3000 words research paper

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Hang Nguyen

ENG 3304

Topic: Machine Learning in Finance

INTRODUCTION

Ever since its development in the 1970s, machine learning has become an irreplaceable tool for increasing efficiency and accuracy in all industries. The finance industry has been one of the leading industries to implement machine learning in many functionalities across the industry. According to the Investment Banking Council (2019), “AI will generate more than $2.9 trillion in business value and recover 6.2 billion hours of worker productivity by 2021.” As more and more financial institutions are taking advantages of machine learning, many people raise the question of whether machine learning will take jobs away from human, which will make an already competitive jobs market become even more cutthroat. Moreover, machine learning has also brings new challenges facing not only financial institutes but anyone who wishes to use it. Any further used of machine learning without addressing these issues can bring up a catastrophe. While machine learning can give predictions based on the data its processes, the accuracy of those predictions rely entirely on the quality of the data. Many firms are struggling to ensure quality of the data that they feed into their machine learning system. Thus, there are many regulations and failures in internal processes that also can endanger the results of the machine learning process. In short, machine learning can bring many opportunities but great challenges are still facing companies.

This report will discuss the current trends in machine learning implementation in the finance industry. Next, the report introduces the benefits and examines the challenges facing financial institutes when using machine learning. After that, the report will analyze the impact of machine learning on the jobs market. Finally, the report discuss the future of machine learning in finance.

FINDINGS

· The implementation of machine learning

· Brief introduction of machine learning in Finance.

· M. Romao, J. Costa and C. J. Costa, "Robotic Process Automation: A Case Study in the Banking Industry," 2019 14th Iberian Conference on Information Systems and Technologies (CISTI), Coimbra, Portugal, 2019, pp. 1-6, doi: 10.23919/CISTI.2019.8760733.

· Discuss the current implementation of machine learning in Finance.

· Didur, K. (2018, July 11). Machine learning in Finance: Why, what & how. Retrieved February 15, 2021, from https://towardsdatascience.com/machine-learning-in-finance-why-what-how-d524a2357b56

· The benefits and challenges facing machine learning

· Benefit of machine learning.

· Didur, K. (2018, July 11). Machine learning in Finance: Why, what & how. Retrieved February 15, 2021, from https://towardsdatascience.com/machine-learning-in-finance-why-what-how-d524a2357b56

· Ai in investment banking - the new frontier. (2019, September 11). Retrieved February 06, 2021, from https://www.investmentbankingcouncil.org/blog/ai-in-investment-banking-the-new-frontier

· Challenges facing machine learning

· Didur, K. (2018, July 11). Machine learning in Finance: Why, what & how. Retrieved February 15, 2021, from https://towardsdatascience.com/machine-learning-in-finance-why-what-how-d524a2357b56

· The impact of machine learning in jobs market.

· Acknowledges the potential jobs loss.

· Press, G. (2019, July 17). Is ai going to be a jobs killer? New reports about the future of work. Retrieved February 19, 2021, from https://www.forbes.com/sites/gilpress/2019/07/15/is-ai-going-to-be-a-jobs-killer-new-reports-about-the-future-of-work/?sh=38faf628afb2

· Rinehart, W., & Edwards, A. (2019, July 11). Understanding job loss predictions from artificial intelligence. Retrieved February 19, 2021, from https://www.americanactionforum.org/insight/understanding-job-loss-predictions-from-artificial-intelligence/

· Opening the door to others jobs field and the skills required.

· The future of machine learning.

· Future implementation trends of machine learning.

· Didur, K. (2018, July 11). Machine learning in Finance: Why, what & how. Retrieved February 15, 2021, from https://towardsdatascience.com/machine-learning-in-finance-why-what-how-d524a2357b56

· Current technology that companies are investing in to address the current limitations of machine learning

· Bouland, A., Van Dam, W., Joorati, H., Kerenidis, I., & Prakash, A. (2020, November 12). Prospects and challenges of quantum finance. Retrieved February 19, 2021, from https://arxiv.org/abs/2011.06492.

CONCLUSION

· Summary of main points

· Brief discussion of future of machine learning

REFERERNCES

(to be included)