As the phrase goes, “everything that can be digitized, will be digitized”, is fast replaced by “If something can be run by algorithms, it will be”. Algorithms are supposed to be performing the following tasks: • Reading resumes: With natural language processing, resumes can be read faster and with more careful eyes. • Using spreadsheets: Soon the analysis made by experts using spreadsheets would be taken over by AI. • Hiring consultants: Since the analysis will all be done by algorithms, hiring consultants is really not needed as before. Hence, for coping up with the changes, one needs to get acquainted with the programs, rent a machine learning expert to design algorithms or make it on your own and invest for the future by learning new software. Read more at:https://www.experfy.com/blog/algorithms-are-replacing-leadership-strategies

According to authors,Machine-Learning, a subset of Artificial Intelligence (AI), is applied by firms in evaluating  financial decisions like assessing credit worthiness and eligibility criteria for an insurance policy, fraud prevention, by tracking fraud indicative transactions, thereby reducing the fraud rate, risk management, tasks of compliance, natural language processing, where this system can shift through thousands of commercial- loan contracts in seconds  and trading, where it is used both to crunch market data and to select and trade portfolios of securities. In the quantitative front, machine-learning algorithm , helped in making investment decisions, by picking up acquisitions before announcement, managing the client money and moving beyond the boundaries of conventional trading strategy. Read more at http://www.economist.com/news/finance-and-economics/21722685-fields-trading-credit-assessment-fraud-prevention-machine-learning?zid=291&ah=906e69ad01d2ee51960100b7fa502595

Machine learning can be used in our daily lives such as filtering the spams in our mailbox or for banks judging the credibility of customers before issuing credit cards to them. We can even deposit checks through our phone. Machine learning models train itself, gather inputs and generate output. Machine learning tools are used as a part of business intelligence. Through Natural Language Processing (NLP) machine learning can comprehend speech or written words and generate graphs and figures. It can correct any anomalies in business and find out when the demand for your product is high. The more inputs one feeds in faster it learns. Read more at: https://www.sisense.com/blog/beyond-hype-machine-learning-unlocking-power-bi/