An enjoyable read by Jeremy Birch, Peter Jones and Kyle Wombolt from Herbert Smith Freehills looking at how big data and data analytics is impacting investigations and compliance. The article takes a look at how predictive data analytics can be used to predict regulatory and compliance issues moving from detecting to predicting.
This is a very interesting topic and something that companies will need to get to grips with. Banks and financial institutions are probably at an advantage here, as these technologies have been used within financial crime to tackle AML and sanctions risk.
Companies need to continue to assess how best to use data and technology to tackle these sort of risks - specifically looking at not just 'human' designed tests around known threats but also using machine learning and artificial intelligence to identify previously unidentified risk.
Data is a vital element to any investigation or compliance exercise, just as it is to the operations of any business. One of the most fundamental aspects of managing data is to ensure that it is fully embedded within the investigation/compliance team – it can not be run on the periphery without negatively impacting the effectiveness and efficiency of the process. It has to be a core element.
Big data is rapidly changing the way in which regulators and law enforcement conduct an investigation and build a case. New technology reduces compliance costs, but also increases regulatory expectations of businesses' monitoring, detection and reporting capabilities. And, as technology evolves, monitoring for misconduct may soon involve predictive capability rather than merely detection. Meeting compliance expectations including due diligence on customers and suppliers, conducting internal investigations and managing government agencies during enforcement are all becoming more complex. More than ever, companies need to keep up with the technology to keep up with their regulators in an investigation.