The assessment of data systems as they actually are, as opposed to what they were previously or are predicted to be, is arguably the paragon of contemporary analytics. Coupling this capability with machine learning enables organizations to not just make the right business decisions, but to capitalize on them in real-time. Achieving this ideal requires more than streaming platforms such as Kafka. The tooling doesn't just involve the right data science models, networking capabilities, or cloud providers. At some point, it comes down to the performance of the underlying database, particularly in regards to concurrency and scale.

The blossoming of fintech shows financial regulators need to update their tools, Rep. Patrick McHenry, possibly the next chair of the House Financial Services Committee, said today. Regulators need to start using Artificial Intelligence (AI) to adapt rules quickly to a rapidly changing financial system, a Republican Congressman who is often mentioned as the next possible head of the House Financial Services Committee said today. To meet the fintech challenge, Rep. Patrick McHenry (R-NC) also called for regulators to begin employing Big Data to develop strategies. "The basic way consumers are interacting with the banking system is fundamentally changing," said the Congressman. McHenry revealed he will be introducing a bill soon to bring financial regulation into the fintech era.