Pave maps multiple data sources to our standardized data model, so you can retrieve one unified view of the user.
Our machine learning models enrich your data, detect recurring behaviors, and predict future events.
Supercharge your decisioning with Pave’s 300+ attributes including income history and stability, rent and mortgage payments, loan payment behavior, Affordability and Risk scores, and more.
Companies of all sizes ranging from early-stage fintechs all the way to financial institutions are challenged with investing millions of dollars and ongoing software engineering, data engineering, and machine learning to:
Pave returns Attributes and Scores to help consumer fintechs and FIs manage credit risk and build personalized financial experiences.
Unlock a comprehensive view of your consumers’ financial profile to drive critical credit decisions.
Here’s an example of how transaction data can show up for one merchant.
It can show up with:
Pave ingests messy transaction data and returns:
Instead of grouping all of these transactions under a broad merchant name like “Money Lion,” Pave analyzes the description, date, amount, and other factors to accurately distinguish between MoneyLion cash advance deposits, transfers, loan payments, subscription fees, and more.
Our AI-powered data platform ingests all of your financial data sources including:
a user’s income frequency, shocks, and predicted next payroll
multiple sources to see a complete view of the user’s financial profile
into debt repayments, changes in spending behavior and financial health
Use granular insight to predict the likelihood a user can afford to repay a debt, save towards a goal, or safely spend without risking an overdraft with Pave’s AI powered data infrastructure.
In an increasingly complex credit environment, lenders need to supplement Credit Bureau data with additional borrower context. It’s been hard to see a real-time view of a borrower’s cashflows and financial situation– Pave.dev’s APIs are changing that. Pave’s models leverage a growing network of bank transaction, payroll, and credit data. Our insight into a growing dataset of over 2 million financial profiles and 4 billion transactions allows us to power insights and mitigate risk against changes to income, spending, and new debt.
Transform raw bank transactions with our Cashflow API including:
Use a growing number of signals in your models with our Attributes Store including:
Use our pre-built Scores trained on billions of labeled datapoints:
Generate attributes and scores in near-real time via our APIs and turnkey access to Pave’s secure and standardized Snowflake data warehouse. Accelerate your development from quarters to days.
Reduce the burden on your data science, data engineering, and infrastructure teams to process billions of data points in-house. Focus on proprietary data sources, models, and unique areas of value.
Leverage a growing number of Attributes and Scores including loan repayment behavior, affordability metrics, income stability, spend shocks, likelihood to repay, and more.