A Survey of Fair and Responsible Machine Learning and Artificial Intelligence: Implications of Consumer Financial Services

2020 ◽  
Author(s):  
Stephen Rea
2021 ◽  
Vol 12 (4) ◽  
pp. 43
Author(s):  
Srikrishna Chintalapati

From retail banking to corporate banking, from property and casualty to personal lines, and from portfolio management to trade processing, the next wave of digital disruption in financial services has been unleashed by the concepts and applications of Artificial Intelligence (AI) and Machine Learning (ML). Together, AI and ML are undoubtedly creating one of the largest technological transformations the world has ever witnessed. Within the advanced streams of research in AI and ML, human intelligence blended with the cognitive reasoning of machines is finally out of the labs and into real-time applications. The Financial Services sector is one of the early adopters of this revolution and arguably much ahead of its leverage compared to other sectors. Built on the conceptual foundations of Innovation diffusion, and a contemporary perspective of enterprise customer life-cycle journey across the AI-value chain defined by McKinsey Global Institute (2017), the current study attempts to highlight the features and use-cases of early-adopters of this transformation. With the theoretical underpinning of technology adoption lifecycle, this paper is an earnest attempt to comment on how AI and ML have been significantly transforming the Financial Services market space from the lens of a domain practitioner. The findings of this study would be of particular relevance to the subject matter experts, Industry analysts, academicians, and researchers focussed on studying the impact of AI and ML in the financial services industry.


Author(s):  
Gagan Kukreja

Almost all financial services (especially digital payments) in China are affected by new innovations and technologies. New technologies such as blockchain, artificial intelligence, machine learning, deep learning, and data analytics have immensely influenced all most all aspects of financial services such as deposits, transactions, billings, remittances, credits (B2B and P2P), underwriting, insurance, and so on. Fintech companies are enabling larger financial inclusion, changing in lifestyle and expenditure behavior, better and fast financial services, and lots more. This chapter covers the development, opportunities, and challenges of financial sectors because of new technologies in China. This chapter throws the light on opportunities that emerged because of the large population of 1.4 billion people, high penetration, and access to the latest and affordable technology, affordable cost of smartphones, and government policies and regulations. Lastly, this chapter portrays the untapped potentials of Fintech in China.


2021 ◽  
Vol 12 (06) ◽  
pp. 27-35
Author(s):  
Prudhvi Parne

Digital disruption is redefining industries and changing the way business function. Artificial Intelligence is the future of banking as it brings the power of advanced data analytics to combat fraudulent transactions and improve compliance. Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector. Additionally, the paper will provide the necessary strategies that any banking organization can follow when digitizing its operations when implementing Artificial Intelligence, Machine learning and Cloud Computing.


Author(s):  
Prarthana Mukherjee* ◽  
Prit Palan ◽  
M. V. Bonde

Studies have shown that new generation of millennials have limited to no knowledge about managing their finances. This lack of awareness has created a need for financial literacy which is not only an essential employ-ability skill but also, a paramount life skill. Not only the younger generation but many individuals already in the corporate field are at their wit’s end when it comes to planning their finances and making correct financial decisions. This is where awareness in wealth management comes in. Wealth management is an investment advisory service. It also combines financial services to address the needs of individuals. It is more than just investment advice; it encompasses all parts of a person's financial life. The users can find all the information of different investments rather than integrating all the information from different places. They can generate a plan themselves or with the help of artificial intelligence and machine learning principles, manage their own and their family's current and future needs.


Author(s):  
Gagan Kukreja ◽  
Divij Bahl ◽  
Ruchika Gupta

Fintech is a new buzz word in the fourth industrial revolution environment. No financial services across the globe are left unaffected by the new technologies. Artificial intelligence, machine learning, blockchain, and data analytics have immensely influenced many aspects of financial services such as deposits, transactions, billings, remittances, credits (B2B and P2P), underwriting, insurance, and so on. Fintech companies are enabling larger financial inclusion, improvement of lives of humans, better decision-making, and lots more. This chapter covers the development, opportunities, and challenges of financial sectors because of new technologies in India. This chapter throws the light on opportunities that emerged because of demographic dividend, high penetration, and access to the latest and affordable technology, affordable cost of smartphones, and government policies such as Digital India, Startup India, Make in India, and so on. Lastly, this chapter portrays the untapped potentials of Fintech in India.


2021 ◽  
Author(s):  
Prudhvi Parne

Financial services are the economical backbone of any nation in the world. There are billions of financial transactions which are taking place and all this data is stored and can be considered as a gold mine of data for many different organizations. No human intelligence can dig in this amount of data to come up with something valuable. This is the reason financial organizations are employing artificial intelligence to come up with new algorithms which can change the way financial transactions are being carried out. Artificial Intelligence can complete the task in a very short period. Artificial intelligence can be used to detect frauds, identify possible attacks, and any other kind of anomalies that may be detrimental for the institution. This paper discusses the role of artificial intelligence and machine learning in the finance sector.


2021 ◽  
Vol 3 (6) ◽  
Author(s):  
Difei Zhang

Financial technology changes the logic of financial interpretation through the use of digital and digital centric technologies, commercialization, big data analysis, machine learning and artificial intelligence. From financial institutions that use technology to provide financial services to technology companies that directly provide financial services, fintech companies play an important role in realizing financial brokerage and financial democratization and improving the availability and efficiency of financial services. Based on this, this paper focuses on the plight and path of cooperative governance of financial technology supervision, for the reference of relevant personnel.


Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


Author(s):  
M. A. Fesenko ◽  
G. V. Golovaneva ◽  
A. V. Miskevich

The new model «Prognosis of men’ reproductive function disorders» was developed. The machine learning algorithms (artificial intelligence) was used for this purpose, the model has high prognosis accuracy. The aim of the model applying is prioritize diagnostic and preventive measures to minimize reproductive system diseases complications and preserve workers’ health and efficiency.


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