Big data is rapidly changing the way in which regulators and law enforcement conduct an investigation and build a case. New technology reduces acquiescence costs but also increases regulatory expectations of businesses monitoring detection and reporting abilities. As technology evolves, monitoring for misconduct may soon involve predictive capability rather than merely detection. Regulators are now relying on advanced analytics and machine learning to spot doubtful patterns within and between data sets. ASIC (Australian Securities and Investments Commission), and others are introducing artificial intelligence to review product disclosure statements to identify pointers of misleading statements during regulatory review. This raises many important questions for an employer in how should they use, share, record or report that information. The employer will need to decide whether the employee should be told about their status, or whether any due process should be triggered by that classification. Better data and analytics will improve third-party due diligence – spotting red flags that weren’t previously possible and minimizing false positives. Government agencies and companies collaborating with law enforcement are changing the way matters are investigated and cases are built. The ability to produce a combined view of evidence using multiple data sources is becoming more valuable. The US and UK are leading the charge in developing a network of more extensive cross-border data request powers for law enforcement, to avoid delays in criminal investigations.