Retrieve a complete view of users’ liabilities with the new Liabilities Endpoint

We’ve released our Liabilities endpoint, allowing you to retrieve a complete and real-time view of a user’s liabilities alongside their cashflows. This view allows you to gauge their ability to handle debt.

To date, there has been no single source of truth to understand a complete and up-to-date picture of a user’s debts, income, and expenses. This data is fragmented across many sources including:

  • Bank transaction data, which contains real-time loan payment information, but not details about the loan itself such as remaining balance and APRs
  • Credit reports, which contain details about a loan, but they often contain inaccuracies and errors, data discrepancies across bureaus, and can be up to 90 days outdated
Pave’s Liabilities endpoint ingests data from multiple data sources to solve this problem including:
  • Bank transactions from any source, including core banking systems and bank aggregators
  • Credit reports from any credit bureau
  • Debt aggregator APIs such as Method
and returns a unified list containing a complete, accurate, and up-to-date view of a user’s liabilities.

Why this matters

  • When making lending decisions, it’s crucial to have up-to-date information to drive accurate decision-making.
  • However, lenders don’t currently have an easy way to get a real-time picture of a borrower’s true affordability. Credit reports are often incomplete, inaccurate, or delayed by up to 90 days.
  • Lenders need a way to assess real-time risk and affordability based on recent loan payments, delinquencies, and new liabilities that haven’t yet surfaced in credit reports.
  • Building interaction variables between liabilities sources allows lenders to settle discrepancies across data.
  • We’re creating a single source of truth across all of a user’s liabilities, loan information, and repayment behavior to better understand their affordability.

Additionally, our new Liabilities Dashboard allows you to forecast debt payoff scenarios in one clean UI.

Use Cases

  • Dynamically adjust credit limits: Increase/decrease credit limits for new and existing users by leveraging real-time affordability signals.   
  • Debt consolidation: Efficiently model different consolidation scenarios to offer users payoff options.
  • Personalize refinancing offers: Monitor your users’ loan history and proactively offer loan refinancing options.
  • Cash Flow Underwriting: Drive lift in your credit and fraud risk models.
  • Personalize debt management experiences: Allow your users to see all of their loans in one place. Recommend optimal debt payoff plans based on their cash flows and interest rates.
  • Manage overdraft risk: Verify upcoming loan due dates against the user’s account balance to anticipate potential overdrafts or ACH returns.

Here are some FAQs to get you started.

What data sources do I need to connect to see a user’s liabilities?

We recommend connecting a user’s bank transactions via aggregators like Plaid and MX as well as liabilities data via APIs like Method to fully benefit from the liabilities endpoint, since it unifies both sources. 

Below are examples of data sources that are currently live:

Bank transactions

  • Plaid
  • MX
  • Finicity 
  • Bond
  • Corecard
  • Ocrolus
  • Stripe
  • Synapse
  • Unit
  • Yodlee
  • Galileo
  • Lithic


  • Method
  • Payitoff (upcoming)
  • Rightfoot (upcoming)
  • Plaid Liabilities (upcoming)
  • Credit Reports (upcoming)

What kind of liabilities do you surface?

We surface the following liabilities:

  • Credit Card
  • Student Loan
  • Mortgage
  • Personal Loan
  • Cash Advance
  • Earned Wage Advance
  • BNPL
  • Loan
  • Auto Loan
  • Title Loan
  • Credit Card Cash Advance
  • Debt Collection
  • Payday Loan


You can find the documentation here –