Zest AI

INFOGRAPHIC: a visual explanation of why it's time to automate credit decisions. Check it out > https://zest.ai/resources/automate-credit-decisioning-infographic

The U.S. is still struggling with COVID and the lending repercussions of the CARES Act are still pending. In these linked workshops, we talk about what lenders can do today to improve current portfolio health and options you can take to quickly and fairly adjust for the future.

zest.ai It’s hard to know how to respond in today’s economic uncertainty so we’ve designed a series of 30 minute workshops taught by subject matter experts to help guide you through the uncertainty. Join us as we equip you with the tools to weather any storm.

First, don't panic. Second, contact your lender.

Coronavirus Pandemic: What Should I Do if I Can't Make My Car Payment? | U.S. News & World Report We will discuss specific steps you can take if you are in danger of missing a payment due to the coronavirus.

Here are some predictions we've got for how AI is going to change and improve lending and fintech in 2020. Worked on this with Forbes contributor Louis Columbus. Let us know what you think!

10 Ways AI Is Going To Improve Fintech In 2020 AI & machine learning will improve Fintech in 2020 by increasing the accuracy and personalization of payment, lending, and insurance services while also helping to discover new borrower pools.

If 2019 was the year AI went from idea to reality for many lenders, 2020 is going to be the year AI becomes a must-have. A November survey of 1,500 bank executives by Accenture found that 72% say their companies risk going out of business in five years if they don’t scale AI. An even greater percentage say they won’t achieve their growth objectives without more AI. So as financial institutions hit the gas pedal on AI tools like machine learning (ML) here are four trends to watch for in the coming year.

Zest's 2020 Predictions For AI In Credit And Lending 2020 will be the year machine learning becomes essential in lending, and smaller lenders and credit unions will get on board to challenge the big banks.

Credit unions, which pride themselves on member service and human touch, are recognizing the potential impact of AI. But the key to making the trend stick, especially in the current climate, is fairness testing – and it’s well within the industry’s grasp. Our CTO's take from Credit Union Times

Fair Is Fair: How Credit Unions Can Unbias AI | Credit Union Times Trust in AI will be hard-won, but we must develop and adopt the tools to make it safe to use.

Research shows that Americans want their financial institutions to use more information to produce fairer outcomes — but they want it used responsibly. AI can do all of this — but only with the right checks and balances in place. We believe that fair AI in financial services is not only possible but currently available. It’s now on the financial industry to ensure the algorithms they use are fair.

There’s A Fix To The Problem Of Biased Algorithms in Lending Discriminatory algorithms are used throughout consumer lending. Regulators are taking note. The good news for financial institutions: it pays to be fair.

The 4 Machine Learning Myths, demystified. These are the reasons why adopting machine learning is easier than you think: https://www.zest.ai/four-reasons-why-adopting-ml-is-easier-than-you-think?utm_source=facebook&utm_medium=organic&utm_campaign=social

Lenders who use AI and machine learning can use more data and valuable trended data to paint a better picture of a borrower's ability and willingness to repay their loan. This helps get more deserving borrowers an affordable auto loan, credit card, or mortgage -- borrowers such as millennials and immigrants with a short credit history or minority homebuyers who have traditionally been shut out of credit opportunities. Check out Zest executive Kareem Saleh talking to the Mortgage News Network about how Zest AI's ML software is expanding opportunities for home buyers.

Using AI to Improve the Mortgage Process Zest AI’s Kareem Saleh shares how this industry can go from 14 days to 500 milliseconds from app to close (not including regulatory restrictions). But wait, ...

Synthetic fraud occurs when a scamster combines a real identity with fake data to rip off banks and lenders. Big banks are starting to get their arms around the problem, but smaller lenders and credit unions are still at a high risk. Here's Zest's CTO Jay Budzik on how AI and machine learning can help detect and fight synthetic fraud.

Why Fake Customers Are a Real Problem for Lenders | Credit Union Times Credit unions are still at a high risk of being targeted by synthetic fraudsters, but AI and machine learning can help.