How AI is Reshaping Banking in 2023 – Fintech Singapore

In recent years, the Artificial Intelligence (AI) growth in the finance market has been considerable, with the sector projected to expand to an astonishing US$ 1,591.03 billion by 2030 at a Compound Annual Growth Rate (CAGR) of 38.1 percent.

A study revealed that it is estimated that adopting AI in Southeast Asia could add an estimated US$1 trillion to the region’s Gross domestic product (GDP) by 2030. IDC reported that Asia/Pacific spending on AI systems (including hardware, software, and services) will rise to around US$46.6 billion in 2026.

A survey also revealed nearly half of the financial institutions expect AI to increase their annual revenue by at least 10 percent, while over a third anticipate a decrease in annual costs of the same measure. The respondents credit AI with enhancing customer experience (46 percent), operational efficiencies (35 percent), and reducing total cost of ownership (20 percent).

This transformative shift towards AI in finance has led to several remarkable advancements in 2023. Here, we take a look at some of these significant developments.

Enhancing fraud prevention mechanisms

Fraudulent activities pose a significant threat to financial institutions. Still, the advent of AI has revolutionised the fight against such malpractices by bolstering anti-money laundering protocols and enhancing electronic Know-Your-Customer (eKYC) processes.

By harnessing the power of machine learning algorithms, complex data sets can be analysed with precision, enabling the identification of suspicious patterns and activities. This proactive approach allows for the early detection of potential fraud, thus mitigating its detrimental effects.

As a result, AI’s role in fraud detection has grown increasingly pivotal, fostering a safer and more secure financial ecosystem.

An example of AI’s impact is in Singapore’s DBS, where the bank employs AI to reduce false positives and prioritise alerts. This strategy enables analysts to dedicate more time to higher-risk activities, optimising their efforts. DBS leverages AI programs to gather and process vast amounts of bank data necessary for making informed decisions on alerts.

Simultaneously, biometrics, encompassing physical or behavioural characteristics uniquely identifying individuals, are gaining prominence in the financial industry.

Leveraging AI technology, the analysis and verification of biometric data can be significantly enhanced, presenting various applications, including secure authentication, fraud prevention, and even customer service enhancements.

For instance, AI-powered systems facilitate the verification of customers’ identities through facial or voice recognition, augmenting traditional methods and adding an extra layer of robust security. This integration of AI into biometric authentication fortifies the protection of sensitive financial information and streamlines and enriches the overall customer experience.

Wide-ranging application potential

The finance industry is keenly aware of the immense potential of AI and machine learning (AI/ML) technologies and eagerly anticipates their widespread adoption across various sectors.

These advanced technologies present numerous opportunities for enhancing financial reporting, financial planning and analysis, sales and revenue forecasting, customer service, and marketing strategies.

One remarkable transformation of AI/ML technologies is in credit decision-making processes. Through comprehensive analysis of multiple factors, these technologies enable banks and credit lenders to make more intelligent underwriting decisions and accurately assess traditionally underserved borrowers.

AI algorithms can even predict potential defaulters, allowing institutions to reduce credit risk and improve the overall performance of their portfolios.

Moreover, AI/ML technologies can automate repetitive tasks and offer valuable insights, empowering financial institutions to optimise their operations and make well-informed business decisions. These technologies drive efficiency and enhance performance by streamlining processes and leveraging data-driven analysis.

Singapore takes the lead in integrating AI and ML in the fintech sector, boasting an impressive penetration rate of 5.36 percent.

This remarkable level of adoption, combined with the country’s substantial economic development, accounting for approximately 0.5 percent of the world’s GDP, solidifies Singapore’s position as a global leader in AI.

The digital insurance sector is also experiencing rapid growth, with an average annual rate of 35.6 percent. This expansion can be attributed to the increasing utilisation of AI and ML technologies, which enable insurance companies to improve their operations, enhance customer experiences, and provide more personalised services.

Delivering personalised digital experiences

The rapid expansion of digital banking and financial services has underscored the importance of delivering personalised digital experiences to customers. In this evolving landscape, AI-based recommendation systems have emerged as powerful tools for financial institutions.

These recommendation systems leverage user data to gain insights into customer preferences and behaviours. This enables financial institutions to offer tailored product recommendations and services, ultimately boosting customer satisfaction and engagement.

Singapore’s UOB has made strides by launching TMRW, an AI-powered mobile-only bank catering to the millennial market. This offering showcases the bank’s commitment to leveraging AI to provide comprehensive solutions that meet the needs of the younger generation.

Using Natural Language Processing (NLP) and chatbots is also gaining traction within the financial services industry. Chatbots, equipped with NLP capabilities, have proven effective in automating repetitive customer service tasks such as answering queries, processing transactions, and providing account information.

By offering instant responses and personalised assistance, chatbots significantly contribute to enhancing the overall customer experience. Their ability to provide real-time support and address customer needs efficiently is invaluable in driving customer engagement.

Integrating AI technologies into financial services has witnessed notable progress in Southeast Asia.  Most Asian banks now have their iteration of a chatbot, either created as white-label solutions or developed internally. For instance, DBS bank introduced Digibot designed to enable customers to make transactional requests such as check pending transactions, check cheque status, enquire on reward points and loans application.

By analysing customer data and delivering personalised financial advice, this AI-powered chatbot streamlines processes, reduces operational costs and elevates the customer experience. 

Impact on quantitative trading and financial risk management

AI has brought about a significant transformation in the finance industry, particularly in quantitative trading and financial risk management. These technologies have revolutionised how financial markets operate by enabling market trends analysis, optimisation of trading strategies, trade execution, and risk management.

Traditionally, quantitative trading relied heavily on traders’ analysis and judgment of various factors influencing stock prices to construct trading strategies. However, intelligent quantitative trading empowered by AI can independently gather a more extensive and diverse range of data.

By processing this data, it can perform logical deductions and identify previously overlooked characteristic factors not considered in traditional quantitative trading.

AI-based systems also can process vast amounts of data to assess creditworthiness and make lending decisions. This improves the efficiency of the lending process while reducing the risks of defaults. Furthermore, AI can extract valuable insights from alternative data sources, enabling loans to be extended to individuals who lack a credit history.

An example in the Philippines is UnionBank, which has leveraged AI-powered credit scoring models to generate credit scores for the unbanked population using alternative data sources. This initiative expands credit access for individuals previously excluded from traditional banking services.

AI and Robo-advisors

AI-powered robo-advisors have become popular for individuals seeking financial advice and investment management solutions. With their automated capabilities, these robo-advisors are transforming the finance industry.

These automated platforms, including startups like Endowus and Syfe in Singapore and Robowealth in Thailand, are reshaping the finance landscape.

Forecasts indicate that the robo-advisors market will grow substantially, with an estimated 24.16 million users anticipated by 2027. Furthermore, the assets under management are projected to experience an impressive annual growth rate (CAGR 2023 to 2027) of 14.47 percent, culminating in a total value of approximately US$190.90 billion by 2027.

The allure of robo-advisors lies in their ability to provide personalised recommendations tailored to the customer’s specific financial goals, risk preferences, and current financial situation. 

These automated platforms can adjust investment portfolios by continuously monitoring market fluctuations. As a result, they offer a convenient and hassle-free way for individuals to engage in investing.

With the integration of AI technology, robo-advisors have streamlined the financial decision-making process, empowering users with accessible and efficient investment management solutions.

Regulatory Measures for AI

Financial institutions in Southeast Asia have made remarkable strides in adopting AI technologies across various applications. However, as AI continues to advance rapidly, regulators worldwide are actively working on formulating comprehensive regulations to govern the use of generative AI.

In February, ministers from the Association of Southeast Asian Nations (ASEAN), consisting of 10 member countries, agreed to develop an ASEAN “AI guide” for the region’s population of 668 million people. While discussions among regional policymakers have not been previously reported, this initiative highlights the significance and recognition of AI’s impact on the financial landscape.

Singapore, known for its forward-thinking approach, has introduced the world’s first AI Governance Testing Framework and Toolkit, named A.I. Verify. This initiative aims to promote transparency and ethical usage of AI between companies and their stakeholders through technical assessments and process checks.

Meanwhile, the Monetary Authority of Singapore (MAS) has released an open-source toolkit to enable the responsible use of AI in the financial industry.

The Veritas Toolkit version 2.0 comes on the back of an earlier version released in February 2022 that focused on the assessment methodology for fairness. The latest version, developed by a MAS-led consortium of 31 industry players, has an expanded scope to include the assessment methodologies for ethics, accountability and transparency principles as well.

These recent developments mark a transformative shift in the finance industry, ushering it into a new era of digital intelligence. Enhanced efficiency, personalised experiences, and heightened security characterise this era. AI’s role in finance has surpassed the experimental phase, firmly establishing itself as a fundamental component of next-generation financial services.