In the financial services industry, artificial intelligence (AI) is emerging as a transformative force, promising to reshape the way institutions operate, innovate, and compete on a global scale. However, challenges including AI talent scarcity and limited collaboration between financial institutions and AI fintech startups.
A study conducted by global consultancy Oliver Wyman in collaboration with the Monetary Authority of Singapore (MAS) explores how cities like Singapore can become global hubs for AI in finance, examining the biggest challenges faced by ecosystem stakeholders and stressing the importance of attracting global AI talent, fostering AI investments, and promoting AI collaboration within the financial industry.
Singapore’s AI talent pool is insufficient
The Oliver Wyman study, which is based on in-depth interviews and surveys involving industry leaders and key players in the financial ecosystem, revealed challenges in sourcing strong AI talents, particularly individuals with five to ten years of industry experience.
56% of the ecosystem stakeholders polled said that Singapore’s AI talent pool wasn’t large enough, with scarcity extending across various AI-related positions, including principal data engineers, data analysts, lead AI scientists, and more.
The competition to attract global AI talent is fierce, with organizations from various sectors and locations competing for the same highly sought-after professionals, both locally and internationally.
To attract AI talent, stakeholders emphasized the availability of cutting-edge projects (98%) and the presence of prominent AI firms (96%) as important factors. These findings reflect the ambitions and drive in today’s AI talents, who are looking for high-impact use cases and projects for their career development.
Livability considerations (96%), such as the cost of living and the ease of cultural assimilation, are also one of the top factors which attract global AI talents. This trend is evidenced by many prominent big tech companies and AI research firms offering compelling salary packages to fortify their competitive edge.
Low collaboration
Besides attracting AI talents, the study also revealed a lack of successful collaboration between financial institutions and AI fintech startups. For many AI fintech companies offering business-to-business (B2B) solutions, collaboration with financial institutions is essential for achieving innovation and success. However, concerns regarding regulations, security, compliance, and reliability create barriers for financial institutions when considering collaboration with fintech companies.
One major issue highlighted in the Oliver Wyman report is the lack of understanding of use cases. Financial institutions struggle to openly share their challenges with AI fintech startups, resulting in a disconnect between incumbents and startups. This leads to a shortage of tailored solutions, frustrating financial institutions and hindering deeper collaboration.
Furthermore, data scarcity for model training poses a significant obstacle. Numerous AI solutions require extensive datasets to train, validate, develop, and refine models, and oftentimes, these datasets are subject to regulations and inaccessible. According to Oliver Wyman’s survey, 82% of stakeholders said they found accessing data for AI-based solutions challenging.
Nurturing Singapore’s AI fintech scene
To attract and nurture AI fintech companies, Oliver Wyman advocates for the establishment of incubators and accelerators focused on AI in finance to provide startups with mentorship, exposure to investors, and a conducive growth environment.
Additionally, the implementation of a comprehensive, government-endorsed accreditation framework tailored specifically for AI fintech companies can boost the confidence of financial institutions in AI fintech solutions. This accreditation, if aligned with global standards, could not only enhance credibility for domestic collaboration but also facilitate international expansion. It would also serve as an incentive for overseas AI fintech companies to consider relocating to Singapore.
To enhance talent quality and accessibility, Oliver Wyman advises stakeholders to implement upskilling programs and build a global network of AI expertise. Regulators can explore the introduction of mentorship or apprenticeship schemes, connecting young AI talents with leading technology firms involved in cutting-edge AI projects, both locally and internationally.
Financial institutions, meanwhile, should equip their senior leadership with comprehensive AI knowledge and offer specialized courses. These courses could cover essential topics, such as generative AI and other transformative innovations in the field.
Finally, establishing a globally interconnected network of AI expertise and knowledge is crucial for smaller countries to compete with larger AI hubs in terms of local talents and firms. Such collaborations could drive innovative technological advancements, contribute to the growth of AI hubs, and help retain talent, Oliver Wyman says.
AI in finance
AI holds tremendous potential in finance, with McKinsey estimating that AI technologies could deliver up to US$1 trillion of additional value each year for the global banking industry. This would be achieved through increased revenues through personalized services, cost efficiencies, and the uncovering of new and previously unrealized opportunities using data.
In the AI domain, Singapore is swiftly becoming a major hub for investment, drawing significant venture capital (VC) funding. According to Oliver Wyman, the city-state has attracted about US$3 billion in VC funding so far, making it one of the world’s top ten countries in AI investments. This appeal is credited to Singapore’s robust global branding, stability, and favorable regulatory environment, a sentiment echoed by 68% of respondents in the study who acknowledged the strong availability of VC funding in Singapore.
Featured image credit: edited from freepik