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Cyber Attacks on U.S. Companies in 2014

October 29, 2014 Comments off

Cyber Attacks on U.S. Companies in 2014
Source: Heritage Foundation

The spate of recent data breaches at big-name companies such as JPMorgan Chase, Home Depot, and Target raises questions about the effectiveness of the private sector’s information security. According to FBI Director James Comey, “There are two kinds of big companies in the United States. There are those who’ve been hacked…and those who don’t know they’ve been hacked.”

A recent survey by the Ponemon Institute showed the average cost of cyber crime for U.S. retail stores more than doubled from 2013 to an annual average of $8.6 million per company in 2014. The annual average cost per company of successful cyber attacks increased to $20.8 million in financial services, $14.5 million in the technology sector, and $12.7 million in communications industries.

This paper lists known cyber attacks on private U.S. companies since the beginning of 2014. (A companion paper discussed cyber breaches in the federal government.) By its very nature, a list of this sort is incomplete. The scope of many attacks is not fully known. For example, in July, the U.S. Computer Emergency Readiness Team issued an advisory that more than 1,000 U.S. businesses have been affected by the Backoff malware, which targets point-of-sale (POS) systems used by most retail industries. These attacks targeted administrative and customer data and, in some cases, financial data.

This list includes only cyber attacks that have been made known to the public. Most companies encounter multiple cyber attacks every day, many unknown to the public and many unknown to the companies themselves.

The data breaches below are listed chronologically by month of public notice.

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Cyber Attacks Likely to Increase

October 29, 2014 Comments off

Cyber Attacks Likely to Increase
Source: Pew Research Internet Project

Experts believe nations, rogue groups, and malicious individuals will step up their assaults on communications networks, targeting institutions, financial services agencies, utilities, and consumers over the next decade.

Explaining Health Care Reform: Questions About Health Insurance Subsidies

October 29, 2014 Comments off

Explaining Health Care Reform: Questions About Health Insurance Subsidies
Source: Kaiser Family Foundation

Good health insurance can be expensive, and is therefore often out of reach for lower and moderate income families, particularly if they are not offered health benefits at work. To make coverage obtainable for families that otherwise could not afford it and to encourage broad participation in health insurance, the Affordable Care Act (ACA) includes provisions to lower premiums and out-of-pocket costs for people with low and modest incomes. The adequacy of this assistance will be a key determinant of how many people ultimately gain coverage and whether or not lower-income people will be able to use the health insurance they obtain.

This brief provides an overview of the financial assistance provided under the ACA for people purchasing coverage on their own through health insurance Marketplaces (also called exchanges). In addition to offering financial assistance to some people purchasing their own private coverage, the ACA also gives states the option to bolster public coverage by expanding their Medicaid programs to cover people with incomes under 138% of the Federal Poverty Level (FPL). While this brief focuses on the premium tax credit and cost-sharing subsidies for marketplace enrollees, expanded coverage for low income people through Medicaid and new tax credits for small businesses are addressed in other reports.

Determinants of Households’ Investment in Energy Efficiency and Renewables: Evidence from the OECD Survey on Household Environmental Behaviour and Attitudes

October 29, 2014 Comments off

Determinants of Households’ Investment in Energy Efficiency and Renewables: Evidence from the OECD Survey on Household Environmental Behaviour and Attitudes
Source: OECD

Many studies on household energy efficiency investments suggest that a wide range of seemingly profitable investments are not taken up. This paper provides novel evidence on the main factors behind consumer choices using the OECD Survey on Household Environmental Behaviour and Attitudes. The empirical analysis is based on the estimation of binary logit regression models. Empirical results suggest that households’ propensity to invest in clean energy technologies depends mainly on home ownership, income, social context and households’ information. Indeed, home owners and high-income households are more likely to invest than renters and low-income households. On the other hand, social context, such as membership in an environmental non-governmental organisation, and households’ knowledge about their energy spending and use may play a relevant role in technology adoption.

New Report: Spending Per Privately Insured Grew 3.9% in 2013, as Falling Utilization Offset Rising Prices

October 28, 2014 Comments off

New Report: Spending Per Privately Insured Grew 3.9% in 2013, as Falling Utilization Offset Rising Prices
Source: Health Care Cost Institute

Privately insured Americans spent more on medical services in 2013 even though they used fewer of them, according a new report by the Health Care Cost Institute. Spending per enrollee in employer health plans grew by 3.9%, continuing the moderate growth trend that began in 2010. But falling utilization helped mask continued growth in health care prices.

In the 2013 Health Care Cost and Utilization Report—an annual study of health care price and utilization trends for Americans younger than age 65 participating in employer health plans—HCCI finds that health care spending averaged $4,915 per enrollee in 2013, up $185 from the year before.

Out-of-pocket costs, including co-payments and deductibles paid directly by consumers, remained stable as a percentage of overall health spending. A companion issue brief, Out-Of-Pocket Spending Trends (2013), details these trends by demographic groups and service category.

FTC sues AT&T for limiting “unlimited data”

October 28, 2014 Comments off

FTC sues AT&T for limiting “unlimited data”
Source: Federal Trade Commission

“Unlimited data” sounds great, right? Browse the Internet, stream videos, use GPS, even make video calls – all to your heart’s content. But what if you bought an unlimited data plan and then weren’t able to do all those things? That’s what happened to some AT&T customers.

From 2007 until 2010, AT&T offered unlimited data plans for smartphones. Even after it stopped offering unlimited data, AT&T allowed customers who already had unlimited plans to renew them.

But here’s the catch: AT&T then began slowing the data speed for “unlimited” customers who used large amounts of data. As a result, those customers with “unlimited” plans no longer had the bandwidth to do everything they wanted to do on their phones. That’s called data throttling.

Data throttling isn’t always illegal, but when it’s done in a way that’s deceptive or unfair, it most certainly is.

Measuring Price Discrimination and Steering on E-commerce Web Sites

October 28, 2014 Comments off

Measuring Price Discrimination and Steering on E-commerce Web Sites (PDF)
Source: Northeastern University

Today, many e-commerce websites personalize their content, including Netflix (movie recommendations), Amazon (product suggestions), and Yelp (business reviews). In many cases, personalization provides advantages for users: for example, when a user searches for an ambiguous query such as “router,” Amazon may be able to suggest the woodworking tool instead of the networking device. However, personalization on e-commerce sites may also be used to the user’s disadvantage by manipulating the products shown (price steering) or by customizing the prices of products (price discrimination). Unfortunately, today, we lack the tools and techniques necessary to be able to detect such behavior.

In this paper, we make three contributions towards addressing this problem. First, we develop a methodology for accurately measuring when price steering and discrimination occur and implement it for a variety of e-commerce web sites. While it may seem conceptually simple to detect differences between users’ results, accurately attributing these dfferences to price discrimination and steering requires correctly addressing a number of sources of noise. Second, we use the accounts and cookies of over 300 real-world users to detect price steering and discrimination on 16 popular e-commerce sites. We find evidence for some form of personalization on nine of these e-commerce sites. Third, we investigate the effect of user behaviors on personalization. We create fake accounts to simulate different user features including web browser/OS choice, owning an account, and history of purchased or viewed products. Overall, we find numerous instances of price steering and discrimination on a variety of top e-commerce sites.

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