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

The Intersection of Technology & Consumer Credit – John Scully

John Sculley is the Vice Chairman to Lantern Credit, where he joined the Board of Managers in August 2015. Mr. Sculley served as chairman, CEO and CTO during a decade-long career at Apple Computer, Inc., following his tenure as the youngest president of the Pepsi-Cola Company. Most recently, he has founded several companies including Obi Worldphone, a Silicon Valley design-led company that markets high-quality smartphones at affordable price points. Additionally, Mr. Sculley is a founder of Zeta Interactive, one of the largest marketing cloud firms in consumer marketing-tech. He currently is an author, recognized expert and popular speaker about high-tech tools for tackling challenges such as corporate revitalization and the high cost of healthcare. Mr. Sculley received a bachelor’s degree from Brown University and an MBA from the Wharton School of the University of Pennsylvania.

Six ways Goldman Sachs’ online lender, Marcus, strives for an edge

There is a reason why they are slowly but surely going to crush it. Plain vanilla approach, no IVR, no fees, no nothing to p… you off. Sounds like a no-brainer to me, though it shouldn’t be. No wonder most of the players can’t make a profit, and that goal will remain elusive for most of them for the foreseeable future. Not for these guys though. Go Marcus!

Goldman Sachs, a recent entrant to the field, is no exception. At the LendIt conference in New York Tuesday, Harit Talwar, head of digital finance at the investment bank, explained this and other components of Goldman’s strategy for its four-month-old online lending division, Marcus.

Source: Six ways Goldman Sachs’ online lender, Marcus, strives for an edge

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

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

Marketplace Lending and the Three Bears: A FinTech Tale – Wharton FinTech – Medium

Sweet write up from a keen observer, helpful in the run up to the most important event of the year in P2P Land – the LendIt NYC conference on March 6 & 7. Yours truly will be present, with different hats and a big appetite and pipeline – so reach out to me if you want details. That said, nothing really novel here, and I would like to see more coming from out of left field, like developments in Big Data/AI/Machine Learning and its impact on the quality of underwriting; Gaming and Gamification techniques that will inevitably change the way the customer is being acquired; and what startup activity is interesting enough to upset an industry that is becoming a bit … stale? 

After a career trading student loans at Deutsche Bank, I had arrived at a pivotal moment in my life. I was shopping for my own loan, which…

Source: Marketplace Lending and the Three Bears: A FinTech Tale – Wharton FinTech – Medium

 

Is AI making credit scores better, or more confusing?

Most interesting analysis on developments in the AI and Machine Learning area for credit. Interesting also to see that a company like CrowdProcess has been able to tackle the exact 2 counter arguments mentioned in the American Banker article. To be continued therefore.

The cons of AI-enhanced credit scores include the risk that the full underwriting process will be hidden from consumers and that the practice would raise transparency questions among regulators. Last month, the Consumer Financial Protection Bureau imposed $23 million in fines to TransUnion and Equifax, noting they claim banks use their scores to determine creditworthiness, when that isn’t always the case.

Source: Is AI making credit scores better, or more confusing?