Despite being largely in pilot mode up to recent times, with fewer projects migrating into production, the advancement of Artificial Intelligence ( AI) has been has been a major driver for Digital Transformation in several industries. A growth in investment directed towards AI has been witnessed between the years 2016 and 2020. Only 9% of organisations had deployed by 2016 but the figure had grown to 19% by the year 2019.( Gartner 2016 cited in Thowfeek, et al., 2020; Hammer, et al., 2022)
AI can be defined as the application of “advanced analysis and logic based techniques, which include Machine learning , to interpret events, support and automate decisions, deliver experiences and take actions”. (Gartner, 2023)
Another study simply defines AI as the ability to make computers do things that, currently, people can do better. A key capability that is now evident in AI is machine learning which is slowly substituting adaptability to environments and behaviours that was until recently remain an exclusive human quality. (Thowfeek, et al., 2020)
AI is increasingly influencing the way businesses make decisions, disseminates information and conducts their operations thus Business and Technology leaders can no longer afford not to invest time and other resources to understand it and possibly create plans to leverage it for strategy execution. However, for the adoption of AI to be sustainable there is need for a holistic approach, it cannot be piecemeal anymore. (Mullen, 2023).
The holistic approach, mentioned above, requires that AI is looked from different perspectives or dimensions. Figure 1.1. below depicts one framework that can be adopted when studying AI and how it can be applied. (Elliot, et al., 2022)
Figure 1.1 The Gartner Framework for Applying AI
Organisations are also encouraged to look at AI from a systems perspective where its interaction with people, processes and other technologies needs to be given due consideration in design and implantation of AI driven systems (Mullen, 2023)
AI has been known to enhance a number of business processes within organisations. These processes include human capital management, customer service, sales and supply chain management (Davis & Elliot, 2022)
AI has become a foundational technology upon which a number of business capabilties are being built in several organisations and has even been advanced to spur national growth and create more business opportunities. The benefits of adopting AI in Banks range from boosting revenue generation, reduced costs of doing business as well as customer experience. With all these reported benefits AI adoption is still in its nascent stages and this is attributable to organisations having yet to come up with a compelling business case as well as develop the requisite competences to successfully deliver an AI capability. Up until recently Banks have run pilot projects on adoption of AI but with few of the projects being migrated into day-to-day business operations (Thowfeek, et al, 2020).
AI has found its way into several industry verticals as depicted in Figure 1.2 below, however this blog will narrow down to the use cases for the Banking and Investment industry. (Davis & Elliot, 2022)
Figure 1.2 Application of AI by industry verticals
When looking at use cases for AI adoption it is important to understand both the business value and feasibility in these cases . Figure 1.3 below can be used to guide Banking Organisations on which use cases to prioritise investment in AI. (Sau, et al., 2022)
From the guide the following use-cases rank high thus should be up for immediate consideration for adoption: Customer churn prediction/Prevention, Customer Segmentation/Personalisation, Transaction Data enrichment, Virtual Financial Assistant, ChatBots, Customer Transaction Fraud Detection, Revenue forecasting. At the base of the pyramid, and of low priority, is the Mortgage default protection, followed by Intelligent Receivables Reconciliation, IT Root Cause Analysis, Portfolio Credit Risk Optimisation, Authentication Optimisation, Enhanced due Diligence
Figure 1.3 : AI Use-Case prism for Banking Industry
Gartner’s use-case prism above corroborates well with another research on adoption of AI in Banks in Sri Lanka which has revealed that AI has largely been adopted to analyse customer behaviour to proactively understand their changing needs and respond with relevant solutions thus gaining a competitive edge over their peers who have not adopted AI. (Thowfeek, et al., 2020)
A typical and more common use case for banks in the developing world is the embedding of chatbots into mobile apps and social media platforms. However the chatbots deployed are still deemed to be too simplistic to meet the expectations of the customer, particularly the digital natives who want similar experiences from their banks as they get from the digital giants like Amazon, Facebook, Microsoft and Apple pre and post transaction. (Thowfeek, et al., 2020)
Table 1.1: Examples of AI utilisation in Banks and Fintechs
A number of successful deployments of AI to enhance customer experience and operational excellence have been recorded in Asia and sub-Saharan African Banks. Table 1.1 here summarises some of the AI deployments currently operational together with the business outcomes out of these.(Kshetri, 2021).
The live use cases of AI in Table 1.1 above are a clear indication of how AI can be deployed to drive socio-economic transformation in the developing world, and in particular Africa. They further demonstrate how AIs can foster operational excellence and superior customer experience as they are being deployed in front-office operations as Chatbots, in the Middle-office to carry out know-your-customer (KYC) and Anti-money-laundering verification activities and in the back-office for risk underwriting. (Decosmo, 2019 cited in Kshetri, 2021)
Figure 1.4 – Digital Technologies adoption Horizon for Africa
The future of AI looks brighter as it has been named the Digital Technology with the highest probability of being implemented by organisations in Africa by the year 2025. Just under 95% of African Chief Information Officers ( CIOs) interviewed by Gartner have advised that they have adopted AI or have immediate plans to adopt it to enhance operational excellence and customer experience . Figure 1.4 here depicts the results the CIO survey on the technologies likely to be adopted by African organisations by the year 2025.(Sau, et al., 2023)
Figure 1.5 High level Enterprise AI landscape
Whilst the benefits of adopting AI are very clear it is key that business leadership fosters a holistic view of AI by ensuring a consistent visibility of the its three high-level dimensions namely AI Techniques and foundations, AI solutions and AI Governance depicted in Figure 1.5 here. (Mullen, 2023)
References
Davis, M. & Elliot, B., 2022. Applying AI in business Domains. [Online] Available at: https://www.gartner.com/document/4004019?ref=solrAll&refval=365793474 [Accessed March 2023].
Elliot, B., Brethenoux, E, Mullen, A., and Choudhary, F, 2022. Applying AI - a Framework for the enterprise. [Online] Available at: https://www.gartner.com/document/code/725152?ref=authbody&refval=4004019 [Accessed March 2023].
Gartner. (2022, October 13). 2023 CIO and Technology Executive Agenda: 4 Actions to Deliver ‘Digital Dividends’.Retrieved March 2023, from Gartner.com: https://www.gartner.com/document/code/776095?ref=authbody&refval=4022659
Hammer, P. D., Elliot, B. & Hare, J., 2022. Applying AI in industries. [Online] Available at: https://www.gartner.com/document/code/726651?ref=authbody&refval=4004028 [Accessed March 2023].
Kshetri, N. (2021, January 4). The Role of Artificial Intelligence in Promoting Financial Inclusion in Developing Countries. Journal of Global Information Technology Management, 24(1), 1-6.
Mullen, A. 2023. Artificial Intelligence Primer for 2023. [Online] Available at: https://www.gartner.com/document/code/779177?ref=ki-10545 [Accessed March 2023].
Sau, M. et al., 2022. Infographic: Artificial Intelligence Use-Case Prism for the Banking Industry. [Online] Available at: https://www.gartner.com/document/code/734650?ref=authbody&refval=4004018 [Accessed March 2023].
Sau, M. et al., 2023. Infographic: Top Priorities, Technologies and Challenges in Africa for 2023. [Online] Available at: https://www.gartner.com/document/4022659?ref=solrAll&refval=359551898 [Accessed March 2023].
Thowfeek, M. H., Nawaz, S. S., & Sanjeetha, M. B. (2020, December). Drivers of Artificial Intelligence in Banking Service Sectors. Solid State Technology, 63(5), 6400-6411.
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