Financial businesses need to automate risk analytics in order to carry out strategic decisions for the company. Using data science and machine learning algorithms they can identify, monitor and prioritize the risks. Similarly, it uses machine learning for predictive analytics. It enables the companies to predict customer lifetime value and their stock market moves. Risk analytics is one of the key areas of data science. With Risk analytics and management, the company is able to take strategic decisions, increase trustworthiness and security. Fraud is a major concern for financial institutions. The dangers of fraud have increased with an increase in the number of transactions. However, with the growth in big data and analytical tools, it is now possible for financial institutions to keep track of fraud. The detection of this type of fraud is due to the improvements in algorithms that have increased the accuracies for anomaly detection.
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