11/21/2019 - Task Force on Financial Technology: Banking on Your Data... - (EventID=110251)

Thursday, November 19, 2019 (9:30 AM) -- Hearing: "Task Force on Financial Technology: Banking on Your Data: the Role of Big Data in Financial Services" Connect with the House Financial Services Committee Get the latest news: https://financialservices.house.gov/ Follow us on Facebook:   / financialdems   Follow us on Twitter:   / fscdems   ________________ This will be a one-panel hearing with the following witnesses: • Ms. Lauren Saunders, Associate Director, National Consumer Law Center • Dr. Seny Kamara, PhD., Associate Professor of Computer Science, Brown University and Chief Scientist, Aroki Systems • Dr. Christopher Gillard, PhD., Professor of English, Macomb Community College and Digital Pedagogy Lab Advisor • Mr. Don Cardinal, Managing Director, Financial Data Exchange (“FDX”) • Mr. Duane Pozza, Partner, Wiley Rein Overview Today it is easy and inexpensive for companies to collect, store, process, and sell data, regardless of the data’s size, type, or location. The vast amounts of consumer information and data collected and stored by financial institutions, data aggregators, and cloud providers, among others, is commonly referred to as “big data.” The “big” in big data refers to the size, complexity, and newness of any given data set; big data is key for product development because it can be used to generate insights, support decision making, and enable automation. Notably, big data and cloud computing are often used interchangeably, but that is technically inaccurate. As discussed in a recent hearing, cloud computing is about computer resources (servers and applications), whereas “big data” refers to the computing resources used by datasets (primarily storage and automation). Big data is not unique to any one industry because it is typically comprised of data sets from all industries. However, the four basic concepts to processing big data across all industries are: volume, velocity, variety, and variability. 1. Volume refers to the size of a data set (as large as terabytes and petabytes) and grows when users generate and submit points of data, an example is a Facebook data feed. 2. Velocity refers to the flow of data coming into and being processed by an algorithm or information technology (“IT”) system. This stream can be delayed or happen in near or real time, including, for example, a large merchant’s transaction data feed. 3. Variety refers to the different types of incoming data into a dataset and can take the form of text, audio, and video. It can also refer to the source of a data set like data scraped from a website and/or data from a partner database. 4. Variability, while not a common characteristic of big data, acknowledges that big data sets are often scalable and can rapidly change with respect to the first three characteristics. A data set at any time may grow or shrink in volume, flow at different velocities, and include different varieties of data. The increased use of big data in financial services has led to the rapid development of new products and services. Often at the forefront of the development of most new products and services in financial services are data aggregators; partly because of their ability to rapidly capture huge swarths of data from multiple sources and compile the data into a standardized and summarized form for sell to investors and other entities. 7As discussed in a recent hearing on alternative data, this is often achieved through web scraping (extracting data from websites without a direct relationship with the website or financial firm maintaining the data) or through application program interfaces (“APIs”), which provide data aggregators access through negotiated agreements and can provide consumers more control. Big technology firms have increasingly explored and entered the financial marketplace, while being subjected to an unclear legal framework compared to financial institutions, and the platforms and consumer data they maintain have been utilized for credit underwriting, discriminatory housing advertisements, and other purposes. Regulating and Protecting Big Data The primary laws regulating the use of data in financial services at the federal level are the Gramm-LeachBliley Act (“GLBA”), which imposes data protection and notice requirements on financial institutions, and the Fair Credit Reporting Act (“FCRA”), which covers the collection and use of data related to credit reporting. Another notable provision of federal law is Section 1033 of the Dodd-Frank Wall Street Reform and Consumer Protection Act (“Dodd-Frank”), which requires the Consumer Financial Protection Bureau (“CFPB”) to issue rules regarding how consumers access their information from financial institutions. The CFPB has not issued rules under this provision, but instead has provided nine Consumer Protection Principles to help... Hearing Page: https://financialservices.house.gov/c...