Category: equipment finance

Friday April 21 2017, Daily News Digest

mobile payments

News Comments Today’s main news: Wealthfront to start lending money. Orange,telecom and ISP company, is launching a bank. Avant files new ABS-15G form with SEC. RateSetter investors have lent 400M GBP to SMBs in UK.  Yirendai makes progress with ABS loan structure. Today’s main analysis: Alipay, WeChat processed $3T in 2016, 10x the volume of Paypal. Today’s thought-provoking articles: […]

mobile payments

News Comments

United States

  • Wealthfront to lend money. GP:”A very interesting move. SoFi is moving from lending to wealth management. Wealthfront from wealth management to lending. The vision is likely to be a single point of contact for all financial needs of the population segment which prefers to interact digitally with their financial institutions. Other potential services that could be added : life insurances ( SoFi has it), other insurance (nobody has it to my knowledge), payments (combine Paypal and your accounts), checking or cash management, savings, mortgages (SoFi has it again), credit cards for payments (UpLend has it for example for non primes), etc. The opportunities in fintech/online lending are still immense. ” AT: “Personally, I’ve never understood the concept of borrowing your own money, but there is a market for it, I suppose. Life insurance policies and retirement accounts can do it, so why not robo-advisors?”
  • Three steps lenders can take to mitigate synthetic ID fraud. GP:”A must read especially for new lenders. Fraud rings tend to attack new lenders first and the most”. AT: “This may very well be the biggest threat to the online lending industry. I have confidence that some very smart people will figure out how to defeat it. My crystal ball says it will likely be a machine learning algorithm that does the trick.”
  • Avant Loans Funding Trust 2017-A. GP:” ABS market continues to be healthy and growing.”
  • Key trends in equipment finance. GP:” Supply chain financing is relatively untouched and I think a great opportunity for digital lenders.”
  • Yieldstreet surpasses $100M loans funded in less than 8 quarters. GP:”Congratulations.” AT: “Great achievement. Congratulations.”
  • Americans may not know which real estate investment types have performed best. AT: “The general population probably doesn’t know, but I would hope that real estate investors know.”
  • Brelion acquires PeerRealty. GP:” A real estate tech company acquiring a real estate crowd funding company, a very interesting move. Not sure if the acquisition was for cash or just a token acquisition.
  • Harvard recommends consumer finance policy overhaul. AT: “When you have a paradigm shift in technology and business practices, a new look at regulation is necessary.”
  • 4 Fintech tools coming out of New York Tech Day. GP:”Very interesting innovation.” AT: “I like the concept of a kid’s bank.”
  • eOriginal names Brian Maddocks CEO.
  • Trust Stamp invited to Money 20/20 Startup Challenge.

United Kingdom

European Union

  • Orange is launching a bank. GP:”This is a very interesting move for a large company. GE and other large companies have and have had banks to help in their b2b sales of equipment usually. I am not aware of many B2C companies with small ticket items ( phones, phone bills, ISP, etc…) who offers a bank. I do think that they can leverage the data they have , brand, customer reach and much more. Imagine if each Orange cell phone cutomer receives pre-approved offers underwritten by the data from their bill payment history, their phone usage and their meta data…”

International

China

Canada

News Summary

United States

Robo-Adviser Wants to Lend You Money, Not Just Manage It (Bloomberg), Rated: AAA

Wealthfront Inc. said in a blog post Wednesday that it will offer loans, calling the move a first among robo-advisers, which are known for wealth management using automated investing platforms. By providing clearing and custody services with RBC Capital Markets LLC, clients with at least $100,000 in a taxable account can take out loans of as much as 30 percent of their account value, using their portfolios as collateral.

To get a loan, Wealthfront’s clients must meet the balance requirement in a taxable account, which eliminates the majority of its customers. The credit program could introduce more risk for the firm, according to George Pearkes, an analyst at Bespoke Investment Group LLC.

Other robo-advisers have looked into lending as well, but decided to focus on different services first.

Three Steps Your Lending Operation Should Be Taking to Mitigate Synthetic Identity Fraud (Biz Journals), Rated: AAA

Synthetic identity fraud is emerging as a key migration point in the post-EMV era, as criminals refocus on application fraud and exploit easy access to sensitive consumer data.

At an alarming rate, fraudsters are using that data to create fake personas – hybrids of stolen and fabricated personal information – and open new lines of credit. In fact, the share of financial losses stemming from application fraud, which includes the creation of synthetic identities, grew by 42% in the fourth quarter of 2016, according to ACG data. Fraudsters’ migration to application fraud is particularly impactful because perpetrators behave like true customers for months or even years before “cashing out,” leaving lenders with massive losses and little recourse for collection and recovery. To make matters worse, a single fraudster can cultivate tens or even hundreds of high-value accounts, greatly increasing financial exposure.

The lending community is mobilizing against synthetics. But a series of obstacles stand in the way: With no true customer, fictitious accounts can be virtually impossible to pinpoint; conventional countermeasures are ineffective; and reporting is underdeveloped, obscuring the true scope of the problem.

A potential solution – cross-checking applicants’ information against Social Security Administration (SSA) records – is out of the industry’s reach, at least for now. The SSA’s existing verification service requires the written consent of the SSN holder, an impractical condition when dealing with synthetic identities. Regulatory reform to open up SSA records, either to lenders or the credit reporting agencies (CRAs), is moving slowly, and there’s no guarantee it will make the legislative agenda.

“SSA validation is considered the holy grail,” said Ira Goldman, Director of ACG’s Synthetic Identity Fraud Working Group, “but it could take years to orchestrate. In the meantime, the industry needs to find other solutions to mitigate mounting losses.”

Without collaboration with peer institutions, mitigating systemic fraud at this scale is virtually impossible. The good news is that the lending community is banding together to find solutions, as it has with more traditional fraud types. In March, ACG’s Synthetic Identity Fraud Working Group held its second meeting to promote industry collaboration on the issue. The introductory sessions have brought together fraud prevention managers and government relations personnel from more than 20 leading credit card lenders, along with payment network risk executives, the national credit reporting agencies, and industry trade associations.

Here are three risk mitigation strategies from the session you can apply to your lending operation:

1.   Strengthen Front-End Detection and Prevention

Massive credit losses aren’t the only financial risk associated with synthetic identity fraud: By the time a synthetic account defaults, the lender has invested potentially years’ worth of marketing, servicing, and other operational costs. Meanwhile, the fraudster has moved on to the next identity. While collections and fraud departments usually deal with the aftermath, lenders are increasingly looking to marketing, acquisitions, and underwriting teams as the first lines of defense.

“Risk detection is vital at each stage of the account lifecycle,” Goldman said, “beginning with more intelligent prospecting to avoid booking bad accounts in the first place.”

Lenders are refining their pre-screening processes to look for anomalies in applicants’ credit profiles and considering supplementing traditional, credit-based criteria with more robust data. The existence of employment information, payroll accounts, and utility records, for instance, can increase confidence that an identity is legitimate. There’s also a push to strengthen identity verification at account opening with knowledge-based authentication (KBA) and enhanced know-your-customer (KYC) techniques. Based on risk tolerance, lenders may queue suspicious applications for manual review, request additional proof-of-life documentation, or decide not to offer credit.

Lenders are also stepping up monitoring at the acquisition and account management stages to detect high-risk behavioral patterns. Warning signs include the velocity of applications submitted under a single name, requests to add a high number of authorized users to an account, and suspicious retail transaction patterns and money movement activity.

2.   Use Data Analytics to Learn from Synthetic Accounts

While synthetic identity fraud is not a new phenomenon, lenders are still developing and refining data-centric identification strategies. Collections and fraud departments are turning to reverse engineering – analyzing confirmed bad accounts to determine how synthetics are constructed and to identify behavioral patterns that signal malicious activity. This postmortem analysis can shed light on attributes lenders can use in fraud modeling and portfolio scoring to strengthen detection. It can also uncover a wealth of data elements – identity, location, and device information – that can be shared with front-end teams for use in pre-screening (a bad IP address, for instance, may be linked with multiple fictitious identities).

3.   Enrich Reporting and Information Sharing

With more robust internal reporting in place, the next logical step is to share information on bad accounts. In the near term, lenders should document known or suspected synthetic identities and report them to law enforcement and the CRAs, which can use the data to cleanse the ecosystem of known synthetics and investigate fraud rings.

“For lenders, there’s mutual benefit in removing bad accounts from the system,” Goldman said. “Information sharing is key.”

In the long term, fraud prevention managers envision a consortium model housing bad account data across industries, from banking to telecommunications, that lenders can use to cross-check applicants. This type of widespread data sharing, which ACG is working with charter members to develop, will require unprecedented collaboration across the industry and with external stakeholders.

Avant Loans Funding Trust 2017-A (SEC), Rated: AAA

We have performed the procedures described below, which were agreed to by Avant, Inc. (the “Company”) and J.P. Morgan Securities LLC, Credit Suisse Securities (USA) LLC and Morgan Stanley & Co. LLC (collectively, the “Other Specified Parties” and, together with the Company, the “Specified Parties”) related to their evaluation of certain information with respect to a portfolio of unsecured consumer loans in conjunction with the proposed offering of Avant Loans Funding Trust 2017-A, Asset Backed Notes.

On April 14, 2017, representatives of the Company provided us with a computer-generated data file and related record layout containing data, as represented to us by the Company, as of the close of business April 13, 2017, with respect to 41,250 unsecured consumer loans (the “Initial Loan File”). At the Company’s instruction, we randomly selected 200 unsecured consumer loans from the Initial Loan File (the “Sample Loans”).

Further, on April 18, 2017, representatives of the Company provided us with a with a supplemental data file containing, as represented to us by the Company, the “representative mix indicator” and the “payment to discretionary income (PTDI (Looker)) percentage” for each of the Sample Loans (the “Supplemental Loan File”). We were instructed, by representatives of the Company, to append the Initial Loan File with the information set forth on the Supplemental Loan File. The Initial Loan File, as adjusted, is herein referred to as the “Statistical Loan File.”

From EX-99.1.

Key Trends in Equipment Finance – by the Alta Group’s Patricia Voorhees (LendIt), Rated: A