Big data rules and regulations should be enhanced and updated by state and federal legislators simply because big data analytics across all industry sectors is important to improve efficiency. In general, big data analytics is used to predict consumer behaviors so they can be targeted by commercial organizations. This information can be gathered when, for example, the consumer visits an e-commerce website and purchases items. Also, information can be obtained when a consumer applies for a loan through a mortgage lender or financial institution.
Information security is important because in most cases the consumer is not aware that his or her information has been shared, transferred, or sold to another company. Again, the information is used to predict a consumer’s future behavior. The third-party that has access to the consumer’s information can use it to predict that person’s financial capabilities.
First, confidentiality of the information, whether it’s at rest, transit, or use, is crucial. Financial institutions have been targeted by hackers for misconfiguring and mismanaging network vulnerabilities over the years. The failure of using preventive measures such as data encryption plays a key role in this discrepancy. It is challenging to protect large amounts of information that’s in use because it depends on shared computing environments – i.e., wide-area-network that can go across cities or countries. Also, big data is processed on a continuous level that requires a tremendous amount of resources.