Game Changer: Why Host Card Emulation Could Help Banks Reclaim Lost Ground in Digital Payments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
[ILLUSTRATION OMITTED] Actually, the next generation card won't be a card at all. That's right. No card at all. It will be a debit card, and two retailers are leading the way with the concept of host card emulation (HCE). They are Tim Horton's, which is the Canadian donut chain, and Starbucks. To explain: A consumer can enroll by visiting the website for Tim Horton's or Starbucks. Once verified, the consumer can download an app, activate it, and begin to use it at the store or online. The system connects the retailer membership program, such as the Starbucks Card, to a or credit card. The next step is for the consumer to preload a selected amount from an enrolled credit or card to her smartphone app. The amount downloaded is not on her phone, but on the retailer's system. Tim Horton's 2013 annual report states that the company had a SI55 million (Canadian) balance in its reloadable Tim Card Program, which serves as the funding vehicle for the TimmyMe smartphone app. That's impressive, but Starbucks, by far, is the front runner in this space with seven million active cards. In its 2013 annual report, the company reported that over $4 billion had been loaded onto its cards and spent for the year. Further, one in three transactions at its stores were paid with the Starbucks app. Starbucks has connected with its customers in a very big way, averaging a monthly purchase volume of over $300 million per month. It's no surprise this trend has garnered the attention of MasterCard and Visa. Opportunity in HCE The technology behind these two programs is HCE, a means of accessing a payment card account at the point of sale (POS) without requiring use of the card. In the case of Tim Horton's or Starbucks, their apps contain a barcode that can be read at appropriately equipped POS terminals at their stores. The barcode emulates the customer's or credit card through a secure gateway. The value that has been loaded onto the Starbucks system from the customer's enrolled or credit card waits until she purchases a drink and will remain until used up, which may take a lot of little purchases depending on the amount initially loaded. Then it's time to reload again. (Starbucks pays the interchange on only one transaction, by the way, which is a huge savings for the retailer.) Expanding the concept of how this can be used, the same device that scans the product barcode at self-checkout terminals also can be used to scan a consumer's smartphone barcode for the payment at any store that is enabled in the near future. It is as simple as that. How soon will this be available? Seeing the success at Tim Horton's and Starbucks, both MasterCard and Visa have announced efforts to develop and promulgate specifications for developers and service providers to use. Visa has already published specifications for HCE. MasterCard will do likewise, and you can bet that American Express and Discover are not too far behind. HCE is not limited to just barcodes. It also can be used in conjunction with near-field communication (NFC)--the technology behind contactless payment cards and NFC-equipped smartphones. But when you think of retailers, most are already equipped with barcode readers now. Very few have readers capable of handling an NFC card or smartphone. Furthermore, there are very few NFC-equipped smartphones out there. They require a special chip. Banks back in the game What does all this mean? Improved customer service and a lot more options. No more waiting for a plastic card to arrive in the mail. Soon, you will be able to download a digital card through your financial institution using the internet. The bank, retailer, or customer do not need to have NFC capability to use HCE. Anyone can download an app onto an existing smartphone. But most important for banks: They don't need to sign up with Starbucks (or any other retailer) to allow their customers to participate. …
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it