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Introducing the NovaScore Cash Flow: the Future of Consumer Credit Risk Scores

Analyzing cash flows from income, expenses, debit transactions, and financial behaviors, the NovaScore Cash Flow provides statistically significant lift in multiple use cases and across all credit tiers

In an era characterized by shifting financial dynamics and evolving consumer behaviors, traditional credit data is increasingly unreliable in predicting risk across a broadening spectrum of borrower populations. Financial institutions and other lenders, who rely heavily on credit-data based scores, such as FICO, are too often left in the dark when making lending decisions. Credit bureau data is murkier than ever. Factors like credit builder products, soft inquiry data, government stimulus, and Buy Now, Pay Later loans are not accurately reflected in traditional credit scores. It’s understandable nearly a third of lenders think traditional credit reports don’t paint a complete picture of a consumer’s finances. 

Alternative sources of data, such as a consumer’s cash flow, offer a more up-to-date and comprehensive view of an individual’s financial health. This data completes the creditworthiness picture, revealing an individual’s ability to pay and offering lenders the ability to make smarter risk predictions and better credit decisions. Leveraging this data, cash flow underwriting is quickly evolving as a key strategy to expand credit access to more consumers without increasing risk.

As more and more lenders race to adopt cash flow underwriting, their organizations require access to these alternative data sources and new forms of risk analytics. However, most financial institutions today don’t have the infrastructure and experience to easily onboard, analyze, and incorporate consumer-permissioned alternative data into credit decisioning and underwriting processes.

Here at Nova Credit, we’ve been helping lenders unlock the advantages of alternative credit data for nearly a decade. The Nova Credit Platform created enterprise-grade alternative data infrastructure, making it easy for customers to effectively onboard and orchestrate multiple aggregated data sources, including bank transaction, payroll, and foreign credit data. And our Cash Atlas™ solution has led the way in cash flow analytics, providing lenders with proven risk attributes and consumer-permissioning workflows that help more applicants get approved. But we’re not stopping there. Today, Cash Atlas now includes the new NovaScore Cash Flow (NSCF) – an easy-to-use, FCRA-compliant credit risk score that leverages bank transaction data to assess creditworthiness.

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NovaScore Cash Flow makes it even easier for lenders to adopt cash flow underwriting. Built from 1,000+ rigorously tested attributes and accompanied by adverse action codes, NSCF resembles the traditional scores lenders already use in decisioning workflows. By tapping into a wealth of bank transaction data, NSCF assigns individuals a score ranging from 300 to 850 and can be used in conjunction with existing credit scores or when thin-file applicants lack sufficient data for a traditional credit score. NovaScore Cash Flow delivers a significant boost in predictive performance (up to 15% lift in KS on average) across the credit spectrum. 

Cash Atlas™ with NovaScore Cash Flow welcomes a new era of credit risk assessment, helping lenders expand their offerings across the credit lifecycle, expanding financial opportunity for over 100 million people in the U.S. NSCF is available now and can be used as a standalone credit risk score or to supplement a traditional credit score. NSCF deployment is compatible both as part of the Nova Credit Platform (end-to-end solution), or as a standalone analytics layer atop your in-house 1st party data or any existing 3rd party data integration. 

To start scoring with NovaScore Cash Flow, learn more at novacredit.com/novascore and connect with a representative.

Introducing the newest Cash Atlas feature: NovaScore Cash Flow (NSCF) – an easy-to-use, FCRA-compliant credit risk score that leverages bank transaction data to assess creditworthiness.