Partner Perspectives

Startup Spotlight: Pave Seeks to Remove Barriers to Accessible Lending

Startup Spotlight: Pave Seeks to Remove Barriers to Accessible Lending
Welcome to Snowflake’s Startup Spotlight, where we learn about amazing companies building their businesses on Snowflake. In this edition, Pave.dev
President and Co-Founder Ema Rouf talks about breaking down barriers to accessible credit and financial lending, how running a startup is like climbing a mountain, and how building on Snowflake gives Pave the data sharing capabilities it needs to show financial institutions a better way to identify more creditworthy borrowers.

What inspires you as a founder?

I’ve long believed technology can dismantle societal and systemic obstacles. Financial systems around the world hold many of these obstacles.
I’m inspired by the opportunity to create a more accessible and fair financial system for underserved communities, alleviating the struggle and ultimately boosting economic growth. 
The majority of Americans struggle to access fair credit—especially those who don’t fit the profile of a typical borrower. Costly credit options force them into debt cycles, and a daily struggle to meet basic needs. I believe new technologies have the power to break these barriers.
Our mission is to build a future where every person has access to equitable financial services.

How did you decide on your company’s name?

We came up with the name for Pave while hiking. Coming across a dirt path through the mountains, we reflected on how we wouldn’t have been able to walk that path if not for someone paving the road before us, and changing the path for us to be able to continue on and up.

Tell us more about the problem Pave aims to solve.

Lending in the U.S. remains vast but unchanged. Recent reports reveal that current credit models inadequately assess a borrower’s affordability. 
When we started Pave, we found that even the most innovative financial institutions (FIs) and fintechs struggled with evolving their risk models, and analytics was the primary challenge. 
Although core banking systems and bank aggregators contain valuable insights, FIs lack the infrastructure to translate this data into standardized analytics. As a result, FIs miss out on a significant opportunity to ​​expand their reach to creditworthy Americans who are overlooked by traditional models. 
Consider Susan, a recent divorceé, who has a 683 FICO score. Because she never leveraged her own credit during her marriage, she has a limited credit history and a lower credit score. Despite appearing “risky” in traditional models, Susan consistently: 
  • Earns healthy income from her nursing career
  • Maintains a healthy bank balance without fees
  • Pays all of her bills on time 
  • Invests a significant portion of her monthly income
Her cash flow suggests greater creditworthiness than her FICO score implies, and she could be an excellent customer—but only if the FI can look past the model’s initial assessment. Pave wants to help lenders distinguish between
healthy
and
risky
applicants based on their cash flow, even if both have similar FICO scores, so people like Susan can improve their lives. 

What’s the coolest thing you’re doing with data?

We’re revolutionizing lending through advanced data analytics. We seamlessly clean and merge disparate data sources, including bank transactions, payroll APIs and credit reports, into unified Snowflake tables with a standardized schema. This empowers FIs to get a 360-degree view of their customers.
Achieving this level of insight usually requires extensive resources, such as large data engineering and data science teams, complex integrations and substantial modeling efforts. Pave simplifies this process by offering ready-to-use, clean and unified analytics within the Snowflake environment.
Our analytics and scoring models are designed to uncover signals of affordability based on cash flow and traditional data, making financial services more accessible. Beyond loans, we aim to create fairer economic opportunities by leveraging data to make lending more accurate, tailored and responsive. Pave is not just transforming lending, it’s transforming lives.

How has building on Snowflake helped your team take on the challenge of improving financial institutions’ analytics?

Our customers access Pave’s analytics for training models, building dashboards, powering campaigns and so on.
This required Pave to deliver large CSV or Parquet files—a complex and insecure process as confidential data was moved in unencrypted formats across machines.
Snowflake Secure Data Sharing enables us to share Pave insights directly and securely with our customers via shared Snowflake tables. This is much more secure as the data never leaves the Snowflake platform, stays encrypted at rest, and adheres to our customers’ already-defined access control policies. This has been a win-win for both Pave and our customers.

When you implemented Snowflake, which architecture did you decide to use?

Pave is currently available as a managed SaaS application. This means that our analytics can be consumed through our API, dashboards, or a Snowflake Secure Data share. This model has yielded many success stories for Pave customers.
As we partner with more clients—especially banks and credit unions that are already in the Snowflake ecosystem—Pave plans to provide its product either as a connected app or a Snowflake Native App
. This will make it even faster and easier for our clients to benefit from Pave insights.

How does Snowflake help you collaborate with customers?

Snowflake has brought us much closer to our customers. Once we establish a data share with our customers (either a bilateral or unilateral share with Pave as the data provider), it becomes extremely easy to make data available. Getting the right data in front of our customers’ data science teams now only takes a single SQL query. Our customers get immediate value, and we benefit from their feedback to make rapid improvements. 

What’s the most valuable piece of advice you got about how to run a startup?

Our investor Sheel Mohnot always says that the strongest correlation to success for a startup is how frequently they ship. Don’t stop moving. Build and ship daily. It’s like climbing a mountain: you can see the trail right ahead of you, and maybe you can see the first peak through the fog, but you have to keep putting one foot in front of the other so you get there before you run out of water. 

Can you share a lesson you learned the hard way?

You have to build a product that gives you energy. The product you build shapes the people you attract and the culture you build. 
In previous companies, I assumed that culture and product were mutually exclusive. But if you build a product for a market you don’t like, or one that takes forever to sell, there’s nothing you can do to shape the culture of the company into what you want it to be. 
If I could go back, I would try to be more self-aware about what’s giving me the energy to keep going every day on what is likely a 10+ year journey. 

What’s on the horizon for Pave?

Over the next few years, there will be thousands of new credit solutions designed for millions of unique consumer segments. Regulatory pressures are also accelerating the need for banks to deliver fair services to traditionally underserved markets.This new era will require banks and lenders to take a different approach to analyzing credit risk and curbing delinquencies. 
Pave is helping usher in this future by creating a flexible data infrastructure to analyze consumer financial data, and to provide a comprehensive view of borrower cash flows and affordability that complements traditional credit data.

5 Key Financial Services Takeaways from Industry Day 2023

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