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This year saw emerging risks posed by AI , disastrous outages like the CrowdStrike incident , and surmounting software supply chain frailties , as well as the risk of cyberattacks and quantum computing breaking todays most advanced encryption algorithms. Of these, AI is at the top of many CIOs minds.
Pörschmann highlighted at the beginning of the series, data governance works best when it is strongly aligned with the drivers, motivations and goals of the business. The businessdrivers and motivation should be the starting point for any data governance initiative. RiskManagement and Regulatory Compliance.
IBM’s Enterprise Cloud for Regulated Industries Building on our expertise working with enterprise clients in industries such as financial services, government, healthcare and telco, we saw the need for a cloud platform designed with the unique needs of these heavily regulated industries in mind.
ManageRisk Better (aka underwriting and adjusting). And that while some of these will require an investment in technology, that investment should be framed in terms of those businessdrivers. On the riskmanagement front, we have begun working with some insurers to automate underwriting and pricing.
Combined, it has come to a point where data analytics is your safety net first, and businessdriver second. Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and riskmanagement.
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