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Record W326785786

Seeking the "New Reality": CRE Loans in Past and Present Tenses Aren't Any Fun. Will Future Tense Improve?

2012· article· en· W326785786 on OpenAlexaboutno aff
Steve Cocheo

Bibliographic record

VenueABA banking journal · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsFellReal estateQuarter (Canadian coin)Nonfarm payrollsAsset (computer security)LoanDebtEconomicsBusinessFinanceHistoryGeographyCartographyAgriculture
DOInot available

Abstract

fetched live from OpenAlex

[ILLUSTRATION OMITTED] Community banks' involvement with commercial real estate can be broken into three phases. There is an aggressive past that is still being paid for; a present that in many markets mixes inactivity with occasional frenetic competition; and a future where the economics will be very different, and where the seeds of potential further trouble have already been planted. That's not exactly an upbeat summary. And it's a composite picture. But when you are dealing with the aftermath of a crisis, simply still being around to talk about it has a great deal to be said for it. The worst is behind us, says Keith Leggett, ABA senior economist. CRE asset quality is improving, vacancies overall are falling, and prices in many markets are firming, albeit at lower levels. Industrywide, FDIC reported in late February, net charge-offs fell by 40.2% in fourth-quarter 2011, versus fourth-quarter 2012, with charge-offs on real estate construction and land development loans, a facet of CRE lending, falling by 62.4%. Noncurrent loan balances in two key categories fell, too real estate construction and land development loans, by 13.2% in the fourth quarter, compared to the third, likewise nonfarm nonresidential real estate loans, by 4%. On the other hand, observers say many community banks have seen their CRE activity shrink, between falling activity, retiring debt, and write-offs. It's a regrouping time for most institutions, says Scott Miller, principal in the risk consulting practice at Crowe Horwath LLP. This has been a real negative environment for people--they are getting fatigued. Playing out the hand Many of the bank failures brought on by CRE have been processed by FDIC. However, write-downs of existing loans in portfolio continue. Miller says he doesn't find much that's positive yet on the CRE front. These days, he says a good deal of his practice touches on clients' loan loss reserve, and he frequently has to push the question: Are we really going to get all of these problem real estate loans worked out? Some banks simply lack the capital to take a harshly realistic view on their CRE portfolios, says Miller, and so they are currently doing a dance until they next see regulators. That will correct itself at the next exam, he explains. Miller's view may sound tough, but bankers also number among the realists. Georgia banker Dan Blanton, a veteran real estate lender with real estate industry experience, as well, brooks no middle ground. this environment, you have to get this stuff off your books, says Blanton. You can't sit on property either. While some bankers say examiners push too hard for disposal of Other Real Estate Owned (OREO), Blanton points to stagnant prices and shrugs, I don't know when values are going to return. In other words, cut your losses and move on. every bad loan has to be written off. Bankers have been engaging in workouts where they can. Most of those interviewed say they found little they didn't already know in the interagency Policy Statement on Prudent Commercial Real Estate Loan Workouts, published in October 2009. However, Michelle Lucci, a former banker and examiner and now CRE risk management consultant for Bankers Toolbox, sees evidence in FDIC's quarterly numbers that a great deal of CRE debt has been rewritten in hopes of successful workouts. (Bankers Toolbox, an ABA-endorsed company, offers CRE stress testing services.) There are banks, or even markets, where CRE troubles didn't reach debacle levels. Not all community banks held their noses and jumped in the same way, says Constantine Tino Korologos, managing director, Deloitte Corporate Finance LLC. He points out that some of the orphan properties out there--e.g. pristine new strip malls sitting empty throughout the crisis--weren't even bank-financed. Many were projects pushed along by investment banks anxious to generate product for commercial real estate mortgage conduits. …

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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)0.002
metaresearch head score (Gemma)0.008
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: Other · Consensus signal: none
Teacher disagreement score0.053
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0120.023
Open science0.0010.005
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0530.011

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 head0.022
GPT teacher head0.220
Teacher spread0.198 · 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
GenreOther

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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