BUSM7012 - Business Project Proposal Assessment Answers

Problem Statement

With the advent of Artificial Intelligence (AI) technologies across Australia's financial and banking sectors, a plethora of legal as well as ethical impediments have emanated, which requires exigent solutions (Bhushan, 2021). From an apparent vision it would seem that AI-driven applications have the potential to streamline existing industrial practices. However, in reality, the feasibility of privacy breaches, as well as bias decision-making approaches, due to misinformation, can inherently enhance impediment across working function of financial and banking corporation in Australia; subsequently leading to loss of consumer trust and violation of regulatory compliance. The following study intends to scrupulously analyze the legal as well as ethical implication pertinent with AI adoption in the BFSI sector, predominantly concentrating upon data privacy, so that bias can be mitigated, and transparency can be inculcated across the working function of BFSI segment in Australia.

Background: The Australian BFSI Sector

Definition:

The Australian BFSI (Banking, Financial Services, and Insurance) sector plays an instrumental role in propelling the nation’s economy (Herrmann & Masawi, 2022). It substantiates a financial ecosystem that is comprehensive in nature, while furnishing crucial services, such as corporate banking, retail banking and investment advisory services aside from well then asset management and insurance.

Players:

Banks: The banking sector in Australia is predominantly secured by Commonwealth Bank of Australia (CBA), Westpac Banking Corporation, Australia and New Zealand Banking Group (ANZ), and National Australia Bank (NAB) (Joshi et al., 2021). Aside from that, there are other

small-scale banks as well as credit unions which cater to diverse market segments. On top of that, insurance industry and superannuation funds play a crucial role in Australia's BFSI segment.

Number of People Employed and Overall Contribution to the Economy:

In consonance with Australian Bureau of Statistics, BFSI segment still secures the vanguard position in contributing to nation’s employment by substantiating more than 450,000 people as of 2021, across diverse disciplines and designations (Khatwani et al., 2023). As far as the contribution of the sector is concerned in relation to the economy, the BFSI industry accounts for a substantial portion of Australia's Gross Domestic Product (GDP). In 2021 alone, the sector contributed approximately 9% to Australia's GDP, which can necessarily be translated into the fact that BFSI segment plays a pivotal role in driving economic growth (Maiti et al., 2022).

Timeline of Development:

Throughout the 1980s, the Australian government inculcated a series of deregulation as well as liberalization policies for the sake of ushering Australia's BFSI segment in heightened competition, where it can conveniently foster innovation within the financial sector. Concurrently, the advent of electronic banking systems and the establishment of online banking platforms during the latter part of the 20th century brought about a paradigm shift, which in turn, endowed customers with unparalleled convenience in accessing financial services. Subsequently, in late 2021, AI technologies have emerged as preeminent forces within the BFSI domain. This recent technological amendment has essentially assisted the integral BFSI segment to propel the industry forward through automation along with data analytics.

Section 3: Situation Analysis - AI and BFSI Connection

The inculcation of artificial intelligence across Australian BFSI sector can be defined as transformative in nature. To put it in simple perspective, it can be stated that aside from

streamlining operational efficiency, augmenting customer experience and ameliorating the process of decision-making practice throughout BFSI sector has essentially been subjected to radical transformation with the help of artificial intelligence.

AI Adoption and Investment: In consonance with 2021 industrial report, the feasibility of incorporating artificial intelligence throughout every stratum of Australian BFSI sector has been undeniable in nature. Statistically speaking, over 73% of the financial institutions operating in Australia has already implemented artificial intelligence in terms of streamlining their operational efficiency. Aside from heavily investing in augmenting their IT framework to substantiate artificial intelligence, research and development has also been deployed in order to derive applications based on artificial intelligence, that can potentially open up new horizon for Australian BFSI sector.

Enhanced Customer Experience: AI-driven chatbots and virtual assistants have emerged as ubiquitous attributes within the customer service milieu of financial institutions. Empirical data suggests that upwards of 60% of banks in Australia have embraced the deployment of AI-powered chatbots to adeptly manage customer queries and offer expeditious real-time assistance (Štitilis et al., 2023). As a consequence, this transformative implementation has yielded enhancements in response times, ensuring round-the-clock availability, and engendering an elevated level of personalized customer experience.

Risk Assessment and Fraud Detection: The survey conducted on Commonwealth Bank of Australia has revealed that as far as risk assessment is concerned, artificial intelligence has proven to be exemplary in natures and the fraud detection capabilities are solitarily dependent on stringent codes, which entails the algorithm. Simply put, it can be stated that machine learning algorithms, which constitute the artificial intelligence driven software, can scrupulously examine massive proportion of transactional data. On the basis of which,

consumer behavior patterns can also be detected. Based on such readings, anomalies as well as suspicious activities can potentially reduce probability of fraudulent transaction, thereby increasing risk management practices.

Operational Efficiency and Automation: It is needless to say that with inculcation of artificial intelligence, streamlining routine tasks that are monotonous in nature, such as document verification and data entry as well as compliance check with due diligence can be carried out in a seamless manner. As a consequence of which, 84% of financial institutions have drastically witnessed a significant rise of their productivity with the help of AI driven process (Štitilis et al., 2023).

Trust Privacy and Security: The capability of AI to process data has potentially raised concern regarding misuse of personal credential, which is why more than 68% of financial institutions across Australia has consolidated their security measure in terms of safeguarding credential information, so that infringement of compliance in relation to privacy regulation and consumer trust protection does not take place (Štitilis et al., 2023).

References

Bhushan, S. (2021). The impact of artificial intelligence and machine learning on the global economy and its implications for the hospitality sector in India. Worldwide Hospitality and Tourism Themes, 13(2), 252-259.

Herrmann, H., & Masawi, B. (2022). Three and a half decades of artificial intelligence in banking, financial services, and insurance: A systematic evolutionary review. Strategic Change, 31(6), 549-569.

Joshi, V., Sharma, M., & Ranjan, P. (2021). Artificial Intelligence and Financial Decision Making-Review of efficacy in Usage within Financial Organizations in India. Turkish Online Journal of Qualitative Inquiry, 12(7).

Khatwani, R., Mishra, M., Bedarkar, M., Nair, K., & Mistry, J. (2023). Impact of blockchain on financial technology innovation in the banking, financial services and insurance (BFSI) sector. Journal of Statistics Applications and Probability, 12(1), 181-189.

Maiti, M., Vuković, D., Mukherjee, A., Paikarao, P. D., & Yadav, J. K. (2022). Advanced data integration in banking, financial, and insurance software in the age of COVID‐19. Software: Practice and Experience, 52(4), 887-903.

Štitilis, D., Laurinaitis, M., & Verenius, E. (2023). The Use of biometric technologies in ensuring critical infrastructure security: the context of protecting personal data. Entrepreneurship and sustainability issues, 10, 133-150.

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