"Regulators can improve their analysis of systemic risks and provide a more holistic view through a better understanding of gaps in their data and by joining up with data from other regulators and employer organisations."
CONRAD THOMPSON, PA regulation EXPERT
To remain at the forefront of effective and efficient regulation, regulators must be able to spot trends and identify and deal with the major risks in their sectors. Yet the growing volume and increasing complexity of data available make this more and more difficult. In a society communicating via social media for both business and pleasure, vast quantities of information are now available in the public domain via the web.
How can regulators decide where best to focus regulation, and how can they move fast enough to obtain accurate information on which to act?
The answer lies in adopting a holistic, risk-based approach to data collection and analysis. By combining modern data collection techniques and innovative social intelligence derived from social media data with traditional forensic approaches that rely on expert insight, regulators can become more effective at identifying, confirming and addressing emerging issues in their sectors.
Traditional thematic reviews covering high-risk areas remain a good starting point for regulators aiming to assess and identify specific problems within firms, sectors or spheres of activity. For example, a thematic review by the UK's financial services regulator identified a problem with payment protection insurance products. The subsequent deeper regulatory investigation into industry practice identified widespread issues with sales and promotional practices, which has since led to over £1 billion being paid to consumers in compensation.
Regulators can improve their analysis of systemic risks and gain a more holistic view through a better understanding of gaps in their data and by joining up with data from other regulators and employer organisations.
These traditional approaches to regulation are increasingly being supplemented by sophisticated data collection techniques that gather data from social media. Activity on social media sites, whether this is disgruntled investors talking about interest rate swaps or householders complaining about dreadful service from their energy provider, can serve as a valuable early indicator of systemic problems that require the regulators' attention.
Managed with suitably developed applications, the predictive capability of social media, has huge potential for regulators. Social intelligence modelling can target specific conversational themes online to provide either a prediction of a developing issue or reveal a problem that has already materialised and is attracting attention on blogs and Twitter, for example.
This type of predictive modelling can be used as an aid to preventative action or a tool to enable regulators to verify the existence of a suspected issue. Regulators can then supplement this insight with traditional investigative techniques to identify potential parties to the issue and formulate the optimal response.
Regulators operate in markets where they increasingly find themselves in the spotlight and under scrutiny to provide effective regulation combined with value for money. Making use of sophisticated data-driven techniques should enable them to become even more effective whilst still maintaining good control over costs.