Credit Reports to Exclude Certain Negative Information, Boosting FICO Scores.

OK – not sure about this, but it has a distinct “deja-vu” feeling in my book – and if one has been in this business as long as I have, it’s clearly not pointing to anything good here.

The decision by the three major credit-reporting firms— Equifax Inc., Experian PLC and TransUnion—could help boost credit scores for millions of U.S. consumers, but could pose risks for lenders. The reports and scores often help decide how much consumers can borrow for a new house or car as well as determine their credit-card spending limit.

The unusual move by the influential firms comes partially in response to regulatory concerns. The three reporting bureaus rarely tinker with the information that goes on credit reports and that lenders consult to gauge consumers’ ability and willingness to pay back debts.

So let me get this straight. We’re going to make it easier for people to access credit (a good thing) by artificially boosting their credit rating (a bad thing)? Reminds me of the pre-housing bust period, where everybody and his dog got approved for NINJA loans, in the name of “democratization of access to housing”, and we’ve all seen what that has brought us. We’re still digging out of that one.

Maybe useful to read the latest Orchard stats on marketplace lending charge-offs by quarter as per the article here:

Source: Credit Reports to Exclude Certain Negative Information, Boosting FICO Scores – WSJ

Is it OK for lending algorithms to favor Ivy League schools?

This article goes deeper into the subject matter, and addresses a number of issues that are important indeed. In the long run though, it’s clear that this has only one way to go, and it’s a positive story. The human factor being what it is, there is always going to be a bias. Put more machines in charge, let them learn, and we’re off to a better credit world, no doubt. 

The main mantra used to be “software is eating the world”. Mine these days and going forward is “AI and Machine Learning is eating all the rest”. TGIF – but have a good read nevertheless.

“I think a baseline question is, how much disparate impact already exists in the system?” said Paul Gu, co-founder of the online consumer lender Upstart, which includes the potential borrower’s college in its underwriting criteria. “I think we would be kidding ourselves if we thought that the traditional way of underwriting was a completely unbiased way of underwriting. If you look at credit scores by any demographic, they’re extremely uneven. If you look at credit access in America, it’s extremely uneven.”

Source: Is it OK for lending algorithms to favor Ivy League schools?

Innovation in Credit Granting With Big Data – Ash Gupta

You want to hear from the big kahuna – you got it!

All you wanted to know about Big Data, AI and Machine Learning, applied also to the un- and underbanked part of the population, call it broadening of access to credit.

“Ash Gupta is an industry leader in machine learning and big data analytics. He promotes AXP wide innovation to drive revenue growth along with best-in-class Credit and Fraud results. His responsibilities extend across all AXP businesses and geographies. He is an executive officer and reports to the company’s Chairman & CEO. Mr. Gupta’s prior roles include company’s Chief Risk officer and CEO of US banking, along with broad leadership positions in Finance and Strategic Planning. Mr. Gupta earned an MBA from Columbia University and a bachelor’s in Engineering from Indian Institute of Technology (IIT), Delhi. Currently, he serves on the boards of Encore Capital Group (NASDAQ: ECPG), Big Brothers Big Sisters of New York, and South Asian Youth Action (Advisory Board).”

 

Unstoppable Trends in Online Lending – Noah Breslow

When Noah speaks – the room gets quiet.

An early player in the industry, he’s more than ever at the forefront of what’s happening out there, and his presentation did not disappoint. Equity investors have not been happy to say the least, and it remains to be seen where we go from here.

However, they are still going strong operationally, and one would expect that at some point, things might take a turn for the better. 

“Noah Breslow has served as OnDeck’s Chief Executive Officer and Chairman of our board of directors since June 2012 and as our Chief Operating Officer from October 2011 to June 2012. Previously, Noah held many executive roles at OnDeck including Chief Product Officer (2009-2011), Senior Vice President – Products and Technology (2007-2009) and Vice President, Products and Technology. Prior to joining OnDeck, Noah was Vice President of Marketing and Product Management for Tacit Networks, Inc., a provider of wide area network optimization solutions.

Mr. Breslow holds an S.B. in Computer Science and Engineering from the Massachusetts Institute of Technology and an M.B.A. with distinction from Harvard Business School.”

 

From SoFi – with love …!

You know you’re making it Big when you’re on Mad Money with the Mad Hatter … Anyway, if there is one man that can get away with it in style it’s Mike Cagney – my favorite libertarian who’s getting us all back to basics on this quaint concept of “customer sercice” in the financial space. ‘Nuf said – just watch and enjoy and understand just why this thing is going gangbusters – and very likely to continue to do so for a very long time. It’s gonna be painful for a lot of people indeed…

Why branch bankers shouldn’t fear bots

I don’t disagree with this observation, but wanted to add a couple of thoughts here. For one, I strongly believe that over time, we’ll see a re-evaluation of the importance of people vs. machines, as we’ll try to deal with some major headwinds and other unpleasant side effects of current developments re. automation. 

More importantly, what I miss in this particular piece, is the fact that AI & Machine Learning is not only there to replace repetitive and low value add activities. It is also there to grow the business, in this case (FI’s) by pointing to opportunities to better serve the un- and underbanked population, who currently are falling through the (credit box) cracks. 

Much of the talk about artificial intelligence in banking has been about how technology can replace some functions currently performed by humans. But AI could help human bankers do their jobs more effectively by giving them quicker access to relevant information than ever before.

Source: Why branch bankers shouldn’t fear bots

CB Insights on Twitter: “Artificial intelligence has jumped the shark”

No further comment needed #CrowdProcess #James #Marketplacelendingrevolution

Management online lending risk with AI & CrowdProcess / James

Most timely update from the team at Lending Times on CrowdProcess, its flagship product “James” and its plans for US domination … guess who’s gonna lead that charge? 

James’ features include:

  • Scorecard: Traditional scorecards have been augmented with a random decision factor, gradient boosting, and neural networks.
  • Validate: It provides precautionary alerts according to the model`s metrics and access to data necessary for validation. James has an edge over other solutions in the market, which may not enable regulators to validate.
  • Deployment: James has superiority with regards to the timeline of deployment. The model can be run automatically or in conjunction with other models. So a 6-month integration time is essentially reduced to zero and the company can compare multiple models in parallel.
  • Monitoring: James monitors its own performance in real-time. The system not gives out early warnings and helps ensure data sets are used appropriately. When a material change occurs, the software is tweaked accordingly.

Source: Management online lending risk with AI | Lending Times

Take the Pokemon Go approach to bank sales

Somewhat hopeful that Gaming & Gamification within the financial services sector is finally being talked about, i.e. discussed. Meet your (future) customer where he is and spends most of his time today, and that is on his smartphone. Increasingly so. Once you realise that, you can then start looking a game mechanics, gamification, game play and other critical elements needed to develop a “buyers journey” commensurate to the times. The famous PBL approach (points, badges, leaderboards) becomes second nature, and you just may be able to take the inevitable lead in the space, and never have to look back. #marketplacelendingrevolution

It is a fallacy that customers respond only to monetary rewards. Banks should use psychological rewards to drive digital product sales just as popular mobile apps do.

Source: Take the Pokemon Go approach to bank sales

Fintech 2017 – Breaking Banks

Good to see CrowdProcess/James being featured here as well – with the following details:

“There have been big advancements in AI over just a short number years owing to better algorithms, much larger datasets for training them, cheaper and faster cloud-based infrastructure and new computing techniques like parallel computing. On the back of this, we are seeing many more AI-related fintechs entering the jams, especially compared to two years ago.

An interesting example from the UK is Crowdprocess whose product James leverages machine learning algorithms to create high-performing predictive models and scorecards for credit risk management.”

Source: Fintech 2017 – Breaking Banks