Navigating personal data rights in an increasingly digital and machine world

Jeewon Kim Serrato, Marc Elzweig, Steven Lee and Andy Gandhi

Journal of Financial Compliance, 2018, vol. 1, issue 4, 357-363

Abstract: Data is the lifeblood of any modern organisation. Data also poses the fastest growing aspect of risk. Over the past few decades, the volume and types of data that are created and collected digitally and by machines have increased exponentially and distinctions have blurred between corporate and personal data. Particularly in the financial services industry, advances in how organisations collect, store and process large volumes of sensitive data make data an ever-growing asset and liability. Because questions can be expected on the quality of the underlying data or the fairness of the model, any data-driven initiative must be approached with caution and an understanding of the evolving regulatory landscape. This convergence — of exponential data growth, the introduction of new data types and processing capabilities, borderless transfers of data, and increasingly complex web of regulations — makes data risk a clear challenge for organisations and requires careful planning and execution. An integrated data risk management strategy is needed at the senior level of each organisation to strike a balance between extracting value from data and appropriately managing the associated risks. This paper explores the impact of advanced data analytics and artificial intelligence to data risk and offer key principles of a data governance programme for data-intensive projects in an increasingly digital and machine world.

Keywords: artificial intelligence; data risk; GDPR; privacy (search for similar items in EconPapers)
JEL-codes: E5 G2 K2 (search for similar items in EconPapers)
Date: 2018
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