When Rules are Meant to Be Broken
Empire Startups Contributor Laura Kornhauser explores the finite art of rule breaking when it comes to financial services.
Hi there,
Throughout history, we have seen if it wasn’t for rule breakers, many pivotal aspects of our lives would not be as they are today. Some would call these rule breakers innovators, others disruptors. The difference between innovators and disruptors ultimately lies in a deep understanding of the distinction between what rules must be followed diligently as opposed to the rules that can (and should) be rewritten.
In the realm of finance, where stability and predictability are crucial, rule-breaking takes on a nuanced significance. While disruptive innovation can introduce instability, conscientious innovation and disciplined monitoring hold the potential to redefine our financial landscape for the better.
As the youngest child in my family, I was a classic example of a people pleaser in my early years. I followed the rules to get praise and some amount of attention. Then, at some point in my teenage years, I started to recognize where I could bend the rules without breaking them, but just enough to usher in incremental opportunity (and fun). In the two decades I’ve spent in finance and the work we’re doing at Stratyfy, knowing this distinction has been critical in driving the right kind of change, change that drives the industry forward while understanding the unique situation (and rules) in which our financial system (and our customers) must operate within.
To say the way lending decisions are being made is broken would be a discredit to the many years of work invested in finding the ideal balance between growth and risk management necessary to make sound lending decisions. Yet, in those years, lenders have stuck to credit policies or rules that only benefit a certain portion of consumers. With these rules providing a comfortable and familiar safety net for risks, it is understandable why it would be much easier to continue relying on the same methods to do business.
But what happens when borrower profiles change faster than that of the methodologies being used to evaluate and make decisions about those borrowers?
Fellow contributor
highlighted in his piece last fall, Trust: The Currency of the Gig Economy, that in the US alone there were an estimated 73.3 million freelancers, or 43% of the total labor force, in 2023. A structural shift towards an independent type of work and income. Another contributor, , reminded us earlier this year how small businesses have always been the backbone of the American economy. What is happening to this growing number of individuals deciding to take the plunge and work for themselves? More advanced methods for making risk based decisions are a must as lenders have struggled to adequately support these businesses with responsible and efficient lending products.Borrowers have clearly changed, but the way in which the majority of lenders make loan decisions has not.
In the example above, based on Capacity within the 5 C’s of credit, the freelancer’s varying income would likely lower their ability to get approved for a loan. So many loan decisions, particularly rejections, are made based on sharp cut-offs that fail to capture the nuances associated with the ways borrowers have changed over the past decade.
This is where AI, more specifically interpretable machine learning, has the power to unlock value for both lenders and borrowers. However, challenging ingrained beliefs and asking people to do the hardest thing –change – is always going to come with a bit of push back.
Take for example, how lending decisions are made. There has been a lot of talk of the value AI, and more specifically Machine Learning (“ML”), can bring to make lending decisions more profitable, efficient and fair. But most of this value has not been realized, particularly by community and regional banks, in part because many ML providers approached these lenders with solutions that throw away the old in favor of the new. They do not meet the lender where they are, offering trustworthy and reliable improvements over time, and instead try to break too many rules. This is not the recommended approach for inspiring change that is also safe – breaking some of the rules, but not all of them at the same time.
The other reason that ML has struggled to deliver the value promised is the fact that finance, and lending in particular, is often slow to move but fast to follow when something has been proven by the masses. This gives Financial institutions (“FIs”) the confidence, strength in numbers and social validation that is often necessary to break away from the rules of yesterday. While most FIs historically have learned to get better through “interpolation,” leading FI innovators have achieved success with “extrapolation” – taking calculated risks in developing products and decision strategies outside of their historical data and policies (aka rules).
The goal of the AI should be to augment human intelligence, not replace it, with the best solutions having the ability to learn from both data AND subject matter expertise.
“AI meets IQ”.
Beyond this overall philosophy of human + machine delivering superior results, there are specific attributes that financial institutions should prioritize when evaluating AI technology to ensure the chosen technology fits the business problem and regulatory environment at hand.
The most important ones for high stakes decisions like lending are:
(1) predictive power, in the field not just the lab,
(2) robustness,
(3) transparency, recognizing that all types of transparency are not created equally and
(4) fairness, both on an individual and group basis.
In the context of lending, #3 is particularly essential. And the right kind of transparency, interpretability, has the ability to also help drive results in 1, 2 and 4 (in addition to 3, obvi). This prioritization will allow lenders to select the right technology that follows the rules it needs to follow and breaks away from the rules that are holding lenders (and their borrowers) back.
With the only constant being change, borrowers will continue to evolve with both newer and older generations having very different financial profiles than the past. ML technology, if selected, developed and deployed properly, is positioned to completely reinvent the way lenders evaluate creditworthiness and make decisions on loans, ensuring these lenders can unlock profitable, inclusive growth and deliver for the borrowers of today and tomorrow.
–
Laura Kornhauser, Co-founder & CEO of Stratyfy, Empire Startups Contributor
Empire Startups Contributors are a community of experts providing unique perspectives and insights on the latest in FinTech. Our model is is merit-based and does not offer monetary compensation.
If your email client clips some of this newsletter, click below to see the rest.
🎨 Need some FinTech art? Say less…
Last month, the Empire FinTech Conference stages were decorated with large, art canvases painted by Jasmine Boyce – and we still have a few in the Empire office (Rise by Barclays building, floor 6!)
If any team is looking for some office art (or individual for some personal decor) you’ve come to the right place. 👇
Please either reply directly to this email or reach out to contact@empirestartups.com if interested in picking up any of the pieces above.
👩🏻💻 Find your go-to workspace with an exclusive offer from WeWork.
Drop in by the day or hour at a location near you with WeWork On Demand. Get started with 50% off your first coworking booking through June 14, 2024 using code TRYWWOD50. Terms apply.
🎟 Featured FinTech Events
NEW YORK
OTHER CITIES
VIRTUAL
🗞🎧 The latest news in FinTech.
Reads
🦄 Meet Cleo, The British Fintech Using AI To Close In On Unicorn Status | Forbes
Cleo is effectively built on the open banking revolution, which has seen American banks provide access to customers’ account data – with their permission – to third parties that can then offer other advice and services.
👀 The FDIC’s Campaign Against Fintech Companies | WSJ
With no authorization from Congress, the bank regulator tries to suppress these innovative firms.
💸 MoneyLion: On a Mission to Become the Expedia of Financial Services | PYMNTS
MoneyLion’s evolution has come at a time when the neobank model itself has been forced to change to survive, and the marketplace concept has been validated by MoneyLion’s earnings.
📈 Americans' inflation expectations are rising | Axios
When people expect higher inflation, it can be self-fulfilling — and if this reversal of progress in inflationary psychology continues, it will make Federal Reserve leaders warier of cutting interest rates.
Listens
🤔 Alex Johnson on Credit Scoring: Past, Present, and Hypothetical Future(s) | Fintech Family Hour
We bring back a fan-favorite of the show: Alex Johnson. But this time we don’t chat over Zoom, we had to do this Podcast face-to-face. Because I needed Alex to deep-dive into how the credit world works…
🗣The Fintech OG Series: Charley Ma and Reshma Sohoni | This Week in Fintech
Beyond their professional insights, both of them offered candid reflections on personal growth and where fintech is headed next. By sharing their professional achievements, key choices (going to work for a tiny company called Plaid even though many told him not to), personal setbacks and times of struggle, there's a lot of great advice for listeners, whether in fintech or not.
🚀 Featured FinTech Funding
SEED
Outpave, $1.2M (Accounting/Finance, Frisco)
Swypex, $4M (Lending, Egypt)
Plenty, $5M (Wealth Management, San Francisco)
SERIES A
Provable Markets , $8M (Capital Markets, New York)
SERIES B
Sift Healthcare, $20M (Payments/Billing, Milwaukee)
Honeycomb, $36M (InsurTech, San Francisco)
💼 Featured FinTech Jobs
New York
Sales Director , Securitize
Director, Corporate Sales , Arbol
Account Executive , Zero Hash
Senior Product Manager, Public
Remote
VP, Associate General Counsel - Litigation and Investigation , EasyKnock
Director of Customer Support , MANTL
Managing Actuary , Jetty
Senior Accountant , Botkeeper
San Francisco
Content Marketing Manager , Numeric
Customer Success Manager , Ansa
Growth Marketing Manager , TomoCredit
Associate Account Manager , Plaid