Banking on Hadoop: 7 Use Cases for Hadoop in FinanceBanking on Hadoop: 7 Use Cases for Hadoop in FinanceSmartData Collective. Hadoop is present in nearly every vertical today that is leveraging big data in order to analyze information and gain competitive advantages. Many financial organizations firms are already using Hadoop solutions successfully and the ones who are not have plans to do so. If they don’t, they risk enormous market share loss. Following are a few of the most intriguing and essential big data and Hadoop use cases. Fraud detection: Fraud, financial crimes and data breaches are some of the most costly challenges in the industry. Hadoop analytics help financial organizations detect, prevent and eliminate internal and external fraud, as well as reduce the associated costs. Analyzing points of sale, authorizations and transactions, and other data points help banks identify and mitigate fraud. Risk management: Every financial firm needs to assess risk accurately, and big data solutions enable them to to do so by effectively evaluating credit exposures.
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