PayPhal is the innovation from CamSoda that gives a whole new meaning to tipping with one’s penis.

Launching in Beta, PayPhal will enable men to pay cam models in real-time during a private cam session based upon their level of arousal
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CamSoda, a leading adult entertainment webcam platform, has developed a novel way to add further interactivity to their adult web cam sessions. By using PayPhal described as ‘a technology solution that acts as a digital wallet’ CamSoda claims that users will be able to pay for their adult entertainment with their erections.

“Erections are synonymous with the adult entertainment industry. It only makes sense that here at CamSoda we cater to our users and provide them with a seamless payment method that aligns with their horniness. All things considered, the last thing someone wants to do when fully aroused is pull out…their wallet and enter their payment details and wait for everything to process,” said Daryn Parker, VP, CamSoda. “PayPhal will go a long way towards significantly expediting things, freeing guys up to enjoy the experience without interruption. Now, not only will guys be able to pay hands free, but models on CamSoda and in strip clubs will be provided a definitive barometer of their performance. If a model isn’t putting any effort into their show, and the viewer is left flaccid, PayPhal will tip accordingly.”

Launching in Beta on CamSoda, PayPhal will initially enable men to pay cam models in real-time during a private cam session based upon their level of arousal, as their penis progresses from “flaccid” to “half-chub” to “erection.” In the coming months, CamSoda will look to partner with strip clubs to replace the use of dollar bills and digitize the industry.

What payment method will be developed in the future for women in a similar fashion - the contactless clit?
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To make payments via PayPhal, users attach a teledildonic penis ring around the shaft of their penis, which will take into account the girth of a user’s penis via the Girth Detector ocated on the ring itself, and establish a baseline size. A user then enters into a private cam session with a model, and, depending on how aroused they get during the session – progressing from “flaccid” to “half-chub” to “erection” – PayPhal will send the model an electronic payment in the form of a tip. So, if a user enters into a private session and their penis grows four inches, the model is paid for the four inches the user’s penis grew.

This all looks remarkably like the internet of things are taking possession of your genitals. The datafication of arousal is remarkably like an innovative and updated version of the penile plethysmograph,  a technology used by some sexologists to measure the ‘tumescence’ of a penis. PayPhal appears to convert this tumescent process into a financial transaction between the user and the sex worker. The ‘Girth Detector’ also appears to standardise penis sizes which could cause some difficulty in erectile confidence for some, and have the ability to enhance experience for others, particularly if there is a preference for genital bondage or restriction by the user. The sizes start at LARGE rising to MONSTER, inspiring confidence and anticipating penis performance – and the size of the financial tip.

The datafication of arousal is remarkably like an innovative and updated version of the penile plethysmograph, a technology used by some sexologists to measure the tumescence of a penis
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In the coming months, CamSoda will look to partner with strip clubs to replace the use of dollar bills and completely digitize the industry. Ideally, patrons will be able to walk into a strip club with the penis ring on and tip performers as their penis grows while they receive a lap dance.

The difficulty with part of the concept is the overall aim to digitize payment for both live and online sex workers. Sex workers will also have their own chip and pin readers if a client does not have PayPhal, and this could lead to a social split between those sex workers who are fully digital, and those who are not. This could also lead to differences in financial control between worker and sex trade business owner.

Ideally, patrons will be able to walk into a strip club with the penis ring on and tip performers as their penis grows while they receive a lap dance
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PayPhal could also lead to payment disputes as clients could possibly find that they are accused of lying about their Girth Detector, and are then not paying the right amount of tip. Potentially this could lead to abuse of the system with the possibility of fake erections, and those who think that they are MONSTER size when they are not and vice versa. There may also be a time factor that may have an effect, tumescence may well come and go during the time spent at a strip club, so when is the best time for the penis to pay the tip to the sex worker or stripper? Who has control over payment – the person or the penis?

Overall this is a novel approach, and CamSoda is being adventurous here, as this could be a new wave of payment control that may well support sex workers if the technology is not abused. But what payment method will be developed in the future for women in a similar fashion – the contactless clit?

The post Paying with Your Penis appeared first on Tech Trends.

To leverage Big Data and build an effective Artificial Intelligence infrastructure, enterprises must embrace collaboration.  

Using data smartly can give your business a crucial competitive advantage
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In a digital economy, the rule of thumb tends to be that the smarter your use of data and technology, the more of a competitive edge your business has. A recent report by Teradata, based on over 260 interviews conducted by research firm Vanson Bourne with senior IT and business decision makers, found that there is widespread enthusiasm for adoption of AI, with 80 percent of enterprises reporting that they were already investing in the technology in some capacity, and over 30% planning to expand their investment in the are over the next 36 months.

“C-level executives – namely CIOs and CTOs, maintain they are committed to AI in their enterprise, because of the expected ROI over the next 10 years.” The report therefore concludes that executives will accept those challenges as the long-term benefits clearly outweigh near-term pain. In fact their analysis showed that over a five-year forecast, organisations effectively expected to double their money when investing in AI: For every $1 spent on AI technologies, organisations predicted a return on investment of $1.23 over three years, $1.99 in five years, and $2.87 over a ten-year period.

The Economist – in a phrase that has since become rather cliché – put forward the idea that “data is the new oil,” and World Economic Forum has now designated Big Data as a new kind of economic asset, just like currency or gold.

A study by the MIT Center for Digital Business confirms that data-driven businesses do indeed have the edge. It surveyed 330 leading U.S. Businesses and found that companies that focused strongly on data-driven decision-making had an average of four percentage points higher productivity and six percentage points higher profits.

C-level executives are committed to implementing AI in their enterprise
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Yet as these results indicate, it would perhaps be more accurate to say that data is in fact the new oxygen. Whereas it is still true that businesses that best leverage data and AI will gain a significant competitive advantage, it is probably fair to say that those that fail to make their organisations data-centric will eventually not be able to survive at all in the digital age.

Data is in fact the new oxygen
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While most people agree on the essential role that Artificial Intelligence and Data play in their organisation’s success, there are significant challenges. The overwhelming majority of business leaders surveyed in the Teradata report anticipated major barriers for adoption within their organisation, with roadblocks ranging from an inadequate IT infrastructure to shortage of in-house talent.

The majority of business leaders surveyed predicted significant roadblocks to AI adoption
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In their book The Sentient Enterprise, The evolution of Business Decision Making – launched at the Teradata Partners’s Conference last month – Oliver Ratzesberger (Teradata’s Chief Product Officer) and Mohanbir Sawhney from the McCormick foundation talk about how agility is key to getting the enterprise to the sentient point where it can analyse data and make decisions in real time.

The crux of the problem enterprises face lies not in the difficulty of gathering data, but in extracting insights and then turning these into actionable processes. The reality is that we live in a time of data overload, and companies can easily find themselves trapped in reactive mode, spending most of their time sifting through mountains of data and making decisions only when problems emerge, rather than anticipating them.

The problem enterprises face is in extracting actionable insights from data
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To tackle these problems, enterprises need access to key talent and infrastructure so as to enable the leveraging of Artificial Intelligence and Big Data. Increasingly, this is not being done “in house” but rather in partnerships with dedicated providers. These go beyond the traditional SaaS and becomes much more of a “Platform as a Service” model that incorporates complex customization and consultancy services.

All banks need a scalable, advanced analytics platform
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Teradata’s Think Big Analytics team, for example, worked with Danske Bank to create a fraud-detection platform that uses machine leaning to analyse tens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding true, and false, fraudulent activity. Together, they built a framework within the bank’s existing infrastructure, crating advanced machine learning models to detect fraud within millions of transactions per year, and in peak times, many hundreds of thousands per minute:

“Using AI, we’ve already reduced false positives by 50% and as such have been able to reallocate half the fraud detection unit to higher value responsibilities,” explains Nadeem Gulzar, Head of Advanced Analytics, Danske Bank. “There is evidence that criminals are becoming savvier by the day; employing sophisticated machine learning techniques to attack, so it’s critical to use advanced techniques, such as machine learning to catch them.”

Using AI, Teradata and Danske Bank reduced false positives by 50%
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“All banks need a scalable, advanced analytics platform, as well as a roadmap and strategy for digitalization to bring data science into the organization.” says Mads Ingwar, Client Services Director at Think Big Analytics. “For online transactions, credit cards and mobile payments, banks need a real-time solution – the platform we developed with Danske Bank scores transactions in less than 300 milliseconds. It means that when customers are standing in the supermarket buying groceries, the system can provide immediately actionable insight. This type of solution is one we’ll begin to see throughout organizations in the financial services industry,” he concludes.

Fintech company Verifi, also collaborates with banks and merchants to connect the multi-layered data-streams and combat fraud. The work the company does with is based on optimising data transmissions using APIs (Application Programming Interfaces). This is much more efficient because whereas legacy systems rely on processing large numbers of files sent in bulk, APIs can process data in real-time.

Verifi collaborates with banks and merchants to connect multi-layered data-streams
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The Verifi system collates APIs from the merchant shopping cart, customer relationship management (CRM) system, shipping data system, and others, and provides the merchant with better information to handle charges disputed by consumers, allowing them to often resolve the issue directly rather than have the bank issue a chargeback. Merchants benefit as they’re able to control the message to the consumer, and banks are happy because the sale remains and they reduce their operating costs. It is the sort of technology enabled, data-driven system that is a true win-win.

Friendly fraud and chargebacks cost $130 million in Q1 2017 in the U.S.
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One of the problems that such systems help tackle is so-called “friendly fraud,” a term used to describe a situation when a customer experiences “buyer’s remorse” and “tries it on” by putting in a claim directly with their bank or card issuer for a refund, when the sale did in fact legitimately occur. Julie Conroy, Research Director of the Aite Group says that in the U.S. friendly fraud and chargebacks would likely near $130 million, in Q1 2017 alone.

“Since many such claims are relatively low-value, banks will often issue the refund rather than dedicating the resources needed to investigate and dispute each transaction,” explains Matthew Katz, Verifi’s CEO Their research in fact showed that up to 86% of cardholders bypass the merchant and contact their issuing bank directly to dispute or question a charge on their bill. “When you add all of these claims up, it amounts to a huge problem for the industry, with billions of dollars in costs being passed onto merchants, and – ultimately – to the consumer,” he says.

Friendly fraud amounts to a serious problem, confirms a report from Javelin Research estimates that the increase in card-not-present (CNP) fraud and chargeback management now consume between 13% and 20% of operational budget for such retailers.

Even with such resources dedicated to fighting fraud, however, not having the right information on hand in real time can mean that businesses are not only vulnerable to fraud, but also risk losing customers and reputational goodwill by challenging legitimate customer claims.

“The key functionality we enable is to connect all the parties to the transaction with the right information at the right time,” says Katz. “Our Order Insight platform provides robust transaction data on each sale, like the merchant’s name and contact information, date of purchase, device name used in the order process and many more important details, directly to the consumer via their bank’s mobile or online interfaces. In most cases, having access to this data can resolve a dispute and avoid a phone call to the issuer altogether, saving the merchant money and keeping customers happy.”

The report by Javelin Research concludes that partnering with third-party providers like Verifi makes sound business sense, in that it frees up merchants to focus on their core business. “It is imperative that merchants stay customer-friendly in the face of growing fraud pressure, yet the amount they have to put into building, managing, and maintaining in-house solutions has significant negative impact on their ability to scale their business over time. The projected growth of CNP fraud will introduce a new level of burden for digital merchants, which they will be unable to combat from a resource and scalability perspective. This will increase the pressure and negative impacts on them because they will be hit by fraud that they can’t handle. Their inability to scale quickly enough may result in measures that will hinder customer experience.”

The key advantage that these technologies – when properly leveraged – bring to enterprise is their ability to streamline and break silos
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The key advantage that these technologies – when properly leveraged – bring to enterprise is their ability to streamline and break silos. Deeper integration and more collaborative approaches to technology can help deliver robust information to the right parties at the right time, ultimately enhancing the experience for customers and users, improving efficiency across the board, and providing higher returns for companies and investors. The pieces of the puzzle are all there, it seems, but stakeholders must all work collaboratively to bring them together.

This article was first published on ERP in News

How Collaboration is key to leveraging AI and Big Data https://t.co/UGfUT6KjYl via @erpinnews@alicebonasio #tw17 #erpinnews #eintechnews

— ERPINNEWS (@erpinnews) November 15, 2017

Alice Bonasio is a VR Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. Connect with her on LinkedIn and follow @alicebonasio and @techtrends_tech on Twitter.

The post Working Together to Build a Big Data Future appeared first on Tech Trends.

Non-legitimate refunds cost merchants billions every year, but Fintech company Verifi is using data insights to spare them costly chargebacks.

In a digital economy, the rule of thumb tends to be that the smarter your use of data and technology, the more of a competitive edge your business has. This is particularly true in the e-commerce and retail sectors, where small inefficiencies can quickly compound and become large-scale problems.

In a digital economy, leveraging contextual data gives businesses an edge
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Take, for instance, the deceptively innocuous-sounding problem of “friendly fraud.” The term is used to describe a situation when a customer experiences “buyer’s remorse” and “tries it on” by putting in a claim directly with their bank or card issuer for a refund, when the sale did in fact legitimately occur.

“Since many such claims are relatively low-value, banks will often issue the refund rather than dedicating the resources needed to investigate and dispute each transaction,” explains Matthew Katz, CEO of payment management and resolution platform Verifi. Their research in fact showed that up to 86% of cardholders bypass the merchant and contact their issuing bank directly to dispute or question a charge on their bill. “When you add all of these claims up, it amounts to a huge problem for the industry, with billions of dollars in costs being passed onto merchants, and – ultimately – to the consumer,” he says.

Julie Conroy, Research Director of the Aite Group adds that in the States, in Q1 of 2017 alone, friendly fraud and chargebacks would likely near $130 million, with the global figure in 2016 being closer to $30 billion. There are many reasons why consumers make these claims, yet they’re not all necessarily sinister or even dishonest. In an age of speedy payments, where we can tap our cards or phones at a shop and walk away with our purchases within seconds or order through a mobile app with a single click, we often forget what we bought over the course of a day, nevermind a week or a month. I for one know that over the years I’ve had trouble clearing my bank’s security questions when they required me to name the amount of the last few transactions I had made on a certain card. A guesstimate was all I could ever manage without actually looking up a statement.

Friendly Fraud is a growing problem for retailers and digital merchants
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This is further compounded by the fact that often the registered merchant name that appears on statements can be different from the trading name on their shop front or website – which is why services such as PayPal usually make a point of telling you that “this transaction will appear on your statement as…” But regardless of the reasons behind it, friendly fraud amounts to a serious problem, especially for merchants dealing in digital goods. A report from Javelin Research estimates that the increase in card-not-present (CNP) fraud and chargeback management now consume between 13% and 20% of operational budget for such retailers: “Fraud and chargeback spend is front and centre for digital goods merchants, with these merchants dedicating significant proportion of operational costs to keeping fraud in check.”

Verifi CEO Matthew Katz

Verifi connects merchants with contextualised transaction information
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Yet even with such resources dedicated to fighting fraud, not having the right information on hand at the right time can mean that those businesses not only leave themselves open to fraud, but they also risk losing customers and reputational goodwill by challenging legitimate customer claims. To avoid such issues, banks and merchants need to be able to share customer and transaction information in near real-time with the issuing bank or consumer, and that’s where platforms such as Verifi provide the missing link.

“The key functionality we enable is to connect all the parties to the transaction with the right information at the right time,” says Katz. “Our Order Insight platform provides robust transaction data on each sale, like the merchant’s name and contact information, date of purchase, device name used in the order process and many more important details, directly to the consumer via their bank’s mobile or online interfaces. For those consumers who do call the bank, the same information is provided to the bank’s call centre personnel to appropriately legitimise the sale and address the consumer’s questions or concerns. In most cases, having access to this data can resolve a questionable charge and avoid a phone call to the issuer altogether, which saves the merchant money while keeping customers happy.”

Partnering with third-party providers like Verifi makes sound business sense, according to Javelin Research, whose report recommendations lay out the advantages of outsourcing fraud solutions in order to allow merchants to focus on their core business: “The amount they have to put into building, managing, and maintaining in-house solutions has significant negative impact on their ability to scale their business over time.” They also warn that businesses need to be mindful of maintaining and building customer relationships while elevating security checkpoints to combat CNP fraud. “The projected growth of CNP fraud will introduce a new level of burden for digital merchants, which they will be unable to combat from a resource and scalability perspective. This will increase the pressure and negative impacts on them because they will be hit by fraud that they can’t handle. Their inability to scale quickly enough may result in measures that will hinder customer experience. It is imperative that merchants stay customer-friendly in the face of growing fraud pressure.”

It makes sense for merchants to outsource their fraud solutions
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Verifi is rapidly expanding into the UK market
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Verifi is investing heavily into its UK market expansion, as well as many other global markets. Since opening their London office just under a year ago, the California-based company says the demand has far exceeded expectations, and they are now focusing on extending their UK network coverage for their Cardholder Dispute Resolution Network (CDRN) to 70% by the end of 2017.

“We currently support hundreds of merchants and recognised global brands in diverse industries spanning digital music, information technology and entertainment, as well as top High Street and UK e-commerce clients,” says Katz, who adds that there is still enormous scope for expansion as the online retail market continues to grow and fraud prevention needs evolve. “Our challenge and goal is to make sure that our data platforms and solutions keep pace with evolving demands, without compromising the customer experience,” he concludes.

Alice Bonasio is a VR and Digital Transformation Consultant and Tech Trends’ Editor in Chief. She also regularly writes for Fast Company, Ars Technica, Quartz, Wired and others. Connect with her on LinkedIn and follow @alicebonasio on Twitter.

The post Fighting Friendly Fraud with Big Data appeared first on Tech Trends.