Get key insights into cashflows and liabilities with standardized tables.
Pave unifies multiple data sources including bank transactions, credit reports, loan performance data, and more – streamlining cashflow and liability analysis without the need for complex ETL pipelines.
Run unlimited SQL queries to uncover insights across your userbase without having to clean, categorize, or unify your data.
Tables are refreshed every 24 hours, allowing you to obtain the most up-to-date insights.
Analyze financial data effortlessly within Snowflake.
Access pre-built Segments built on our models that group users by financial behavior into Segments like Auto Owner and Student Loan Holder.
Check out this demo of the Segments Table.
Retrieve a standardized view of all user transactions, complete with clean and normalized merchant names, granular tags, categorization, and detection of recurring transactions.
Backtest 1500+ Cashflow Attributes to identify opportunities to reduce delinquencies, enhance credit quality, and more.
Leverage Pave’s Cashflow Scores trained on millions of defaults in order to identify users who could have been accepted or declined.
We’re actively expanding our offerings based on your feedback.
Score users for cash advances.
Score applicants for small dollar loans.
Score applicants for personal loans.
Set dynamic credit limits for credit and charge cards.
Use our Scores trained on billions of labeled datapoints:
Forecast user cashflows including:
Check out our use cases for cash advance, credit and charge cards, small dollar loans, personal loans, and more.
