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Record W246392962

One-Click Check Presentment

2000· article· en· W246392962 on OpenAlexaboutno aff
Steve Cocheo

Bibliographic record

VenueABA banking journal · 2000
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBanking Systems and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentBusinessThe InternetPopulationPayment systemComputer scienceFinanceWorld Wide WebMedicine
DOInot available

Abstract

fetched live from OpenAlex

THE FED AND THE PAYMENT SYSTEM: PART II banks lead the way in the Fed's EPIC electronic check presentment pilot which combines imaging with Internet delivery Malta, Mont., lies about 45 miles below the Canadian border in the northeastern part of the state, where major roads are few, the population sparse, and nature itself can be a formidable opponent. We're remotely located, says Corliss Nelson, cashier of First State Bank of Malta, with a bit of understatement. Yet, First State and a group of other banks are at the very center of state-of-the-art developments in payment systems. Backers of electronic check presentment as part of the solution to the payment system's glut of paper watch very closely, for Federal Reserve efforts there may someday spread, in some variation, throughout the system. With about 200 depository institutions, most of them small, spread over a geographic area as long as the distance between Philadelphia and Chicago, made an attractive proving ground for the Federal Reserve System's EPIC project. EPIC, which stands for Electronic Presentment Internet Checking, is a technology pilot proposed and spearheaded by the staff of the Helena, Mont., branch of the Federal Reserve Bank of Minneapolis. The goal of the Montana Pilot, as EPIC is more commonly referred to in Fed circles, is to set up a completely electronic check payments process throughout the state in voluntary collaboration with the state's financial institutions. The technique of choice is electronic check presentment, accompanied by check imaging provided by the Fed, and internet availability of check images and related records. Building greater acceptability of electronic check presentment has turned into a major goal of the Fed's Payments System Development Committee (ABA BJ, Sept. 2000, p. 42). In early September the committee issued a list of steps to take to build that acceptance. (See page 62.) Electronic check presentment consists of substituting MICR line data for the check itself, so that the actual check need not travel beyond the point where that data is captured. This eliminates much or all of the physical transfer of checks, while still permitting consumers and businesses to make payments using the familiar paper checks they have been using for more than a century. The potential payoffs include increased efficiency, reduced fraud, improved accuracy, and reduced costs. This is electronic check presentment as defined by the Fed, and as practiced in Helena; some private sector electronic check presentment efforts still include the actual check somewhere in the flow. A phased approach The pilot is a testing of legal concepts as well as technological ones. A key issue is ensuring the acceptability of an official replica of a check in lieu of the actual check. The Fed's Helena branch and participating depository institutions are engaged in the program under bilateral agreements that supersede certain laws and rules that would otherwise apply to checking transactions. This temporary legal underpinning would have to be made permanent, in some fashion, before much of what is going on in could be applied beyond the state. The pilot consists of three phases, with participating institutions already engaged in the first two, with the third still under development: * Phase one -- Beginning in June 1999, the Helena Fed began to image capture and archive all checks that pass through it, with the branch now processing an average of 750,000 checks daily, according to Sam Gane, branch manager. At the imaging stage, both MICR line information as well as the front and back of every check are captured. Participating depositories, in their role as paying banks, receive electronic presentment files, rather than checks, and process these as if they had received checks. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.713
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.005
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7130.487

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 head0.025
GPT teacher head0.225
Teacher spread0.201 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2000
Admission routes1
Has abstractyes

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