Artificial Intelligence in Financial Services – Need to Blend Automation with Human Touch

Author(s):  
Anupam Mehrotra
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ankita Bhatia ◽  
Arti Chandani ◽  
Rizwana Atiq ◽  
Mita Mehta ◽  
Rajiv Divekar

Purpose The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms. Design/methodology/approach This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes. Findings Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors. Research limitations/implications Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market. Practical implications This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner. Social implications In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems. Originality/value This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.


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.


The following article tracks the leading trends in Artificial Intelligence (“AI”), focusing specifically on companies in the Financial Services, Healthcare and Business Services arenas. Wide-ranging exploration in the space charted the many breakthroughs and triumphs in developing AI and the roadblocks in commercializing the technology in areas such as self-driving, machine-diagnosing and the future of autonomous decisions. A clear consensus on the future of AI is automation, particularly where traditional systems are reaching natural limits. For example, in Healthcare, hospice has experienced very little innovation. However, the aging population is taxing the hospice system with a heavy burden falling on otherwise productive family members. How can AI add capacity or improve the effectiveness of hospice? It seems inevitable that AI will play a role by progressing quality in the future of our lives.


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.


Author(s):  
Yousif Abdullatif Albastaki

There is a paradigm shift in the financial services industry. Combined with ever-changing customer expectations and preferences, emerging technologies such as artificial intelligence (AI), machine learning, the internet of things (IoT), and blockchain are redefining how financial institutions deliver services. It is an enormous task to remain competitive in this ever-changing environment. Financial institutions see FinTech as a major part of the digital future, and as proof of this, since 2015, financial institutions have invested over US$ 27 billion in FinTech and digital innovation. This chapter is an introductory chapter that explores FinTech in the literature. It focuses on how FinTech is reshaping the financial industry by describing FinTech phases and development process. The financial products and services using FinTech are also described with a highlight on Islamic FinTech. The chapter finally concludes by describing the future of FinTech.


2022 ◽  
pp. 187-204
Author(s):  
María A. Pérez-Juárez ◽  
Javier M. Aguiar-Pérez ◽  
Miguel Alonso-Felipe ◽  
Javier Del-Pozo-Velázquez ◽  
Saúl Rozada-Raneros ◽  
...  

A lot of millennials have been educated in gamified schools where they played Kahoot several times per week, and where applications like Classcraft made them feel like the protagonists of a videogame in which they had to accumulate points to be able to level up. All those that were educated in a gamified environment feel it is natural and logical that gamification is used in all areas. For this reason, gamification is increasingly becoming important in different fields including financial services, bringing new challenges. Gamification allows financial institutions to provide personalized and compelling experiences. Big data and artificial intelligence techniques are called to play an essential role in the gamification of financial services. This chapter aims to explore the possibilities of using artificial intelligence and big data techniques to support gamified financial services which are essential for digital natives but also increasingly important for digital immigrants.


2022 ◽  
pp. 74-87
Author(s):  
Sunanda Vincent Jaiwant

AI has begun making its presence felt in every industry and now across the financial services industry as well. This chapter examines and presents the use of AI in banks for better customer service giving them a personalized experience. This chapter explains how banks are getting future-ready for their financial services by means of AI and are delivering financial offerings seamlessly. This research primarily focuses on the concept of AI in the field of banking, how AI has revolutionized personalized banking and made banking operations more efficient and successful. AI innovations are an integral part of Industry 5.0 which aims at integrating automation and human intelligence. This chapter aims to study and describe the current applications of AI in the banking industry and its impact on the banking sector. The study also gives a description of the banks employing AI to facilitate an exceedingly personalized customer journey with the banks.


2020 ◽  
pp. 61-66
Author(s):  
K. Yefremova

Problem setting. Artificial intelligence is rapidly affecting the financial sector with countless potential benefits in terms of improving financial services and compliance. In the financial sector, artificial intelligence algorithms are already trusted to account for transactions, detect fraudulent schemes, assess customer creditworthiness, resource planning and reporting. But the introduction of such technologies entails new risks. Analysis of resent researches and publications. The following scientists were engaged in research of the specified question: D.W. Arner, J. Barberis, R.P. Buckley, Jon Truby, Rafael Brown, Andrew Dahdal, O. A. Baranov, O. V. Vinnyk, I. V. Yakovyuk, A. P. Voloshin, A. O. Shovkun, N.B. Patsuriia. Target of research. The aim of the article is to identify key strategic issues in developing mechanisms to ensure the effective implementation and use of artificial intelligence in the financial services market. Article’s main body. The paper investigates an important scientific and practical problem of legal regulation of artificial intelligence used by financial services market participants. The legal risks associated with the use of artificial intelligence programs in a particular area are considered. The most pressing risks to address targeted AI regulation are fundamental rights, data confidentiality, security and effective performance, and accountability. This article argues that the best way to encourage a sustainable future in AI innovation in the financial sector is to support a proactive regulatory approach prior to any financial harm occurring. This article argues that it would be optimal for policymakers to intervene early with targeted, proactive but balanced regulatory approaches to AI technology in the financial sector that are consistent with emerging internationally accepted principles on AI governance. Conclusions and prospects for the development. The adoption of rational regulations that encourage innovation whilst ensuring adherence to international principles will significantly reduce the likelihood that AI-related risks will develop into systemic problems. Leaving the financial sector only with voluntary codes of practice may encourage experimentation that in turn may result in innovative benefits – but it will definitely render customers vulnerable, institutions exposed and the entire financial system weakened.


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