AI and Machine Learning In Finance: Present Use Cases and Future Scope - PowerPoint PPT Presentation

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AI and Machine Learning In Finance: Present Use Cases and Future Scope

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AI and machine learning have revolutionized the working of almost every industrial sector today. Most recently, the application of machine learning in finance has become an integral part of its ecosystem. The financial industry is perhaps one of the most suitable fields where machine-learning use cases are plenty. – PowerPoint PPT presentation

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Title: AI and Machine Learning In Finance: Present Use Cases and Future Scope


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AI and Machine Learning In Finance Present Use
Cases and Future Scope
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Trading Decisions
  • Machine learning algorithms facilitate
    organizations to make better trading decisions.
    It is done by the continuous, real-time
    monitoring of the trade results and the
    subsequent detection of patterns that governs the
    movement of stock prices upwards or downwards.
    Its predictions enable it to make decisions
    regarding selling, holding, or purchasing stock.

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2. Automation of processes
  • Chatbots, call-center automation, customer
    onboarding, account opening, and closing, and
    loan processing automation are just some of the
    few Machine-learning use cases in the financial
    sector. By automating these manual, cumbersome
    and lengthy processes, ML solutions allow
    financial institutions to enhance efficiency,
    minimize personnel costs, mitigate risks, and
    expand their capacity.

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3. Financial monitoring for better security
  • A United Nations report estimates that around
    800 billion - 2 trillion money is laundered
    each year globally. With the growing number of
    security threats in finance, it has become
    imperative that this sector incorporates ML
    technologies to combat transactional security
    threats.

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4. Better investments decisions
  • One of the major applications of Machine learning
    in finance relates to the investment landscape.
    As datasets get more complicated, ML-based
    sophisticated data analysis techniques are being
    used to analyze data and develop suitable
    strategies.

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6. Enhanced customer service through sound
financial advice
  • Apps powered by ML help customers to monitor and
    analyze their expenditures, thereby enabling them
    to increase savings. More recently, ML-based,
    Robo-advisors are being utilized for processes
    like portfolio management and financial product
    suggestions

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6. Extracting insights from customer data
  • Today, data from countless sources inundates
    financial institutions. Although this data is
    crucial for an organization's progress, its vast
    quantities make its processing nearly impossible
    manually.

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Contact Us
  • To attain success in your next machine learning
    project, join hands with the specialist team at
    Narola Infotech.
  • Email info_at_narola.email
  • Contact number 1 (650) 209-8400
  • Website https//www.narolainfotech.com/machine-le
    arning-company

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