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Smart Homes In The U.S. Becoming More Common, But Still Face Challenges

4G/5G Densification To Push Global Small Cell Spend To $2 Billion By 2020

Energy

Power Forecast Briefing: Fleet Transformation, Under-Powered Markets, and Green Energy in 2018

Fintech Investors Pushed Stripe To Massive Valuation In September

Sears Strikes Out What Is In Store For Other Retailers In The US


Smart Homes In The U.S. Becoming More Common, But Still Face Challenges

Jun. 14 2017 — The following post comes from Kagan, a media research group within S&P Global Market Intelligence. To learn more about this research, please request a call

Despite the growing popularity of several smart home applications and products, the majority of U.S. homes still aren’t “smart.” 

Kagan, a media research group within S&P Global Market Intelligence, reports that the number of U.S. smart homes grew to over 15 million at the end of 2016. While this total equates to just 12.5% of total U.S. households, that percentage is forecasted to grow to 28% by 2021.

US smart homes as a percent of total u.s households

Smart homes have long existed on the edge of reality, something of a futuristic idea that appears to be close, but is always “two years away” from becoming big. However, with smart/connected products filling the shelves of both online and brick-and-mortar stores, the smart home has become real.

The smart home is also rapidly becoming a key component in the technology industry’s vision of the emerging Internet of Things, or IoT.

The current industry vision of an IoT-enabled world is one that creates a more convenient, secure, intelligent, and personalized experience. While this seems to be an achievable vision, the reality of IoT is sometimes different.

For example, in order to create real value, IoT has to solve real problems, not just connect a bunch of devices. Enter the smart home, which can meet the goal of creating real value for the user. At its best, the smart home can solve problems, create new efficiencies, and even save a consumer some money.

Market challenges and drivers

The drivers supporting the growth of the smart home market are broadly based on growing consumer awareness about the value of connected devices. More specifically, these drivers are:

  • An increasing consumer focus on home security. While home security concerns certainly aren’t new, many current security products and services weren’t possible without a broadband service or a mobile electronic device. Products and services such as IP security cameras, smart locks, and automatic notifications sent directly to your mobile phone are becoming integral parts of the smart home.
  • There is growing consumer awareness of the utility of smart hub products. Led by the explosive growth of Amazon’s Echo, smart hub devices such as Google Home and Samsung’s SmartThings Hub have moved beyond simply being smart speaker systems. These devices can now control other smart home products and are increasingly becoming the centerpiece of “do it yourself,” or DIY, smart home systems. 
  • Connected energy management devices now offer greater functionality. Demand for devices such as smart thermostats and smart lighting systems has increased markedly over the past two years, driven by both their money-saving capabilities and their easy-to-use reputation.

Market drivers smart home

On the other hand, the concept of the smart home is still viewed with a healthy dose of skepticism. Challenges that are holding back the smart home market include:

  • Defining the value proposition of the smart home remains problematic. Consumer surveys routinely show the skepticism of some homeowners about the real value of connected devices in the home. Frequently heard comments such as, “If I need to adjust the temperature in my home, I’ll do it manually,” and “Why would I ever need a smart doorbell?” underline the challenge of moving the smart home past the early adopter phase.
  • The price of both smart home service packages and some leading smart home devices are often viewed as too high for mass adoption. On the service provider side, support for smart home services usually requires an existing subscription to either a security service or a broadband service. Examples include Comcast charging $30 per month for its Xfinity Home service, while ADT pricing starts at $59 per month for its Pulse + Home Control package.

Market challenges smart home

On the device side, many products used in the smart home are generally perceived to be more reasonable than a smart home monthly service fee. Examples of leading product prices include the Amazon Echo at $50, the Nest Learning Thermostat at $250 and the SkyBell HD video doorbell at $199. Still, for many consumers, these prices can seem high for products often viewed as unnecessary.

  • One of the toughest problems faced by smart home advocates is security. Unlike the market driver that focuses on improving the physical security of the home, this challenge has to do with keeping the access to the home, personal information and data secure from illegal or unauthorized access.
  • With online access to everything from door locks to security cameras, many consumers are rightfully concerned about the vulnerability of these products to hackers. In September 2016, hackers managed to take control of over one million home video security cameras. This hack, which was generally limited to security cameras from a single vendor, received worldwide attention and publicity. It also served to highlight how challenging it is to convince many potential smart home adoptees that their connected devices will truly be secure.#learnMoreAbout("sector-intelligence-1") 
  • On the physical security side, a common fear is that smart locks or smart alarm systems can be bypassed or hacked. A leading security service executive recently mentioned that this issue was the second most common reason they hear as to why consumers refuse to sign up for an online security system (number one was price).
  • Another significant market challenge to the smart home is the overall usability and interoperability of connected devices in the smart home. This is especially true in a smart home not supported by a service provider, where a consumer might want to integrate a standalone smart thermostat from one vendor into to a smart home hub from a different vendor. It’s important to point out that just because a device is an internet-connected device, that doesn’t mean it will communicate with, or even work with, a different connected device.

The future of the smart home

At year-end 2016, we estimated there were just over 15 million households in the U.S. that met our definition of a smart home. By the end of 2017, we are projecting that total to increase to more than 20 million households.

Over the next several years, we are forecasting solid, but not meteoric, growth in the number of U.S. smart homes. Fueled by an expanding number of connected devices in the home, coupled with the desire to allow these devices to communicate and interoperate, we are projecting U.S. smart homes to exceed 35 million by 2021. 

US smart homes,2016-2021

Some notable elements of our smart home shipment forecast are:

  • The current base of smart homes in the U.S. falls into two categories: service provider-supported smart homes and DIY smart homes. The service provider category consists of homes supported by pay TV/telecommunications service providers, home security companies, and some home improvement retailers (i.e. Lowe’s, Home Depot) that offer or promote proprietary smart home platforms. The DIY category includes homes with multiple connected devices, meeting our definition of a smart home, but they do not rely on a service or platform provided by one of the companies in our service provider category.
  • In the U.S., the DIY smart home category is significantly larger than the service provider smart home category. Currently, the segmentation stands at approximately 70% DIY smart homes, 30% service provider smart homes. Much of this split is based on the cost, or perceived cost, of the smart home. A majority of consumers with smart homes seem to view the monthly subscription fees charged by service providers as being too expensive. This pushed them into relying on the DIY model for their smart homes.
  • There is some churn in the smart home market. Although the annual percentage is quite small, estimated in the 1% to 2% range, there are some consumers who either end their smart home service provider subscription or effectively “disconnect” their home.

Virtually all of the anecdotal stories we hear about these homes “going dumb” are based on three issues:

      • Security concerns
      • Service pricing
      • Unfulfilled expectations of the smart home

    While we are projecting the number of smart homes in the U.S. to increase significantly over the next few years, it is important to point out that they will still be a minority of total U.S. homes. In fact, in 2021 the number of “dumb” homes will still outnumber the number of smart homes by more than a two-to-one margin. 

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    Technology, Media & Telecom
    4G/5G Densification To Push Global Small Cell Spend To $2 Billion By 2020

    Highlights

    In 2023/2024, emerging markets will begin to see volume small cell deployments.

    Nov. 19 2018 — Global mobile operators are expected to rely heavily on small cells to dramatically improve network coverage in indoor locations, select metro areas, suburbs and rural and remote locations over the next five years. According to new research from Kagan, global small cell revenues are expected to grow to $2.4 billion in 2020, as mobile operators and enterprises look to improve the coverage of both 4G LTE and 5G networks in both indoor and outdoor environments.

    Total combined indoor and outdoor small cell revenue is expected to reach a peak in 2022, before declining in 2023 and 2024. Our expectation is that the bulk of initial small cell rollouts for 4G LTE and 5G densification will be complete by 2022, particularly those deployments throughout EMEA designed to enhance coverage and capacity for 4G LTE networks. We do expect a slight decline in revenue in 2019 as pricing on indoor small cell units decreases due to volume shipments. In 2023 and 2024, more emerging markets in CALA and Africa will begin to see volume small cell deployments. However, those deployments will be on a smaller scale when compared with larger markets, including the U.S., China, India and those of Western Europe.

    Small cells are low-power radio access points designed to complement and enhance existing macrocell locations. They can operate in both licensed and unlicensed spectrum bands and be deployed both indoors and outdoors and with multiple form factors. The largest of these devices are typically used in urban and rural outdoor locations and the smallest are reserved for indoor residential applications.
    There are three primary types of small cells:

    • Femtocells: small footprint, low-power devices designed to improve coverage in homes and small businesses. Femtocells can improve coverage gaps indoors, especially when signals originating from outdoor macrocells are unable to penetrate walls. Current femtocells support anywhere from four to eight mobile devices and have a range of 50 feet or less.
    • Picocells: base stations designed to cover a small area of around 700 feet or less. Picocells can be deployed both indoors and outdoors, with most being deployed indoors in shopping malls office complexes and train stations to add network capacity. Outdoor locations include stadiums and urban areas to improve network capacity and coverage. 
    • Microcells: typically have a range of around three miles, compared with macrocells, which have an average range of 22 miles. Microcells are used to add network capacity and coverage in outdoor locations, including dense urban areas, as well as rural and remote areas.

    This summary is from Kagan’s first article providing in-depth global coverage of mobile infrastructure technologies. It includes worldwide small cell locations by region, revenue and units forecast through 2024. Following this will be an article covering global distributed antenna systems, or DAS, also with forecasts through 2024.

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    Banking
    Fintech Investors Pushed Stripe To Massive Valuation In September

    Nov. 14 2018 — Stripe Inc.'s $245 million capital raise was the clear highlight of U.S. financial technology fundraising in the month of September, weighing in at more than four times the next-highest raise. Stripe's massive round even stood out in comparison to other sectors, ranking in the top 15 of all U.S. private placements during the month.

    The latest raise values Stripe, a payments company founded in 2009, at $20.25 billion on a post-money basis. The most recent valuation is a massive increase from November 2016, when a $150 million infusion valued the company at $9.15 billion. But on a percentage basis, an even bigger jump in valuation came from May 2012, when the company was valued at about $100 million, to January 2014, when its valuation skyrocketed to $1.75 billion.

    The Stripe tale is a classic tech story. With only seven lines of code, two brothers in their early twenties launched the company that now counts industry giants such as Amazon.com Inc., Alphabet Inc., Facebook Inc. and Microsoft Corp. as clients. Patrick and John Collison believed that PayPal Holdings Inc., one of the leading payments companies, was designed specifically for peer-to-peer transactions, rather than e-commerce, and that it was not built for scale, as they explained in a May episode of How I Built This. In response, they built a system that allows e-commerce companies to easily add payment functionality to their websites. For instance, an e-commerce company can add a button to its page that collects the customer's credit card information and sends it to Stripe for processing.

    Stripe was also unique in that it appealed to software developers. As a result, it could attract tech startups as customers that, while small at the time, would grow to become sizable institutions. This reputation in the developer community even led to companies approaching Stripe about creating new systems. For instance, ride-hailing company Lyft Inc., a loyal customer, specifically asked Stripe to help create an instant cash-out service for its drivers, according to a Recode article published in September 2016.

    Due to Stripe's large capital raise in September, the payments category ranked highest in terms of aggregate deal value among the six fintech categories that S&P Global Market Intelligence tracks. But based on number of transactions, financial media and data solutions was the leader.

    The financial media and data category includes companies such as Crux Informatics Inc., which helps institutions store and process data. San Francisco-based Crux, which was founded in 2017, has some big-name backers from the financial services world: Citigroup Inc., Goldman Sachs Group Inc. and, more recently, Two Sigma Investments LP. Of the three, Two Sigma would seem the most likely user, as a quantitative asset manager that, according to its website, crunches more than 35 petabytes of data. But Wall Street investment banks seem increasingly focused on tech as well. A recent article in the Financial Times, for instance, said that a fresh crop of analysts in JPMorgan Chase & Co.'s asset management division were required to complete coding lessons.

    No particular investor appeared to make an inordinately large amount of fintech investments during the month, but there were several institutions that made two investments.

    Stripe lined up a large number of investors — eight in total — which is not surprising given the size of the transaction. Meanwhile, OODA Health Inc. also managed to assemble a roster of eight investors for an offering that was about one-sixth the size of Stripe's. Founded in 2017, OODA Health aims to simplify and automate payments in the healthcare industry, using technology to help payers and providers collaborate on a better system. The investor list on its September capital raise demonstrates this effort to bring together both sides, with participation from health insurers and hospital systems alike.

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    Credit Analysis
    Sears Strikes Out What Is In Store For Other Retailers In The US

    Nov. 13 2018 — Recently, Sears Holdings Corp. (“Sears”) became yet another retailer in the U.S. that defaulted, and the firm filed for Chapter 11 on October 15, 2018. Similar to other retailers, this former giant could not keep pace with its more agile competitors in a fast-changing landscape. As reported by S&P Global Ratings,1 Sears’s default brings the annual corporate default tally in the U.S. to 37 as of October of this year, making the retail sector the largest contributor with eight defaults to date.

    Sears transformed how America shopped and was once the largest retailer and largest employer in the country. However, it gradually fell out of consumers’ favour, and online stores and big box rivals took the helm. Sears' last profitable year was in 2010, and rapidly declining sales and weak cash flow offered the company limited room to improve its operations. Sears dipped into its assets to fund ongoing operations, closing more than 3,000 out of its 4,000 stores between 2011 and 2018. However, continuously negative earnings and a high interest burden prevented Sears from going on without a reorganization. The company’s credit rating by S&P Global Ratings captured this gradual decline in credit quality, deteriorating from ‘A-’ in 2000 to ‘CCC-’ prior to default.2

    Only a limited number of companies have assigned credit ratings by a Credit Rating Agency (CRA), leaving out a significant part of the corporate universe. S&P Global Market Intelligence’s Credit Analytics suite includes a range of statistical tools that facilitate an efficient and cost-effective evaluation of a company’s credit quality by generating credit scores3 for both rated and unrated corporates globally. PD Model Fundamentals (PDFN) is a quantitative model that utilizes both financial data from corporates and the most relevant macroeconomic data available to generate probability of default (PD) values over a one- to more than 30-year horizon for corporations of any size. The numerical PD values can be mapped to S&P Global Market Intelligence credit scores (e.g. ‘bbb’), which are based on historical observed default rates extracted from the S&P Global Ratings’ database (available on CreditPro®).

    In the analysis that follows, we review the credit risk landscape of retailers in the U.S., and explore which risk factors are the main drivers of PD. We then take a look down the road and assess how possible future macroeconomic scenarios may impact the credit risk of retailers in the U.S.

    U.S. Retail Landscape

    By leveraging PDFN, we can broaden the view beyond the realm of the CRA-rated universe. Figure 1 shows the distribution of implied credit scores obtained using PDFN for U.S. public retail companies. From 2013 to 2018, the distribution of the credit scores has been gradually shifting toward lower credit scores. In this period, the average credit score shifted from ‘bb+’ to ‘bb’, whilst the percentage of companies in the speculative credit score category (credit score ‘bb+’ and below) increased from 60% to 74%. These trends are symptoms of a change in the risk profile of the U.S. retail industry, which resulted in the bankruptcy of several other big retailers (e.g., Toys “R” US, Inc., RadioShack Corp., and The Bon-Ton Stores, Inc.).

    In the second quarter of 2018, 45% of companies in our sample had been assigned a credit rating by S&P Global Ratings. Importantly, whilst a majority (76%) of companies in the investment grade universe do have a CRA rating, the speculative grade is largely unaddressed, with only 35% of companies in our sample having been assigned a credit rating by S&P Global Ratings. The use of statistical models, such as PDFN, assists investors in expanding the analysis and providing a comprehensive overview of credit risk across a wider universe.

    Figure 1: Distribution of PDFN credit scores for public companies in the retail sector in the U.S.

    Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
    Notes: Public companies in the retail sector in the U.S. (GICS® 2550 and 3010). Distribution of companies based on PDFN credit scores calculated using the latest financial data for each respective period.

    Drivers of Default

    We further explore which risk factors are the main contributors of the PD for the retail sector. Credit Analytics’ models are equipped with tools, such as contribution analysis, which helps users identify drivers of risk in absolute or relative terms. These tools assess the “weight” or importance of the contribution of each risk factor to the credit risk estimate.

    We divide the companies in deciles based on their PD and construct financial ratios for a median company in each decile. Next, we calculate PDs for each median company and evaluate associated absolute contributions of each risk factor.

    Figure 2 shows the absolute contribution of each risk factor for a median retail company, a median retail company in the top decile, and a median retail company in the bottom decile. Note that absolute contributions for each company add to 100% to facilitate comparability, however, their nominal values are scaled by PD values and are, thus, markedly different.

    Figure 2: Overview of absolute contribution of credit risk drivers for public companies in the retail sector in the U.S.

    Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
    Notes: Public companies in the retail sector in the U.S. (GICS® 2550 and 3010).

    Efficiency and profitability represent important drivers of PD, directly reflecting an operating environment of low margins in the retail sector. Together with company size, these three risk factors represent roughly 50% of the PD value. In addition, low margins also limit available funds to respond to unexpected expenses and investment opportunities, resulting in restricted financial flexibility. However, the current macroeconomic environment for retail companies in the U.S. is favourable, and represents a small part of the PD value. On average, these companies have sustainable capital structures and sufficient liquidity, resulting in the limited contribution of these factors to PD.

    For retail companies with high credit risk (bottom decile denoted in red in Figure 2), the company size, whilst still important, is no longer the only dominant factor. Factors like profitability, sales growth, and debt service capacity grow in importance and represent key factors when determining the credit quality of riskier retail companies.

    View Down the Road

    Next, we review how future economic scenarios may impact the credit risk of the public companies within the U.S. retail sector from a systematic point of view. The Credit Analytics Macro-Scenario model enables risk managers and analysts to gauge how a firm’s credit risk may change across both user-defined and pre-defined forward-looking scenarios, based on a set of macroeconomic factors. The model is trained on S&P Global Ratings’ credit ratings and leverages the historical statistical relationship observed between changes in credit ratings and corresponding macroeconomic conditions to explore what future scenarios may look like.

    In Figure 3, we analyse the impact of different macroeconomic scenarios on companies with various credit scores. We depict relative changes in PD to directly demonstrate, in numerical terms, the impact on the expected loss calculation and, in turn, credit risk exposure. As a baseline prediction, we apply macroeconomic forecasts for the U.S. in 2019, developed by economists at S&P Global Ratings. We observe an increase in one-year PDs across all credit scores, suggesting a possibility of further deterioration of creditworthiness in the U.S. retail sector. Additionally, we evaluate the influence of two downturn scenarios: a mild recession scenario and a global recession scenario, which are based on economic trends during the early 2000s recession and the great recession of 2008, respectively. The downturn scenarios show proportionally larger increases in PDs, in accordance with the severity of each recession scenario.

    Figure 2: Relative change of PD in the retail sector in the U.S. under various macroeconomic scenarios

    Source: S&P Global Market Intelligence (as of October 22, 2018). For illustrative purposes only.
    Notes: Macro-Scenario model captures the average tendency of all companies with the same creditworthiness profiles to transition to a different creditworthiness level (or remain at the same level) under a given macroeconomic condition, and does not take into account company-specific characteristics.

    S&P Global Market Intelligence’s Credit Analytics suite helps users unlock relevant credit risk information to perform an overview of a company’s creditworthiness and undertake an insightful deep-dive analysis. All model inputs can be easily adjusted to perform sensitivity analysis for selected financial ratios, or to conduct a stress-test exercise using a fully-adjusted set of financials. The Macro-Scenario model integrates with standalone credit risk models and provides a forward-looking tool to help support expected credit loss calculations required by the new accounting standards: International Financial Reporting Standards 9 (IFRS 9) and the Financial Accounting Standards Board’s (FASB) Current Expected Credit Loss (CECL).

    S&P Global Market Intelligence leverages leading experience in developing credit risk models to achieve a high level of accuracy and robust out-of-sample model performance. The integration of Credit Analytics’ models into the S&P Capital IQ platform enables users to access a global pre-scored database with more than 45,000 public companies and almost 700,000 private companies, obtain PD values for single or multiple companies, and perform a scenario analysis.

    1 S&P Global Ratings: “Default, Transition, and Recovery: The Global Corporate Default Tally Jumps To 68 After Two U.S. Retailers And One Russian Bank Default This Week”, October 18, 2018.
    2 S&P Global Ratings: “Credit FAQ: Credit Implications Of Sears Holdings Corp.'s Bankruptcy Filing For Retailers, REITs, CMBS, And Our Recovery Analysis”, October 17, 2018.
    3 S&P Global Ratings does not contribute to or participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence credit model scores from the credit ratings issued by S&P Global Ratings.
    4 Numbers as of September 15, 2018.

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    Credit Analytics Case Study Poundworld Retail Ltd

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    Credit Analytics Case Study The Bon-Ton Stores, Inc

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