- Netflix Q4 revenue $1.3B (+35.7% Y/Y); net income beat, profit outlook for 2017 sends shares up 16%: Netflix will expand to 200 countries, raise $1B in debt to create original content: Netflix Revenue rose 35.7 percent, to $1.3 billion, compared with the year-earlier period. Net income for the quarter was $83 million, or $1.35 a share, up from $48 million a year earlier, because of a benefit related to the resolution of a tax audit. Without that tax benefit, net income would have been $45 million, beating the forecast for $27 million. The company lost less money than it had expected in its international business and also benefited from other tax credits. The company said it had exceeded its forecast for total paid streaming subscribers. That number increased to 54.5 million in the quarter that ended Dec. 31, 2014, up 31.5 percent from the same period in 2013. n the United States, Netflix had 39 million streaming members in the fourth quarter, a net addition of 1.9 million. In the year-earlier period, it added 2.3 million members. For the coming quarter, Netflix predicted that growth would slow further. Netflix is pouring resources into original productions. Investors sent the shares up as much as 16 percent after the Los Gatos, California-based company said it will profitably reach all 200 of the countries that have broadband Internet service within two years. “We then intend to generate material global profits from 2017 onwards,” Chief Executive Officer Reed Hastings and his finance chief, David Wells, said today on the company’s website. The outlook reassured investors who have expressed concerns about the company’s narrow margins, widening international losses and a budget for films and TV shows that’s swollen to $9.5 billion from $7.3 billion in the past year. Netflix rose 15 percent to $404.01 in extended trading. It reached as high as $405.70 following fourth-quarter results that included better-than-predicted subscriber growth. The stock gained 3.4 percent to $348.80 at the close in New York. International subscriber growth outstripped gains in the U.S. for the third straight quarter, as Hastings raced to plant his flag before other would-be competitors. Users outside the U.S. expanded by a record 2.43 million in the fourth quarter, reaching 18.3 million. Fourth-quarter revenue rose 26 percent to $1.48 billion, compared with analysts’ predictions of $1.49 billion. Net income almost doubled to $83.4 million, or $1.35 cents a share, aided by a tax benefit, Netflix said on its website. Domestically, the company added 1.9 million new customers to reach 39.1 million, compared with the 1.85 million predicted. That brought the worldwide total to 57.4 million. This quarter, Netflix forecasts 1.8 million new U.S. customers. Profit will be $37 million, or 60 cents a share. To support its programming efforts, Netflix plans to borrow at least $1 billion. The company’s has committed to spending $9.5 billion on programming.
- IBM misses on both topline and bottomline, posts 11th straight quarterly revenue declines, shares down 1.8%: International Business Machines Corp posted a new 2015 profit target and quarterly revenue that both missed analysts' estimates, as the one-time world technology leader continues to grapple with its journey from low-margin hardware maker to the new world of cloud computing.Shares of IBM, which is still the world's largest technology services company, but no longer regarded as a leader in innovation, fell 1.8 percent to $154.05 in extended trading. It was the 11th straight quarter that the Armonk, New York-based company has reported falling quarterly revenue, including the effects of currency. It has seen shrinking revenue for three years now as it sheds low-profit businesses such as cash registers, low-end servers and semiconductors and tries to focus on emerging areas such as security software and cloud services. But the new businesses have so far failed to make up for revenue lost to divestitures. Annual revenue fell to $93 billion for 2014, from $107 billion in 2011. The company had no guarantee that it would not fall further. "We're not interested in revenue for revenue's sake," IBM Chief Financial Officer Martin Schroeter told Reuters in a phone interview. "We'll continue to divest if something doesn't fit the model." The struggle to make headway in the new Internet-based technology industry is shared by other longstanding giants. SAP SE, Europe's largest software group, on Tuesday cut key profit forecasts and abandoned a target for higher margins. "IBM as well as other tech stalwarts such as Oracle, SAP, HP and Cisco face major headwinds as they adjust to this new cloud paradigm shift, which coupled with a cloudy IT spending environment have negatively impacted results," said Daniel Ives, an analyst at FBR Capital Markets. IBM is in the midst of a challenging transition, and its fourth-quarter financial results reflected that reality. The technology giant on Tuesday reported quarterly declines in both sales and profits, though its earnings were above Wall Street’s diminished expectations. The company said net income in the quarter fell to $5.5 billion, down 11 percent from the same quarter a year ago. The company’s operating earnings declined to $5.81 a share, above the average estimate of analysts for $5.41 a share, as compiled by Thomson Reuters. IBM’s revenue slid to $24.1 billion, well below the $27.7 billion in the year-earlier quarter. Its quarterly sales were somewhat below Wall Street’s consensus forecast of $24.8 billion. In after-hours trading, IBM’s stock price slipped $2.90 a share, or about 1.9 percent, to $154.05. The new businesses the company has earmarked for growth — data analytics, cloud, security and mobile apps for corporations — grew at a 16 percent rate in 2014 and contributed $25 billion in revenue, or 27 percent of the company’s total sales. These growth businesses, he said, should continue to expand at a double-digit rate. But analysts question how well IBM is doing in achieving its objectives.
- Twitter's makes first India acquisition, buys missed call startup Zipdial for $30-40M; gains a Bangalore office and a way to engage customers offline: Twitter acquired Indian startup Zipdial earlier today, signaling that the social network is doubling down on the fast changing Indian market. But the ramifications of the buy-out don’t stop there. What Zipdial does is give companies a way to engage with people without forcing consumers to make calls, send SMS, or go online. All people have to do is send a missed call to a specific number belonging to a brand or service, and that subscribes the individual to relevant updates. It’s a little bit like Twitter, except it works mostly offline. And now that Twitter owns Zipdial, that way of operating will be used by the social network in India and a lot more countries. “It can drive growth in other similar emerging markets, like Indonesia or Brazil,” says Rishi Jaitly, Twitter’s market director for India and Southeast Asia. While there are no specific plans yet, Jaitly explains to Tech in Asia that Zipdial has experience across Southeast Asia and Africa, so the know-how is ready to roll. What Zipdial offers Twitter, says Jaitly, is a way for people to “connect to digital content offline. Jaitly says those early experiments in conjunction with Zipdial worked well. Those allowed India’s phone users to make a missed call to follow certain celebrities on Twitter. This worked entirely offline, by receiving SMS updates, and didn’t require the individual to sign up to Twitter. “All kinds of people on all kinds of devices consumed content” through those projects, says Jaitly. “You can expect us to draw lessons from experiments with Zipdial and scale them up,” he adds. The acquisition – Twitter’s first in India, and which gives it a Bangalore office – leaves Twitter with a lot moves it can make in emerging markets, which also opens up new revenues streams from brands and media using this “missed call” service to engage with consumers. Although deal size was not disclosed, separate media reports pegged it at $30-40 million. ZipDial’s user experience combines SMS, voice, mobile web and access to mobile apps to bridge users from offline to online. The company’s core business model, though, was built on leveraging the ubiquitous behaviour of ‘missed calls’ between friends and applying them as an offline call-to-action for brand engagement. For example, through ZipDial, one can engage with a publisher or brand by making a toll-free ‘missed call’ to a designated phone number. The caller will then begin receiving inbound content and further engagement on his/her phone in real time through voice, SMS or an app notification. These interactions are especially appealing in areas where people aren’t always connected to data or only access data through intermittent Wi-Fi networks. Additionally, prepaid recharge or top-up (money added to a user’s prepaid mobile account) is considered as valuable as currency in emerging markets. That became a foundation for the company’s couponing and gratification products.
- Alibaba is everywhere: invests in an Israeli QR code startup, and also seeks a stake in a giant state-owned Chinese insurance firm: QR Codes: Alibaba invests in Visualead, an Israeli startup that generates QR codes. Alibaba has announced it has helped raise a series B round in Israel’s Visualead, a startup that lets users generate visually appealing QR codes. The size of Alibaba’s investment remains undisclosed, but Visualead has previously raised US$2.4 million to according to CrunchBase. Visualead helps small business create QR codes that blend into images more seamlessly than standard black-and-white QR codes. Using the company’s web-based service, users can upload images, specify urls, and generate QR codes that mesh into the particular graphic. The company offers numerous tiers for individuals and enterprises based on the number of QR codes they hope to create. According to a release from Visualead, Alibaba will help its Taobao and Tmall vendors integrate Visualead into their marketing initiatives. The Chinese ecommerce giant has its own QR-code initiative, Mashangtao, which helps merchants create QR codes for any number of purposes like parcel tracking or marketing. Insurance: Alibaba is planning to buy shares in the state-run New China Life Insurance Shanghai Securities News said on Wednesday, citing unnamed sources. Alibaba is already invested in China's insurance market. The founders of Alibaba and Tencent Holdings Ltd (0700.HK) were among a consortium of investors who purchased stakes in Ping An Insurance Group Co of China Ltd (2318.HK) (601318.SS) in a HK$36.5 billion ($4.7 billion) deal in December. New China Life Insurance has a market capitalisation of $24 billion and provides life insurance services and products.
- Alibaba, Tencent and Baidu are starting to make increasingly similar investments and behave more and more alike: Before China became the biggest smartphone market, there was little overlap between the businesses of e-commerce leader Alibaba Group Holding Ltd, social networking firm Tencent Holdings Ltd and search engine provider Baidu Inc. Now, as more and more Chinese use their phones for everything from shopping to booking restaurants, the three companies are increasingly stepping over each other - and investing in the same services - to attract the same users. In little over a month, taxi-hailing apps Didi Dache, supported by Tencent, and Alibaba-funded Kuaidi Dache raised over half a billion dollars each, while U.S. taxi app Uber attracted an undisclosed sum from Baidu. The next arena looks set to be group-buying services, where customers agree to buy a certain item or service at the same time to gain discounts. Baidu bought out Nuomi last year and Alibaba-backed Meituan on Monday said it raised $700 million, valuing the company at $7 billion.
- Rumors have it that Olacabs might be close to raising another $300-500M at $2B: Barely three months after Mumbai-based ANI Technologies Pvt Ltd, the company behind Olacabs, an online marketplace for cabs and car rental services, raised $210 million led by SoftBank, it is back in the market to scoop between $300-500 million more, sources privy to the development told Techcircle.in. “Ola has doubled in size in terms of revenue run rate since its last fundraise when it was valued at $1 billion. It is now seeking twice the valuation,” said one of the sources. The source added that it is likely to rope in at least two new investors including a New York-based fund besides a Hong Kong-based fund house, besides participation from most of its existing investors. “While one of the new investors is a hedge fund, the other is a PE investor,” he said. The proposed fundraising, which would be its Series E or fifth round of institutional funding, would strengthen its position as the most heavily funded player in its business. It would also make it the third most funded new generation tech venture behind Flipkart and Snapdeal. One97 which operates Paytm is in the final stage of scooping a large round. Olacabs had raised $210 million in its Series D round led by Japanese internet and telecom giant SoftBank. Previously, it raised Rs 250 crore ($41.8 million) in its Series C round of funding led by Hong Kong-based hedge fund manager Steadview Capital and Silicon Valley-based Sequoia Capital. Existing investors Matrix Partners India and Tiger Global Management also participated in this round. In November 2013, Olacabs had raised its Series B round of funding led by Matrix Partners India for a big minority stake, with participation from existing investor Tiger Global Management. Although the company had not disclosed the amount at the time, media reports pegged it at $20 million. Prior to that, it had raised Rs 19.2 crore ($3.2 million) from existing investor Tiger Global in July the same year, which was believed to be part of the same round. Back in 2012, the company had raised over $5 million in its Series A funding from Tiger Global. Prior to that, it had raised angel funding from a bunch of individual investors, including Rehan Yar Khan and Anupam Mittal. In the cab booking segment, Ola is seen as the biggest player competing with Google Ventures-backed global major Uber and domestic players such as TaxiForSure (backed by Accel Partners and Bessemer Venture Partners), Savaari, taxiGUIDE and Cabs24X7.
- Big-data based lending story #1: Small startups attempt to use borrower profiling models that use behavioral signals to cut default rates on student loans, personal loans: When bankers of the future decide whether to make a loan, they may look to see if potential customers use only capital letters when filling out forms, or at the amount of time they spend online reading terms and conditions — and not so much at credit history. These signals about behavior — picked up by sophisticated software that can scan thousands of pieces of data about online and offline lives — are the focus of a handful of start-ups that are creating new models of lending. No single signal is definitive, but each is a piece in a mosaic, a predictive picture, compiled by collecting an array of information from diverse sources, including household buying habits, bill-paying records and social network connections. It amounts to a digital-age spin on the most basic principle of banking: Know your customer. Yet the technology is so new that the potential is unproved. Also, applying the modern techniques of data science to consumer lending raises questions, especially for regulators who enforce anti-discrimination laws. None of the new start-ups are consumer banks in the full-service sense of taking deposits. Instead, they are focused on transforming the economics of underwriting and the experience of consumer borrowing — and hope to make more loans available at lower cost for millions of Americans. Earnest uses the new tools to make personal loans. Affirm, another start-up, offers alternatives to credit cards for online purchases. And another, ZestFinance, has focused on the relative niche market of payday loans. They all envision consumer finance fueled by abundant information and clever software — the tools of data science, or big data — as opposed to the traditional math of creditworthiness, which relies mainly on a person’s credit history. Investors certainly see the potential; money and talent are flowing into this emerging market. Major banks, credit card companies and Internet giants are watching the upstarts and studying their techniques — and watching for the perils. By law, lenders cannot discriminate against loan applicants on the basis of race, religion, national origin, sex, marital status, age or the receipt of public assistance. Big-data lending, though, relies on software algorithms largely working on their own and learning as they go. The danger is that with so much data and so much complexity, an automated system is in control. The software could end up discriminating against certain racial or ethnic groups without being programmed to do so. The data-driven lending start-ups see opportunity. As many as 70 million Americans either have no credit score or a slender paper trail of credit history that depresses their score, according to estimates from the National Consumer Reporting Association, a trade organization. Two groups that typically have thin credit files are immigrants and recent college graduates. Affirm says it is on track to lend $100 million during its first 12 months. More than 100 online merchants are now using its installment loan product, Buy With Affirm. Next up, the company says, will be student loans. Earnest was founded in 2013, and began lending last year. In 2014, its loans reached $8 million, growing gradually. By December the month-to-month growth rate was 70 percent, Mr. Beryl said. The typical Earnest loan is for a few thousand dollars, though they can range up to $30,000. Many of the loans are for relocation expenses and for professional training.
- Big-data based lending story #2: Payday loans - where every borrower has poor history - attract big data models too, but fairness and discrimination concerns persist: The payday market is a niche compared with mainstream consumer and credit-card loans, two markets where start-ups are now applying data science to lending, as I wrote about in an article on Monday. Still, the payday market is a sizable niche. At any given time, there are an estimated 22 million payday loans outstanding, and the fees paid by payday borrowers amount to about $8 billion a year — a lot of money for those in the working population least able to afford it. Mr. Merrill saw a market in need of greater efficiency, a business opportunity — and the potential to lower costs to borrowers. ZestFinance has been practicing big data-style underwriting longer than most other start-ups. Founded in 2009, ZestFinance made its first loan in late 2010 and has increased its lending steadily since, having underwritten more than 100,000 loans. Its loans are called ZestCash, and the company is authorized to be a direct lender in seven states including Texas, Louisiana and Missouri. ZestFinance also handles the underwriting for Spotloan, an online lender that is part of BlueChip Financial, which is owned by the Turtle Mountain Band of the Chippewa Indian tribe of North Dakota. Winning over state regulators has been a slow process. “We’re showing up with a different kind of math,” said Mr. Merrill, who is now the chief executive of ZestFinance. “And that’s going to make it more difficult from a regulatory standpoint.” A healthy dose of caution is in order, policy analysts say. A recent report, by Robinson & Yu, a policy consulting firm, looked at new data methods as a way to make credit available to more Americans. In the report, supported by the Ford Foundation, ZestFinance was the featured example of big data underwriting, which it called “fringe alternative scoring models.” “I have no doubt that they have come up with neat correlations that are predictive,” said Aaron Rieke, co-author of the report and a former lawyer at the Federal Trade Commission. But the concern about ZestFinance and other start-up lenders using big data methods, Mr. Rieke said, is that “we have no idea how to talk about or assess the fairness of their predictions.” Mr. Merrill believes that such qualms will fade as data science lenders build a track record of offering lower costs and greater convenience to borrowers. The typical payday loan, Mr. Merrill explains, is for a few hundred dollars for two weeks, and rolls over 10 times on average, or 22 weeks. In a traditional payday loan, all the fees are paid upfront with the principal paid at the end, in a “balloon” payment. With ZestCash loans, borrowers are paying down principal with every payment, which reduces the cost. It also charges lower fees. In a traditional payday loan, Mr. Merrill said, a person would typically pay $1,500 to borrow $500 for 22 weeks. Using ZestCash, he says, a borrower generally pays $920 to borrow $500 for 22 weeks — still hefty fees, but far less than a standard payday loan. ZestFinance can charge less, Mr. Merrill said, largely because its data-sifting algorithms reduce the risk of default by more than 40 percent compared with a typical payday loan, and the software is being constantly tweaked to improve further. Borrowing candidates are asked to fill out an online form with their name, address, Social Security number, bank account information and a few other questions. ZestFinance then combines that with streams of information from data brokers and online sources, and sets its algorithms to work. The automated risk analysis, Mr. Merrill said, is done in a matter of seconds. The person is informed of the decision online. If approved, a customer service representative soon calls to verify the borrower’s identity, double check on numbers, and go through the loan terms again by phone. The data signals used to assess risk in the payday market are different than for most consumer loans. “In our space,” Mr. Merrill observed, “virtually everyone has a bankruptcy.” In payday underwriting, by contrast, signs of financial stability would include how long a person has had his or her current cellphone number or the length of time on a current job.
