Digital Risk Management & AI: Mining Risk From Disparate Data

In today’s global economy, businesses’ technology portfolios are increasingly complex, varied, layered, accretive and expensive to acquire and maintain. Most businesses are becoming digital, even those who produce physical, retail goods and maintain a brick-and-mortar presence. On the flip side, many companies born online are establishing physical facilities, complicating their technology portfolios. This introduces the added complexity of public-facing interfaces, vendor-credentialed or open APIs, and content delivery networks (CDNs) in multiple global locations with cache.

These factors are compounded by external forces such as new regulations around privacy, the press for environmental, social and governance (ESG) compliance and increasing threats of cybercrime. Add in the proliferation of professional productivity platforms like Microsoft Office, its competitors, team collaboration, bring-your-own-device (BYOD) policies, email, file stores, virtual conferencing, hosting, code repositories and anything else that takes an attachment or upload. On the other side, the majority of customers are now fully immersed in the digital world, and expect their trade to be accommodated anywhere, everywhere, and anytime.

Underneath it all, there is a plethora of disparate data sources and infrastructure, including hybrid hosting. While AI is generally incapable of human heuristics, its statistical reasoning capabilities makes it good at discovery in mountains of data.

In this paper, we will focus on how AI can be used to identify risk from low-level data layers. We will also introduce some processes to manage the jetsam and funnel leads into an operational queue for CISO, CCO and IT security teams to investigate.

Download the white paper to learn more.