Background
The financial services sector has experienced both crisis and huge change in recent years. This has led to regulatory burdens necessary for the management of systemic risk, which in turn has led to increased compliance challenges. Add to this the fact that the world’s data is doubling every two years and it is clear that the industry faces significant challenges.
The monitoring and regulation of systemic risk has become a major concern for regulators, governments and financial institutions. Managing ‘Big Data’ is a core part of this process and a challenge for the industry is therefore, how to use the breadth and depth of data available to both address the demands of regulators, but also improve services for customers.
Aims and Objectives
This half event embedded within the UCL Theory of Big Data conference (http://www.ucl.ac.uk/bigdata-theory/ ), aimed to address some of these issues through a series of talks from leading industry and academic experts. The focus will be on Big Data Analytics - the process of examining large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful business information. A major component of Big Data analytics is mathematics – the models and algorithms that are needed to extract knowledge from the data in order to maximise these insights.
A key objective of this event was to investigate the challenges and possible solutions for this area from a mathematical perspective specifically focusing on:
- Systemic risk
- Financial regulation
Experts delivered presentations on industry insights and state-of-the-art mathematical techniques for Big Data Analytics.
This event was of interest to participants from the financial services industry, including economists, regulators, risk professionals, and scientists from related disciplines.
Registration and Venue
The workshop took place at British Library, Euston Road, London. Please see the link for further information about the venue.
