Analytics Solutions for Monitoring Conduct Risk

Risk should be considered in any kind of decision process.  Even seemingly very simple decisions can have high risk.  So, this means they are not simple decisions after all.   Conduct risk, or how people: individuals or groups (or cognitive agents) act or react, is particularly difficult in today's networked world.  Or how regulation is a kinds of conduct.   Good piece addressing this, but not quite enough about how the context of conduct can also make a huge difference.  But good start here.

The advanced-analytics solution for monitoring conduct risk  in McKinsey

Advanced analytics and machine learning can help institutions “connect the dots” across customer and other data to detect conduct risk comprehensively and cost-effectively.

Advanced analytics and machine learning can help institutions “connect the dots” across customer and other data to detect conduct risk comprehensively and cost-effectively.

The fallout from highly visible instances of misconduct—including reputational damage, material losses, and increased regulatory focus—have led financial institutions to treat conduct risk as an important priority. As a risk category, however, conduct has proved difficult to monitor effectively with traditional controls and testing. The varieties of potential misconduct are numerous, and transgressing individuals or whole departments find ever-changing ways to circumvent rules. In addition, sample-based tests such as transactional reviews are not effective in finding isolated instances of misconduct.

Effective misconduct detection requires a new approach, one that can “connect the dots” across individual and team activities. These connections are often hidden in data that derive from multiple sources. They can be revealed by deploying advanced analytics and machine learning to mine the rich data and thereby identify incongruous sales or transaction patterns, misaligned incentives, and inappropriate customer interactions. Frequently underutilized records (such as the transcripts of customer interactions), can be automatically analyzed for potentially inappropriate treatment that customers may have experienced. But advanced-analytics solutions go beyond the detection of past instances of misconduct—by which the damage to an institution, if any, has already been done—to intercept the outlying patterns of activity that could lead to future losses.

What is conduct risk?

The definition of conduct risk varies somewhat by industry and region but can be commonly understood as individual or group actions that could cause unfair outcomes for customers, undermine market integrity, and damage the firm’s reputation and competitive position.

Conduct risk has only recently become recognized as a stand-alone risk category, in the aftermath of a number of high-profile incidents of misconduct (and regulatory responses) in retail and commercial banking, capital markets, and wealth management ....