Two Decades of Laws and Practice Around Screen Scraping in the Common Law World and Its Open Banking Watershed Moment
30(1) Washington International Law Journal (2020)
35 Pages Posted: 13 Jan 2021
Date Written: July 1, 2020
Screen scraping — a technique using an agent to collect, parse, and organize data from the web in an automated manner — has found countless applications over the past two decades. It is now employed everywhere, from targeted advertising, price aggregation, budgeting apps, website preservation, academic research, and journalism, to name a few. However, this tool has raised enormous controversy in the age of big data. This article takes a comparative law approach to explore two sets of analytical issues in three common law jurisdictions, the United States, the United Kingdom, and Australia. As the first step, this article maps out the trajectory of relevant laws and jurisprudence around screen scraping legality in three common law jurisdictions — the United States, the United Kingdom, and Australia. Specifically, the article focuses on five selected issue areas within those jurisdictions — “digital trespass” statutes, tort, intellectual property rights, contract, and data protection. Our findings reveal some level of divergence in the way each country addresses the legality of screen scraping. Despite such divergence, one may see a sea change amid the trend of data-sharing under the banner of “Open Banking” in coming years. This article argues that to the extent that these data sharing initiatives enable information flow between entities, it could reduce the demand for screen scraping generally, thereby bringing some level of convergence. Yet, this convergence is qualified by the institutional design of data sharing schemes — whether or not it explicitly addresses screen scraping (as in Australia and the United Kingdom) and whether there is a top- down, government-mandated data-sharing regime (as in the United States).
Keywords: Screen Scraping; Open Banking; Data Sharing; PSD II; Consumer Data Right; Smart Data
JEL Classification: K22; K10; K13
Suggested Citation: Suggested Citation