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12 Use Cases of AI and Machine Learning In Finance

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There's no doubt that the finance industry is undergoing a transformational change. The recent years have seen a rapid acceleration in the pace of disruptive technologies such as AI and Machine Learning in Finance due to improved software and hardware. 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 AI and Machine Learning In Finance are having a significant impact on this sector.


10 Applications of Machine Learning in Finance

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Machine learning in finance has become more prominent recently due to the availability of vast amounts of data and more affordable computing power. Machine learning in finance is reshaping the financial services industry like never before. Leading banks and financial services companies are deploying AI technology, including machine learning (ML), to streamline their processes, optimise portfolios, decrease risk and underwrite loans amongst other things. Here in this article, we will explore some important ways machine learning is transforming the financial services sector and examples of real applications of machine learning in finance. To answer this question and understand the role of machine learning in finance, we must first understand why machine learning is suitable for finance. Machine learning is about digesting large amounts of data and learning from that data in how to carry out a specific task, such as distinguishing fraudulent legal documents from authentic documents. Machine learning in finance is the utilization a variety of techniques to intelligently handle large and complex volumes of information. ML excels at handling large and complex volumes of data, something the finance industry has in excess of. Due to the high volume of historical financial data generated in the industry, ML has found many useful applications in finance. The technology has come to play an integral role in many phases of the financial ecosystem, from approving loans and carrying out credit scores, to managing assets and assessing risk.


AI Is Disrupting the Finance Industry

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In January 2020, the Cambridge Centre for Alternative Finance (CCAF) released a study on the impact of AI in the finance industry. Known as one of the most comprehensive global surveys in this domain, it comprised around 151 respondents from 33 countries, including incumbent financial institutions and FinTech firms. At least 77% of the respondents believe that AI bears high importance to their organization in the next couple of years. Almost 64% of the respondents intend to earn revenue through AI via client acquisition, customer service, risk management, process automation, and new products. At the moment, AI is widely used in risk management, having an implementation rate of 56% among firms.


Artificial Intelligence in Finance: Opportunities and Challenges

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Artificial intelligence (AI) is not a new kid on the block anymore and the field is developing at a constantly increasing pace. Pretty much every day there is some kind of new development, be it a research paper announcing a new or improved machine learning algorithm, a new library for one of the most popular programming languages (Python/R/Julia), etc. In the past, many of those advances did not make it to mainstream media. But that is also changing rapidly. Some of the recent examples include the AlphaGo beating the 18-time world champion at Go [1], using Deep Learning to generate realistic faces of humans that never existed [2], or the spread of Deep Fakes -- images or videos placing people in situations that never actually happened.


5 Ways Artificial Intelligence Is Shaping the Future of Financial Services TechMeru

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Artificial intelligence (AI) comes with numerous promises in several sectors, and the financial industry is no exception. Whether it is in improving customer experience or in automation, AI has significantly disrupted the financial industry and is now shaping its future. Banking, for instance, is one sector slated to benefit significantly from incorporating AI systems. According to analysts, AI will result in more than $1 trillion in savings by 2030. Moreover, financial services players who will incorporate AI prudently will experience a 14% net gain in jobs and a 34% increase in revenues by 2022.