How is artificial intelligence transforming the banking sector in the UAE?
The role of artificial intelligence within the banking sector in the UAE and how can this technology be leveraged for banking functions.
1) Information gathered to research topic:
Artificial intelligence (AI) is the field of science that deals with improving the capabilities of modern computer systems issues and revolves around the use of humans like complex capabilities of learning, reasoning, and self-correction. AI is being adopted in various industries in that it offers real-time analytics and has highly accurate at interpreting images, sounds, and natural language. Moreover, it is embraced for its predictive nature and can sort unstructured data which to an average computer system might prove tedious and difficult. Application of AI is extensive and encompasses fields such as transport networks, healthcare, banking, insurance as well as food and agriculture among others.
The banking sector handles lots of financial data that makes the employment of high speed and superior decision-making technologies like AI crucial. Alzaidi. P.146 argues that machine learning, the blockchain, data analytics provided by artificial intelligence tools have the ability to transform the manner in which the banking industry works. The author further notes that further studies should be conducted to examine how the adaptation of AI has in the banking sector.
Maria, 2018 notes that artificial intelligence has a huge potential in the banking industry and can be successfully applied in tailored financial services, underwriting, voice aided transaction, and data-driven loaning decisions. As the population grows banks customer bases are poised to grow and consequently the transactions hence the need for a computer system that is superior to human experts. Besides insurance, the bank has benefitted immensely from the use of AI.
Other financial entities are merging AI and the Internet of Things in a bid to stretch the extent to which banking system can accommodate other external factors. In analyzing the importance that AI has brought to the banking sector, it is important to examine how it has leveraged on the use of information from other sectors such as insurance, and government agencies.
2) Literature Review:
With the need to cater to a growing clientele and improve efficiency, banks are automating their process and improving infrastructure so as to offer seamless customer satisfaction. Advanced technology like advanced data-driven AI lies at the heart of what has enabled banks and financial entities to automate operations. Vedapradha and Ravi, (2018) argue that adopting AI-based technology has aided in anti-money laundering and anti-fraud in the banking sector. The application is supported by Kingdon, p. 87, who confirms that after the 9/11 attacks, almost half of the top 20 banks adopted the AI system as a method to fight money laundering and identification of suspicious transaction that could be funding terrorists. Choi and Lee, p.7, note that fraud encompasses the spread of false information which humans cannot determine in real time and which may eventually affect sectors like stock trading. They, however, cites the case of the Bombay Stock Exchange that has rolled out AI-assisted solutions which detects rumours as a way of minimizing information disproportionateness.
Bershidsky, (2019) assert that AI has revolutionized how lenders calculate credit scores and develop credit profiles. AI is favoured in the banking sector for its ability reconcile and harmonize an individual’s banking transaction, past decisions, spending and earning patterns as well as mobile data. Then it can give informed credit score. The present application of AI in determining creditworthiness reduce greatly the risk of defaulting. Motwani, Chaurasiya and Bajaj, (2018) who researched on machine learning approach on predicting bank creditworthiness, noted that AI algorithms gave over 80 percent accuracy in prediction. The results from their study did not show significant error signifying the feature can accurately determine the creditworthiness. It thus follows that the use of AI in banks has minimized the number of loan defaulter likely to pass a creditworthiness assessment.
AI has transformed how transactions are handled in the banking sector. Manser Payne, Peltier and Barger, p.328, notes that AI has secured transactions using features such as voice recognition via banking applications. The research further asserts that the AI personal assistants are being embedded in transactions as a way of offering more integrated transaction that does not require extra verification. Put differently, the AI offers a conversational interface that streamlines the transaction process.
In streamlining the banking industry, the transformation has been associated with a disadvantage as noted by Schulte and Liu, p.41, who argues that AI had a negative impact on the financial job market. AI has reduced the manual labour required for activities such as network risk testing, auditing, suspicious activity testing, legal research among other areas (Maria, 2018, Manning, 201). Though automating may have a positive advantage to the bank while rendering others jobless. Another negative impact can affect the bank. For example, the risk of financial turmoil in an AI dominated market may be heightened by many traders adopting the machine learning strategy that overdo others. Moreover, the predictive nature may be manipulated for criminal purposes (Barnhizer, 2016). Market volatility in banks trading may also be affected by high-frequency trading and a large number of transactions.
It thus stands to reason that AI has had a huge impact on the transformation of the banking sector. Important areas impacted include credit score analysis, transaction, anti-fraud and anti-money laundering among other areas.
4) Research question/objective/hypothesis:
The main aim of this research is to investigate the effect of artificial intelligence observed in the banking industry and the changes in the way banks operate, the innovations in products and services emerged, the transformations in customer experiences. The research will focus on addressing the following question “How is artificial intelligence transforming the banking sector in the UAE?” while doing so, the research paper will shed light on the below objectives:
- The effect of artificial intelligence on cost reduction and process optimization within the banking industry.
- Identify the impact of artificial intelligence on customer satisfaction and retention.
- Identify the regulations and level of compliance adopted by banks to minimize the risks associated with artificial intelligence.
5) Methodology:
The research will be conducted using a combination of Qualitative & Quantitative research approach as a methodology of the research. This method is known as the pragmatism research philosophy where it allows for the integration of more than one research methodologies within the same study. (Saunders, 2012)
Analysing the impact of AI on the banking industry will require the collection of large samples of customers to examine their level of satisfaction with the banking products and services adopting artificial intelligence. Hence, a quantitative approach will be best suited for conducting such surveys. A qualitative approach will be used when analysing the effects of artificial intelligence on cost reduction and process optimization within the banking industry and identifying the regulations and level of compliance adopted by banks to minimize the risks associated with AI. This will be analysed through interviews a with industry leaders within the operations units of banks.
6) Timetable of Key Activities - May 1st – May 31st
o Develop survey items
o Review and revise the survey
o Pre-test the survey with a sample of target population and revise the survey if changes are required.
o Conduct the survey with the target population (banking customers within the UAE on their experience with products and services in which artificial intelligence was adopted). - June 1st – June 30th
o Develop interview questions.
o Review the questions and obtain the necessary approvals.
o Set interviews with banking professionals with knowledge on the research topic (to answer the research objectives related to the cost effectiveness and process efficiencies resulting from utilizing artificial intelligence within processes of the bank.) - July 1st – July 15th
o Processing the data gathered through surveys and interviews. - July 16th – July 31st
o Statistical analysis of the data at hand - Aug 1st – Aug 31st
o Preparation and submission of the 1st draft for review - Sep 1st – submission date
o Feedback will be received for further adjustments and the research paper will be prepared for final submission.
7) Resources
This research will be using primary data in order to achieve its objectives. The data collection process will include a combination of surveys and interviews. Each of which will serve to answer a specific objective. The survey questions will be structured in the form of a close ended questionnaire. This will assist in gathering data on customers satisfaction levels and knowledge levels on artificial intelligence adopted products and services. The interview will help in understanding the effect of artificial intelligence on reducing costs and increasing efficiencies and the steps taken to mitigate the risks associated with adopting such technology.
8) Population, Sampling and interview process
The sampling method used will be random sampling method for the surveys conducted. The data will be gathered from banking customers in the UAE banking with local and international banks consuming products and services that adopt artificial intelligence technologies. In order to conduct the interviews a group of banking professionals within the operations units will be contacted via emails or Linkedin and meetings will be set accordingly.
9) Practical and ethical issues:
The ethical issues that might arise from the research conducted will concern privacy and confidential data obtained from banking professionals in relation to their internal processes and the data shared. Their consent to share the data in this research will be obtained prior to conducting the interview.