Residential proxies are the tool that most major web scraping vendors use to make scraping requests appear as if they're coming from genuine users, in their homes. These proxies use real IP addresses assigned to home computers or smartphones (rather than datacenter IPs) to increase anonymity and reduce the risk of being blocked by a website.

How are these web scraping vendors acquiring their vast networks of residential proxies?

In the first month of the new administration in the United States, the federal government has changed course sharply and made headlines with firings, buyouts, and a complete halt of operations at the Consumer Financial Protection Bureau. Regulated businesses are left guessing as to longer-term plans for priorities in regulating AI development, data collection, cybersecurity, and more. And DOGE's attempts to access sensitive Treasury and IRS data is prompting renewed calls for a national privacy law.

There seems to be a new world order – but what will it mean for organizations that depend on emerging technology?

Read Business Insider’s coverage of the litigation between YipitData and M Science, which features comments from Glacier.

It might be a sign of a maturing industry - the largest players in alternative data and investment research are now turning to the courts in the United States to enforce their intellectual property rights and check their competitors. Often smaller disputes are settled privately - whether through a phone call, a change in deal terms, or with the decision to end a business relationship. Increasingly, it seems that well-known providers of once-obscure data are willing to risk public scrutiny to protect their growing businesses. Perhaps this is not surprising as the data industry produces public companies and billion dollar valuations. But is it good for business?

Three cases in the alternative data industry represent the range of disputes that are inspiring litigators.

Data supply risk in 2024 can be characterized by two major themes: data companies operating at scale, and a rebalancing of the norms around commercializing user data. On the former, data and research companies are now subject to risks faced by mature companies, such as cybersecurity attacks, widespread adverse media, and survival at scale. With respect to norms around user data, artificial intelligence has reopened the debate on ownership, collection, and transformation of "public" data. Glacier expects that in 2025 we will see further consolidation and looser regulation in favor of data collection as the United States, the primary market for emerging tech, adapts to a new administration.

Cybersecurity regulation of data buyers is not well understood. As a result, it is often overlooked, as are cyber risks, despite the attention that individual breaches receive in the press and the resulting litigation. This post is not a summary of the current state of cybersecurity law, which includes the recent SolarWinds decision on July 18th, 2024 in the Southern District of New York (in which the court dismissed many of the Securities and Exchange Commission’s claims against SolarWinds). Instead, Glacier reviews some of the ways in which cybersecurity risk is underestimated by the data community and several steps to address it.

Web scraping presents a perplexing set of risks that fluctuate with developments in software, law, and business norms. These risks shift as use of the web becomes more automated overall. The current trend in major markets does track the anticipated growth of web scraping as an almost conventional means of accessing data, checked by click-wrap legal terms and access controls such as CAPTCHA. But site operators and scrapers are deploying less well-known tools to fortify those walls and to profit from the data they protect.

Current Federal Trade Commission leadership has used US antitrust law to rein in big tech platforms. This overarching trend is now impacting domestic data collection in a significant way. The FTC has algorithmic pricing and automated decision making (including artificial intelligence) in its crosshairs – as affected sectors of the economy (such as housing) also overlap with the White House’s policy agenda. Private class action litigation against data businesses is on the rise as well. For some data vendors, data quality and even the existence of popular products are now at risk.

Many organizations evaluate data vendors based on information provided directly by those vendors - either in marketing materials, demos, or third-party marketplaces. As costs rise and business dependencies increase, however, that approach is not sufficient to create a durable data supply chain.

There is significant demand for data in 2024, fueled by the adoption of new technology, particularly artificial intelligence. At the same time, regulators and lawmakers in major markets including the United States, UK, EU, and China have stepped up privacy controls to limit the collection and sale of data. There is a clear conflict between the nascent data market and national interests in protecting citizens' data and geopolitically sensitive information.

Many data users are concerned that alternative data brings significant potential risk if it relates to a public company and might qualify as material, non-public information (or "MNPI") under US law. This risk is understandably difficult to assess; a complete analysis of these terms of art (and their application to a particular dataset) requires sophisticated legal counsel. We do, however, also see some common misunderstandings among buyers and sellers of data on this topic, which may serve as a starting point in understanding this complex risk.

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