Nima Ghamsari, Co-Founder and CEO of Blend Labs (NYSE:BLND), presented on a sponsored panel at Digital Mortgage 2021 – a virtual conference a couple of weeks ago.  His topic “proactive finance” was timely and compelling.  What’s more, I heard him saying all the same things I’ve been saying and writing about over the last few months.  Banks and lenders must serve actual credit offers based on real data before customers have even applied for a loan or product.  It seems simple but, until now, banks and lenders have only used indicative data or plain advertising.  New product development in customer experience (CX) that enables consumers to link bank accounts into fintech platforms has launched the next phase of innovation.

Rather than relying on indications of credit worthiness or contextual data like how long the customer has held a bank balance with the bank, lenders of all shapes and sizes can now ask consumers to share direct deposit accounts and make better decisions and real credit offers directly to customers and potential customers.  This capability is what made Plaid and Finicity so successful in a relatively short amount of time.  Blend, I believe, uses Plaid to accomplish this for their lender customers.

First, consumer expectations in financial services are high.  Consumers have experienced proactive recommendations and services in other areas of their consumer lives – grocery shopping, car shopping, etc.  The expectation that your banking app can serve the same cadence is evitable.  What’s more, consumers do not want to see teaser links or teaser offers.  Consumers want to know “what does this mean for me?” Fintech must rise to meet this challenge.   

Second, cash flow data is actual liquidity data, real-time data. Banks and lenders will soon be able to leverage cash flow to unlock credit approvals.  Fintechs offering “starter” financial products such as low-limit credit cards or low dollar unsecured loans are already using income & employment data versus a traditional FICO or credit score.  Increasingly, banks, credit unions and lenders will need to start doing the same.  The upside is that the decisions may be stronger than (or as strong as) traditional models. We will not know until more data and attempts are in the market. The goal, not being change for change sake, but more contextual, behavioral data to unlock more insights about the right product fit for the right person at the right time.

Upstart, the digital AI lending platform, published “10 Bold Predictions” for 2022.  One of the industry leaders, Nathanael Tarwasokono, predicts the industry moves away from credit scores and consolidation is inevitable.  Credit score is based on historical performance but cash flow is real time.  The benefit of traditional credit score is that it has been consistent over many years.  The potential weakness is that traditional credit scores have not updated according to changes in the economy or peer groups.  Specifically, credit scores tend to overweigh debt or payment history that are more common in communities of color.  

Once credit scores began to standardize repayment history and scoring, automated underwriting software (AUS) were able to better scale. In the mortgage industry AUS is provided by Fannie Mae and Freddie Mac allowing lenders to make decisions more consistent across populations. AUS also means mortgage investors see consistency in decisions across lenders of all shapes and sizes.  AUS also helped lenders become more efficient both with initial approvals and identifying “conditions” required to finalize the approval.  The concept of AUS is active and growing in all types of credit approvals.

Credit scores, AUS, and real-time account data have set the stage for tokenization.  Once you have the ability to reduce aspects of a credit application – identity, real-time credit history, and actual income status to a verified token, we will start to see innovation more quickly than ever before.  Tokenization will be one important aspect of Proactive Finance.  Lenders can use tokens to offer better products based on better data before the consumer goes through the manual application process.  Obtaining consent UPFRONT and fintechs will be able to make recommendations, provide insights and deliver actionable decisions right to the consumer in real time, based on real data.

Proactive Finance is not without risks.  First, credit scoring was developed and is weighted based on reactive lookbacks of activity across personas who are already part of the mainstream financial services providers. Shifting to contextual data in addition to credit scoring does not automatically mean it is not without biases built into the system or technology.  We must continue to scrutinize our tools and products for potential unfair treatment of different groups.  Second, real time data might make some consumers look more risky not less. Cash flow underwriting (one potential innovation based on bank account data) could show that consumers who would be approved in the gross income standards of the traditional credit guidelines now appear to have less money or income.  It’s possible this could make things like homeownership harder to obtain.