July 27, 2021
The universe is always sending us gifts, all we have to do is open them. ~ Di Princell
Artificial Intelligence (AI) may well be the supportive superhero for credit decisioning in the current decade: slaying machine-learning systems, disrupting financial services, fighting against biased algorithms, demanding more accurate predictions, and destroying the way credit risk is measured. Combining AI with financial data creates knowledge out of confusion and sees into the future: changing status quo, paving the way for innovation in the financial arena, and tearing down closed doors to credit.
The RIBBIT.ai team combines behavioral analytics with bank and payment data to generate smarter decisioning for consumer finance providers – lending, credit cards, buy now pay later. RIBBIT.ai applies AI to bank transaction data to examine the behavior that reflects the way consumers manage their bank accounts. RIBBIT.ai’s data scientists curate transactional bank data to more accurately understand the ability to afford a financial product or service.
Historically, the financial world has excluded a large segment of the population deemed not worthy of credit, built on biased algorithms and analytics from outdated machines. The revolution has arrived; the myopic, outdated, credit structure that the bureaus have built is crumbling. Adding AI to the credit risk formula creates diverse loan opportunities for Fintechs and for the underserved so that accessibility and fairness can thrive. Thousands, not the typical hundreds of data points, relating to a customer’s financial behavior will be analyzed by RIBBIT.ai’s data scientists; no longer will credit worthiness be underestimated, opening doors to a myriad of successful loans.
According to Research Gate, “about one-third of companies expect 51% to 75% of their workloads to be supported by AI technologies in five years’ time.” RIBBIT.ai uses AI as a deeper learning vehicle to create a more informed and customized product by constantly manipulating, changing, and improving data. Understanding the shifting nature of the world, AI doesn’t accept static measurements, “one for all, all for one.” Credit scores encompass static consumer information that often doesn’t reflect present purchasing patterns, a definite gap in assessing risk.
Employing artificial intelligence, RIBBIT.ai’s team analyzes mega amounts of data that prompts software to create incessant patterns and features resulting in deep insights, connections, relationships, and intelligent meaning to the data. Predicting the relevancy of information is paramount in RIBBIT.ai’s new Bank Insights analysis, what really matters, what doesn’t and how do we use it to make the outcome smarter and more dependable for lenders and consumers. Evaluating payment behavior over a more appropriate and insightful period is at the core of RIBBIT.ai’s Bank Insights, painting a relevant picture of consumer’s fiscal propensities in real-time.
Shawn Princell, CEO of RIBBIT.ai, comments “It’s exciting to be a long-awaited disruptor in the lending space relying heavily on the powers of AI because it allows us to remain adaptable to the relentless changes and improvements in the Fintech world. Our team of data scientists is creating opportunities for everyday people who need and deserve loans based on a much broader picture of their abilities to pay them back.”
Stay tuned . . .
OXFORD, Ohio, April 12, 2022 /PRNewswire/ — Today, RIBBIT Inc. announced the appointment of Greg Rable to the RIBBIT Board of Directors. As the former Founder/CEO of FactorTrust, since acquired by TransUnion in 2017, Greg brings over 25 years of management and strategy experience, combined with a history of building successful fintech and alternative data businesses for the consumer finance space. In his role, Mr. Rable is helping guide the RIBBIT leadership team and promote the growth of bank behavior data as a powerful and necessary predictive data solution.
Financial inclusion matters not only because it promotes growth, but because it helps ensure prosperity ~ Sri Mulyani Indrawati
How arbitrary are the words ‘financial inclusion’; who’s in, who’s out and why is it so unfair? If a consumer is ‘in,’ there are financial opportunities for building a better life. If a person is ‘out,’ good luck with climbing out of a deep money pit. Today’s financial institutions think they are building a more inclusive process. However, many are still using information reflective of historical bias so if it didn’t work then, it ‘ain’t gonna work now’.
When a man gives you a rose, what you see may not be what he intends~ Patrick Rothfuss
Assessing information is the foundation of most of life’s important decisions. Mistakes are made when the data is unavailable, unclear, inaccurate, insufficient, immaterial, or unjust. How many people have suffered throughout history by poor decision-making? Like it or not, today’s world is data driven, hopefully an information mecca for making insightful, educated, proven and unbiased decisions. However, data is just that, information on a page, it becomes meaningful only when it is wisely analyzed and interpreted.