Data Tipping Point.. Good things will happen

Recent issues with Facebook, Equifax, GDPR compliance, … have brought us to a tipping point in data. The basic structure of how data is: permissioned, shared, used, accumulated, analyzed, sold, regulated, … must change. Google and FB operate in a Big Data 1.0 architecture powered by the “virtuous cycle”. Edward Snowden showed us how the NSA also acts in this centralized model as a data vacuum (not so virtuously). Literature and entertainment have created broad awareness of the dangers of centralization and loss of privacy: 1984, the Borg, The Circle, Black Mirror, … etc.   Continue reading “Data Tipping Point.. Good things will happen”

Banks as a Data Business – Example Amex Advance/Acxiom

Traditionally the core of bank margin is in risk management. The core of risk management is data.. thus Banks have been the among the best data businesses (as IBM knows). Banks “learn” about their customers through bank interaction: payroll, card transactions, lending. This has helped banks make better risk decisions (both credit and fraud/identity). Within the bank data cycle the traditional use of data is for an internal benefit: risk and cross sale of the bank’s products and services (not that of consumers or merchants).  However the “virtuous cycle of banking data” is very different from that enjoyed by Amazon and Google, both in the scale and type of data and consumer facing use.  Continue reading “Banks as a Data Business – Example Amex Advance/Acxiom”