2 min read

Machine Learning Use Cases in Finance.

Machine Learning works by extracting meaningful insights from raw sets of data and provides accurate results. This information is then used to solve complex and data-rich problems that are critical to the banking & finance sector.
Machine Learning Use Cases in Finance.

Machine learning in Finance.

The finance sector, specifically, has seen a steep rise in the use cases of machine learning applications to advance better outcomes for both consumers and businesses. Until recently, only the hedge funds were the primary users of AI and ML in Finance, but the last few years have seen the applications of ML spreading to various other areas, including banks, fintech, regulators, and insurance firms, to name a few.

Right from speeding up the underwriting process, portfolio composition and optimization, model validation, Robo-advising, market impact analysis, to offering alternative credit reporting methods, the different use cases of Artificial Intelligence and Machine Learning are having a significant impact on the financial sector.

The finance industry, including the banks, trading, and fintech firms, are rapidly deploying machine algorithms to automate time-consuming, mundane processes, and offering a far more streamlined and personalized customer experience.

Why Use Machine Learning in Finance?

Here are some of the reasons why banking and financial services firms should consider using Machine Learning despite having the above-said challenges –

  • Enhanced revenues owing to better productivity and improved user experience
  • Low operational costs due to process automation
  • Reinforced security and better compliance

Read more...

Source:https://marutitech.com/ai-and-ml-in-finance/

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