Plenty of Time to Get Compliance-AI Right

When will the company fall out of compliance, and why?

Artificial intelligence and machine learning continue to create a more significant media frenzy than BlackPink performing at Coachella!

All the noise from many globally intelligent people talking about slowing down AI so we can get our heads around what this automated robotic, non-human interaction, self-propelled, job-killing science is all about.

Until we figure that out, how about we turn the “pirate ship a hard left” and focus our brain power on a more pressing need; compliance-AI.

If you turned to my podcast yesterday, “CyberBlock and Chain with a Touch of Web 3.0,” I poked fun at the ENRON and Arthur Andersen scandal and compared it to the recent KPMG/SVB nightmare that is still unfolding.

For a moment, if SVB, the banker regulators, and the board of directors had an AI-powered Machine learning data crunching system letting them know months or even a year in advance, “because of current data trends, we will no longer comply with SOX, GLBA, PCI, and GDP if we continue to take these risks.”

I suspect SVB and other banks have invested heavily in data analytics to measure their investment risk strategy. However, what I believe is missing is when “human judgment,” including email communications or failure to hire a chief risk officer, these attributes should factor into the overall “risk of being non-compliance.” By taking telemetry from Cybersecurity, Risk Management, and Email Compliance alerts, including external DLP rule violations and other compliance findings, with the power of AI, this should create a pretty good dashboard for everyone to see.

What good will it do? Well, think about what is coming out about SVB and KPMG possibly going “old-school (DOT.COM) for a moment and buttering up the books to paint a clear and concise picture while the absolute truth is buried somewhere with an email or voice mail or maybe some other method of communication.

Natural Language Processing (NLP) would have a home here for years!

What is being said? Who said it? When was it said? What results came about? These questions yield more of the same risk-seeking culture with a greater reward.

In English, we call this “greed.”

How should organizations reconsider their AI investments in XDR, MXDR, DDR..etc.. and significantly invest in compliance AI?

There is never a good time or wrong time to change direction for the good of the organizations, investors, and employees.

Compliance AI can tell us more than what we want to know. And that is a good thing. We just want to ensure that more people see this “analysis” so “old-school” checks and balances can help prevent the subsequent “failure” and taxpayer bailout.