The Practical Application of Artificial Intelligence and Deep Learning: The Finance Vertical - AnalyticsWeek

Artificial intelligence (including myriad subsets such as deep learning, machine learning, natural language processing and others) has maintained an enduring relevance in the contemporary IT landscape because of its novelty, its potential, and even its intrigue. Today, these facets of artificial intelligence are more than just'cool'--they represent a tangible means of increasing the ROI for data management infrastructure in that most objective of vertical industries: finance. "I think we've reached a turning point where there's this realization that for all the text and imaging that you're able to sift through with AI, there are people who have to sift through 400 pages of day," indico CEO and co-founder Slater Victoroff explained. Unstructured Data Deep learning can profoundly influence the productivity and efficacy of financial analysts in numerous ways, the vast majority of which pertain to gleaning insight from unstructured data. The appositeness of unstructured data in the financial vertical should not be underestimated, particularly for companies looking to make or monitor investments in any number of segments of this industry.