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Record W275544304

Video Banking on the Verge: Two-Way, Interactive Customer-Facing Installations Show Promise for Cost Savings, Increased Service

2010· article· en· W275544304 on OpenAlexaboutno aff
John Ginovsky

Bibliographic record

VenueABA banking journal · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingBusinessDatabase transactionService (business)CashMarketingCustomer retentionFinanceTelecommunicationsComputer scienceEconomicsManagementService quality
DOInot available

Abstract

fetched live from OpenAlex

[ILLUSTRATION OMITTED] Imagine doing away completely with an in-person teller line and instead offering branch customers a row of what look like automated teller machines on steroids, each with a high definition monitor, the other end of which is focused on a customer service representative located in some centralized location that may be miles away. The customer and rep conduct business screen-face to screen-face in real time and can complete just about any transaction an in-person teller could do. The rep would automatically be able to address the individual by name, because the customer's identification would be verified and all the account information would be available instantly. Cash could be dispensed, checks received, forms signed, and most any problem solved. Then imagine having this capability at 2 a.m., or whenever the customer found it most convenient to do business. That's one scenario of video banking that is starting to take shape, if not in the United States, yet, then in a number of other countries--notably Great Britain, India, Germany, Norway and, more recently, New Zealand, Australia, and South Korea. A handful of credit unions have already embraced this technology, however. Gene Pranger, CEO of uGenius Technology, Sandy, Utah, which has been working with several credit unions since 2009 on such systems, claims they reduce staffing, increase operating hours, free up managers to focus on products and services, and boost employee retention. Also, he says, consumer research, we've found that 90% of customers who use our machines are either very satisfied or extremely satisfied with their transactions. He adds customers find it faster, easier and more personal than traditional teller lines. If that seems odd, consider that in some urban locations, teller transactions are conducted through plastic bandit barriers, and also that younger customers have been raised on video and texting. Step into the high-def room In a second scenario of video banking, imagine a customer coming into a branch needing the services of a particular loan specialist or licensed professional, but that individual is physically located miles away in another branch. Instead of forcing the customer to make an appointment and come back another day, a bank rep would direct the customer into a special room set up with high definition video screens, cameras, finely tuned acoustics and lighting. The bank specialist would go into a similar room down the hall from his or her office, connect over special lines and immediately get down to business. This so-called immersive connection offers life-sized video of each individual and allows the illusion of a face-to-face meeting. It is almost like being there. You can't shake hands, but you can exchange business cards, says David Stern, who is global video services leader for IBM. He's helped set up such systems for businesses in Canada, Italy, Denmark and Greece, and sees a lot of potential for such applications for banks in the United States. It's taken a while but retail organizations are starting to figure out how to leverage the technology in an affordable way to generate revenue ... I think it's coming, he says. Many larger and regional banking companies have already embraced video conferencing as a way to facilitate staff and executive communications. Back-office meetings, training courses, and other consultative, in-house sessions have offered serious savings in travel time and costs, boosted productivity, and reduced corporate carbon emission tallies. Bank of America, in fact, recently contracted with Cisco Systems Inc., Charlotte, N.C., to install 200 Telepresence rooms across its office network, targeted specifically for staff-only use. [ILLUSTRATION OMITTED] This is different from video banking with customers at the retail level, however. Security for the types of things discussed in a customer-facing video system, while stringent, would be much different from the type of security required for the back-office video conferencing networks, says Jonathan Brust, vice-president/marketing, Glowpoint Inc. …

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.142
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.1420.026

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 head0.026
GPT teacher head0.258
Teacher spread0.232 · 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
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
Published2010
Admission routes1
Has abstractyes

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