New rules to navigate financial world powered by AI and automation

AS Industry 4.0 technologies become a growing reality in today's business landscape, it is vital for companies to address the urgent need to adopt and integrate such smart technologies.

Artificial Intelligence (AI), in particular, is shaping up to be a dominant force for transformation in the financial services sector. A study by Microsoft Asia and IDC Asia-Pacific revealed that half (52 per cent) of financial services organisations in the Asia-Pacific have already started their AI journeys.

IDC said that spending on AI in the region grew almost 54 per cent in 2019, compared to 2018, with the banking industry leading at 10.7 per cent of total spending; it is where AI is mainly used in fraud analysis and investigation, as well as automated customer service agents.

However, amid such rapid adoption of AI, the harnessing of AI technology for financial services is still very much in the preliminary stage. A global survey on the adoption of AI in businesses by McKinsey reported that only 21 per cent of respondents indicated the embedding of AI into multiple business units or functions.

In fact, many organisations still lack the foundational practices to create value from AI at scale - encumbered by factors such as shortage of tech talent, issues with replicating successful AI systems used in smaller business areas into the rest of the company processes, legacy tools and misunderstanding AI's impact on employment and privacy issues.

A framework

Last year, the Monetary Authority of Singapore (MAS) announced that it is working with the financial industry to create a framework to evaluate AI solutions and ensure they are fair, ethical, accountable and transparent. This is part of a broader national AI strategy announced last November to pave the way for a progressive and trusted environment for AI adoption within the financial sector.

Improvement in governance and accountability of board members will also help increase trust among stakeholders, aiding the push for the adoption of AI technology in overall business and financial services.

The value that AI brings to financial service providers is formidable. In the banking industry alone, McKinsey Global Institute predicts that AI and machine learning could generate more than US$250 billion in value. The IDC study has found that organisations are reaping the benefits from AI such as better customer engagement, higher competitiveness, accelerated innovation, higher margins and improved business intelligence.

To unlock the full benefits of AI, enterprises must consider how to deploy it effectively across the entire ecosystem rather than taking a siloed approach.

Integrating AI into an organisation's strategic objectives is key to driving a holistic, enterprise-wide adoption strategy. Companies need to get their employees on board and work alongside analytics experts to ensure that AI-driven initiatives address broad organisational priorities, and not isolated business issues. It also requires informed decisions on processes like recruiting skilled manpower to facilitate these AI adoption plans and devoting necessary resources to reskill and upskill current employees.

The benefits of AI are countless. These include being able to perform complex tasks at a fraction of the time needed by a human operator, producing insights and results that are more consistent and reliable, and the ability to complement human efforts.

To unleash the possible benefits and potential of AI, organisations need to embed AI into organisation-wide strategic plans where they can be utilised holistically in multiple development models. These implementations will require updated processing systems that can meet high demands for processing power, increased skilled manpower support that can operate and improve the AI technology used, and a secure infrastructure that can reduce the organisation's susceptibility to cyber attacks and data breaches.

While these factors will require monetary investments, financial assistance is available for companies to cushion the cost of integrating AI-powered tools and processes into their businesses. For instance, the MAS Artificial Intelligence and Data Analytics (AIDA) grant can be used to co-fund up to 50 per cent of project costs for companies leveraging AI and data analytics to generate insights, formulate strategy and assist in decision making.

AI-powered tools are also being used to refresh or autonomously manage customer engagement processes.

The market for such service providers is also rapidly expanding. Gartner predicts that by 2020, 85 per cent of customer interactions will be managed without a human, with AI further transforming customer engagement by providing real-time insights and personalised offerings.

A good example of how financial institutions are applying AI to customer engagement is the use of AI and predictive analytics to help customers manage their finances. In-app services that monitor customers' transaction data and patterns in real time and provide personalised notifications to make subscription payments and financial advice help customers feel more engaged with their service provider.

Meanwhile, AI-powered solutions such as chatbots and personal assistants are being used extensively in the financial industry today. Designed to simulate human interactions and provide immediate, personalised responses at any time of the day, chatbots eliminate frustrating delays and errors, particularly when handling customer complaints.

Another AI-related sector that is showing promising signs of growth is the use of voice assistants. UK-based analysts at Juniper Research estimate that there will be about 8 billion digital voice assistants in use by 2023, up from 2.5 billion assistants in use at the end of 2018. Financial services have also started to use voice assistants to automate customer services, simplifying the process of personal finance and wealth management. Its ability to be used for biometric validation creates a more secure platform for customers and merchants to complete their transactions, providing top-notch customer experiences.

A top business priority

In a future fuelled by automation and AI, data analysis and data-driven solutions must be at the top of one's business priorities.

Financial institutions must therefore take a collaborative approach to bring together real-time AI technologies and traditional banking services to more partners. This is part of the larger trend of open banking, which enables data sharing between banks and third-party providers through the use of application programming interfaces (APIs).

Several local banks in Singapore have already taken the lead and shared hundreds of APIs, empowered by multiple initiatives of the Singapore government over the past years, including the Asean Fintech Innovation Network.

Third-party developers can access these APIs for functions such as real-time payments. The availability of data will encourage more fintech organisations to develop unique AI-powered solutions at a speed faster than larger financial institutions could do on their own.

Collaboration is thus integral to achieving growth in an AI-powered future.

The ultimate goal of AI adoption is to drive business value by enabling the financial-services industry to develop new products and services, become more efficient and thus increase cost savings.

As organisations advance in their AI transformation journeys, adopting and integrating these smart technologies will impact financial and payment solutions at all levels of the financial services industry. Financial institutions will need AI to remain relevant in the years to come as merchants and customers demand more seamless and personalised experiences.

This process of evolution will likely continue well into the future, when we will see the emergence of new business models and with it, new rules of engagement. Above all, companies can also harness new possibilities if they are willing to rethink the meaning of business as usual.