We often hear the complaint that a company can't utilize analytics in a compliance department because so much of its compliance program is "paper-based." But here are some of the opportunities that risk and compliance professionals can evaluate within their organization to integrate technology into their compliance program:

Robotization and workflow optimization. Compliance, especially within insurance companies, inevitably involves a high degree of process. An organization cannot certify which executives have been trained, which whistleblower reports have been investigated, which policyholders or third parties have been vetted without tracking and monitoring. If done well, automation can simultaneously remove mundane workflows and allow compliance to focus on the trends and pattern analysis that drive meaningful decision-making.
Mobile. According to the research site Statista, there are more than 6 billion smartphone users worldwide in 2021. We predict that as training becomes increasingly mobile, those who can capture attention and communicate in a memorable way that translates well to a mobile device will have significantly more lasting power.
Identifying relevant data sets. Traditional compliance assessments in insurance tend to focus on the extent to which a business is regulated, the jurisdictions in which it operates and the financial control environment, to name a few. Organizations that are investing in artificial intelligence will be investing in improving the data hygiene of their systems, particularly concerning how a company pays third parties or tracks sales to customers or distributors. Compliance insights do not need to come solely from compliance department data — in fact, in almost all cases, it is more insightful for business risks if it does not. For example, the data sets that a revenue management function would find desirable to review sales margins are the same data sets that would yield insights into fraud and abuse for compliance.

The advent of unsupervised learning

With so many companies looking at digital transformation and technology initiatives to reduce costs and seek competitive advantages, the continued buzz around artificial intelligence, particularly around the subset focused on machine learning, is an important element to understand and apply when seeking to enhance your risk and compliance monitoring functions. Specifically, the advent of unsupervised machine learning in compliance is particularly relevant given the conspicuous and hidden nature of fraud and corruptions schemes. But first, it is important to understand the differences between supervised versus unsupervised learning.

Special Reports /

Blending data & technology to improve compliance

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