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Record W304629260

Online Lending Circles Hit Circuit Breaker: What Will Possible SEC Regulation Mean for P-to-P Lenders, a Rising Bank Competitor-And Potential Partner?

2008· article· en· W304629260 on OpenAlexaboutno aff
Órla O’Sullivan

Bibliographic record

VenueABA banking journal · 2008
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessCredit cardRevenueMonetary economicsFinancial systemPaymentFinanceEconomics
DOInot available

Abstract

fetched live from OpenAlex

[ILLUSTRATION OMITTED] Websites that help individuals make loans to other individuals online suddenly have been stopped their meteoric rise, calling into question whether such sites are the easy antidote to the current credit crisis. Collectively, site operators such as Prosper, Zopa, Virgin Money, GlobeFunder, and Lending Club tend to be termed for person-to-person lending. However, some reject that label, partly, it seems, to distance themselves from subprime, and now tarnish coming over the pto-p niche. Micro lending is another term for the practice, although that term has more often been used reference to loans made to the poor developing countries. We know what happened to peer-to-peer music sites, like Napster, which enjoyed explosive growth at the start of this decade: Lawmakers shut them down. While p-to-p lenders may not be facing something so drastic, April's announcement by Lending Club that it was ceasing to take lender applications pending a process to register with the appropriate securities authorities begs the question what the future of p-to-p will be. With the music sites, record companies were hemorrhaging revenues from songs that would have been sold, instead being shared for free online. contrast, with p-to-p loans, the upstarts have taken maybe just $250 million of the $400 billion now funded by credit cards. However, with the initial p-to-p defaults running one case near 20% market generally jittery about bad loans; with unsophisticated financial players (consumers) involved; and with uncertainty about where the buck stops, greater scrutiny now is not too surprising. A regulatory At the heart of the knot is whether p-to-p sites issue loans or securities. Typically, loans made on these sites are subdivided between many parties, so the $20,000 borrower gets has been advanced by ten individual lenders, each with $2,000 stake. subdividing or syndication makes it less like simple loan and more like structured debt instrument, or security. The U.S. securities law is very clear on this: if you have segment of consumer loan, then it is security, says Doug Dolton, chief executive of Zopa, which operates differently the U.S. than the U.K., precisely for that reason. The whole world of p-to-p lending, we're finding, is not simple, Dolton notes. A Canadian site and Dutch site have been shut down, he adds, and in the U.K., we had to carve out new category [with regulators]. Asheesh Advani, chief executive of Virgin Money, which operates similarly on both sides of the Atlantic--servicing pre-arranged private loans that are not subdivided--says, By design, we've avoided the minefield from the beginning. Lending Club could not take press calls during its mandatory quiet period with the SEC. Prosper, the biggest, true p-to-p lender (both Zopa and Virgin say they are not that category) said it filed an SI with the SEC last October and referred ABA BJ to statement issued after Lending Club's hiatus, noting that Prosper believes it is, structured... compliance with applicable state and federal laws. Banking law specialist Walt Moeling, partner Powell Goldstein LLP, Atlanta, says, If the SEC said 'you have to register as securities broker,' I don't think these sites could function. It is possible for bona fide loans, even when they are shared, to be distinguished from securities, he says, but factors considered include the financial sophistication of the parties involved and how tailored the offers are. The more it looks like 'take it or leave it' the more it looks like security, Moeling says Asked whether SEC regulation would kill the p-to-p model, Jim Bruene, former banker who is now editor and publisher of the e-zine NetBanker, said, Certainly, it's huge barrier to entry but my speculation is that it won't kill it. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.063
Threshold uncertainty score0.210

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0190.026
Open science0.0020.004
Research integrity0.0210.012
Insufficient payload (model declined to judge)0.0630.023

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.241
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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