forecasting future opportunities and risks is the most prominent application of regression analysis in business. How it's using AI in finance: Kensho provides machine intelligence and data analytics to leading financial institutions like J.P. Morgan, Bank of America, Morgan Stanley and S&P Global. Here are just four of the many ways predictive analytics can help finance teams move their companies ahead of the competition. I am consulting in the aforementioned domain for a couple of years now, specifically Business process improvement in capital markets practice. Takeaways for Business Leaders in Finance Based on the companies we researched for this report, it seems as though predictive analytics applications in finance seem to have the most traction. Now, this particular sub-vertical requires a relatively deeper domain knowledge. The banking sector is the largest investor in service based analytics. With Risk analytics and management, a company is able to take strategic decisions, increase trustworthiness and security of the company. However, demand is not the only dependent variable when it comes to business. Demand analysis, for instance, predicts the number of items which a consumer will probably purchase. Application of Data Science in Finance Industries 1. Risk Analytics is one of the key areas of data science and business intelligence in finance. Risk Analytics. Kensho’s software offers analytical solutions using a combination of cloud computing and natural language processing (NLP). You will explore techniques to analyze time series data and how to evaluate the risk-reward trade off expounded in modern portfolio theory. Predictive Analytics: Predictive analytics i.e. Sharpening online revenue projections. The disciplines of big data analytics and banking have shared a keen bond from the very beginning. Data analytics drive virtually every aspect of the insurance business today, from premium pricing and customer experience to claims management and fraud prevention. This course introduces an overview of financial analytics. 1. You will learn why, when, and how to apply financial analytics in real-world situations. 1. A sturdy analytics framework can detect any discrepancy in the processes way faster, thus decreasing the risk. Using data on how customers navigate through a website, predictive analytics can help online retailers identify the site paths most likely to lead to a sale or abandoned cart. BFSI and the analytics industry. Offered by University of Illinois at Urbana-Champaign.