -H "Authorization: Bearer sk_WyZEWVfTcH7GqmPzUPk65Vjc" ``` ```json theme={null} { "id": "acc_attr_Lp2mXwKn9RjTv", "account_id": "acc_4m9amk4KFiaQX", "status": "in_progress", "attributes": null, "error": null, "created_at": "2026-04-09T17:03:15.334Z", "updated_at": "2026-04-09T17:03:15.334Z" } ``` Method fires an `account_attribute.update` webhook on completion. Retrieve the completed object via [GET /accounts/\{acc\_id}/attributes/\{acc\_attr\_id}](/2026-03-30/reference/accounts/attributes/retrieve). For a credit card account, the response includes the full set of credit-card-eligible attributes — attributes that can't be computed (e.g. trends/deltas with insufficient history) return `value: null` with an `ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA` error: ```json theme={null} { "id": "acc_attr_Lp2mXwKn9RjTv", "account_id": "acc_4m9amk4KFiaQX", "status": "completed", "attributes": { "type": { "value": "credit_card", "error": null }, "usage_pattern": { "value": "revolver", "error": null }, "delinquency_flag": { "value": false, "error": null }, "utilization": { "value": 61, "error": null }, "utilization_trend_30d": { "value": "up", "error": null }, "utilization_trend_90d": { "value": null, "error": { "type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "sub_type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "code": 28001, "message": "Insufficient data to compute this account attribute." } }, "utilization_delta_30d": { "value": 9, "error": null }, "utilization_delta_60d": { "value": null, "error": { "type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "sub_type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "code": 28001, "message": "Insufficient data to compute this account attribute." } }, "utilization_delta_90d": { "value": null, "error": { "type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "sub_type": "ACCOUNT_ATTRIBUTE_INSUFFICIENT_DATA", "code": 28001, "message": "Insufficient data to compute this account attribute." } } }, "error": null, "created_at": "2026-04-09T17:03:15.334Z", "updated_at": "2026-04-09T17:05:10.220Z" } ``` Even if the entity's aggregate utilization looks healthy, this account is at 61% and climbing (`utilization_delta_30d` of +9 percentage points) — a risk signal that would be masked by entity-level aggregation alone. Personal loan and mortgage accounts return a different attribute set — see the [reference](/2026-03-30/reference/accounts/attributes/overview) for the per-liability-type breakdown. ## Monitoring Use Cases ### Delinquency Early Warning Portfolio Intelligence detects delinquency signals 30–45 days faster than bureau-only approaches, because direct sync reflects the account state within roughly one week of the missed payment event — before the lender reports to the bureau. Watch for: * `delinquency_flag_credit_cards` → `true` (entity) or `delinquency_flag` → `true` (account) * `revolving_credit_card_utilization_delta_30d` > +30 (30+ pp rapid accumulation) * `payment_to_minimum_ratio_avg_credit_cards` approaching 1.0 (paying only minimums) * `usage_pattern` shifting from `transactor` to `revolver` ### Credit Line Increase Eligibility A borrower demonstrating sustained paydown is a CLI candidate. Trigger a review when: * `revolving_credit_card_balance_change_90d` is negative (consistent paydown) * `revolving_credit_card_utilization_delta_90d` \< −20 (20+ pp improvement) * `credit_card_utilization` drops below your threshold (e.g., \< 30) * `payment_to_minimum_ratio_avg_credit_cards` > 2.0 ### Refinance & Consolidation Retargeting When a borrower's debt profile improves post-origination, use PI attributes to surface them for a new offer: * `weighted_average_apr_credit_card` reveals the blended rate on outstanding revolving debt * `monthly_installments_estimate_personal_loans` calculates real-dollar savings at your offered rate * `revolving_credit_card_balance_change_30d` confirms they're actively managing their debt For example, a borrower with \$18,400 in credit card debt at a weighted APR of 22.1% has a `monthly_installments_estimate` of \~\$340/month. Your 9.5% personal loan offer reduces that to \~\$190 — a \$150/month savings you can surface in a targeted campaign. ## Attribute Availability by Level Some attributes are only meaningful in aggregate and are available at the entity level only. Others can be computed per-account. | Category | Attribute | Entity | Account | | ---------------- | ---------------------------------------------- | :----: | :-----: | | Core Balances | `revolving_credit_card_balance_total` | ✓ | — | | | `personal_loan_balance_total` | ✓ | — | | | `mortgage_balance_total` | ✓ | — | | | `installment_balance_total` | ✓ | — | | | `revolving_credit_card_balance_change_30d` | ✓ | — | | | `revolving_credit_card_balance_change_60d` | ✓ | — | | | `revolving_credit_card_balance_change_90d` | ✓ | — | | Utilization | `credit_card_utilization` | ✓ | ✓ | | | `personal_loan_utilization` | ✓ | ✓ | | | `overall_utilization` | ✓ | — | | | `revolving_credit_card_utilization_trend_30d` | ✓ | ✓ | | | `revolving_credit_card_utilization_trend_90d` | ✓ | ✓ | | | `revolving_credit_card_utilization_delta_30d` | ✓ | ✓ | | | `revolving_credit_card_utilization_delta_60d` | ✓ | ✓ | | | `revolving_credit_card_utilization_delta_90d` | ✓ | ✓ | | | `overall_utilization_trend_30d` | ✓ | — | | | `overall_utilization_delta_30d` | ✓ | — | | | `credit_limit_total` | ✓ | — | | Payment Behavior | `usage_pattern` | ✓ | ✓ | | | `payment_to_minimum_ratio_avg_credit_cards` | ✓ | — | | | `next_payment_minimum_total_credit_cards` | ✓ | — | | Delinquency | `delinquency_flag_credit_cards` | ✓ | ✓ | | APR | `weighted_average_apr_credit_card` | ✓ | — | | | `weighted_average_apr_personal_loan` | ✓ | — | | | `weighted_average_apr_mortgage` | ✓ | — | | Opportunity | `monthly_installments_estimate_personal_loans` | ✓ | ✓ | Attributes marked entity-only require cross-account aggregation and cannot be computed for a single account in isolation. ## Webhooks Method fires a webhook when an Attribute request completes or updated data is available for a PI-enrolled entity or account. Use these to trigger monitoring workflows without polling. **Entity Attribute Webhook:** ```json theme={null} { "id": "whk_Rm4nPqTx8LjWv", "type": "entity_attribute.update", "path": "/entities/ent_qKNBB68bfHGNA/attributes/attr_Qk9nPmRw3LjTx" } ``` **Account Attribute Webhook:** ```json theme={null} { "id": "whk_Wn5qPmRx6KjTv", "type": "account_attribute.update", "path": "/accounts/acc_4m9amk4KFiaQX/attributes/acc_attr_Lp2mXwKn9RjTv" } ``` The `.create` variants (`entity_attribute.create`, `account_attribute.create`) fire once on initial computation, and `.update` fires thereafter whenever PI surfaces new values for a PI-enrolled entity or account. ## Putting It All Together | Monitoring goal | Endpoint | Key attributes | | ------------------------ | ------------------ | -------------------------------------------------------------------------------------------- | | Total debt exposure | Entity attributes | `revolving_credit_card_balance_total`, `installment_balance_total`, `mortgage_balance_total` | | Debt trajectory | Entity attributes | `revolving_credit_card_balance_change_30d/60d/90d` | | Utilization health | Entity + Account | `credit_card_utilization`, `revolving_credit_card_utilization_trend_30d` | | Payment behavior | Entity attributes | `usage_pattern`, `payment_to_minimum_ratio_avg_credit_cards` | | Delinquency detection | Entity + Account | `delinquency_flag_credit_cards` (entity), `delinquency_flag` (account) | | Refinance opportunity | Entity attributes | `weighted_average_apr_credit_card`, `monthly_installments_estimate_personal_loans` | | Account-level drill-down | Account attributes | Any account-eligible attribute from the table above | Full list of available attributes, how they're computed, and endpoint details. Deep dive into subscription types and webhook payloads. API reference for pulling entity-level attributes. Return to the lending use case overview.