AxiomSL: All of my Intelligence is Artificial
Financial institutions sit on vast quantities of data, and many stakeholders require data submissions at ever-increasing frequencies — often daily. Data and business leaders are eager to implement technology innovations around artificial intelligence (A.I.), big data, cloud, machine learning, cognitive computing and intelligent data management. However, firms need to demonstrate return on data investment.
Leaders understand that just “kicking the tires” on new technologies won’t deliver the analysis they need to address major strategic decisions that will transition their businesses for future success. Applying A.I.-type capabilities to poor quality or poorly organized underlying data won’t yield the tempting results they are after.
How then can organizations position themselves to benefit from A.I.-type technologies?
Harry Chopra, Chief Client Officer at AxiomSL, will discuss how to define a data-quality foundation by applying a Service Level Expectations (SLE) orientation to the rivers of core data flowing through a financial institution’s lines of business. Using an SLE approach enables firms to create high-quality data objectives and pinpoint the interconnections among their datasets. Establishing a data-quality foundation enables firms to explore A.I.-type technologies to drive a business benefit.
Thus, it is best to be ‘artificially’ intelligent, before applying artificial intelligence.