Banking on AI
Financial services industry in Asia is ahead of other sectors in AI adoption and is starting to see benefits, says Microsoft study
Financial services organisations that have adopted artificial intelligence (AI) expect to see a 41% improvement in competitiveness within three years, according to a new study by Microsoft Asia and IDC Asia-Pacific.
More than half (52%) of the financial services organisations in Asia-Pacific have already started on their AI journeys. This is higher than the average of 41% for all industries, indicating the sector is more advanced than others in the region. The findings are contained in “Future Ready Business: Assessing Asia-Pacific’s Growth with AI”.
“The digital economy has resulted in demands for organisations to reinvent themselves to remain relevant to their customers,” said Connie Leung, senior director and financial services business lead with Microsoft Asia.
“To do so, financial services organisations need to address three key imperatives: how to leverage data and AI for their operations, how to build and maintain trust among their customers, and how to tap partnerships to drive innovation to stay ahead of the game.”
Financial services organisations that have already begun adopting AI report improvements in areas such as better customer engagement, higher competitiveness, accelerated innovation, higher margins and improved business intelligence, recorded in a range of 17% to 26%, according to the survey.
By 2021, they expect improvements of between 35% and 45% in these areas, with the biggest jump in the rate of higher margins (estimated increase of 2.1 times).
Among those making good use of AI is China Asset Management Company. It serves 46,000 institutional clients and 110 million retail investors, with US$153 billion in assets under management. When it comes to quantitative investment — analysing data such as price and volume to calculate which stocks to buy or sell and when — collecting the right data from the mountains of information available is a challenge.
The company turned to Microsoft Research Asia to build the “AI+Index Enhancement” machine-learning model for fund managers and traders. It can help make better informed buy and sell decisions that bring in higher returns. Now undergoing testing, the model is well ahead in performance when compared with the market or specific indices.
ADOPTION CHALLENGES
The study found nine out of 10 business leaders from the financial services sector agree AI is instrumental to an organisation’s competitiveness. However, the top adoption challenges include lack of skills, resources and continuous learning programmes, lack of thought leadership and lack of advanced analytics and tools.
The study evaluated six dimensions contributing to AI readiness: strategy, investments, culture, capabilities, infrastructure and data. While financial services firms are ahead of other sectors in Asia-Pacific in all dimensions, they lag the AI leaders in capabilities, infrastructure, strategy and culture.
AI leaders make up only 6% of organisations in Asia-Pacific. They have already incorporated AI into their core business strategy and nearly doubled their business benefits today as compared with other organisations.
Compared to other organisations, AI leaders are more likely to:
Increase investments every year to support an organisation-wide AI strategy;
Have a centralised team of specialised roles to develop and validate AI models;
Have advanced AI analytics and tools such as robotic process automation and natural language processing in their existing technology mix;
Have in-house capabilities of developers, specialists and data engineers;
Have ongoing enterprise data governance practices jointly performed by IT, business and compliance teams.
Among the AI leaders is Moula, an Australian organisation that uses AI to assess business loan applications made online. It uses an Azure-based realtime credit decision-making service and Azure AI and machine-learning capabilities to predict the probability of an small business being able to pay back its loan. Successful applications can result in business loans of up to $500,000 being made available in 24 to 48 hours.
‘LOAN MACHINE’
Another leader is MoneySQ, a Hong Kong fintech company. Its K-Cash personal loan platform uses AI to analyse the financial profiles of applicants to deliver faster loan experiences. The platform, built on Azure and coupled with homegrown AI algorithms, reduces the time needed by staff to review and approve loan applications. And it does so with greater accuracy and precision.
With this capability, borrowers can now walk up to a “loan machine”, apply for a loan, get approval and receive cash instantly, whereas previously, this would take days.
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AI leaders — only 6% of organisations in Asia-Pacific
— are those that have already incorporated AI into their core business strategy and nearly doubled their business benefits compared with other organisations.
ICICI Lombard partnered with Microsoft to develop India’s first AIenabled car inspection feature in its mobile app, called Insure. The company saw AI as a solution to reduce the time needed to evaluate renewals or claims, which can take up to days, and is also resource-intensive as it requires insurance personnel to be present.
The app allows customers to buy or renew policies anytime, anywhere by uploading pictures of their car, without the need for physical inspection. AI and machine learning identify damage quickly from the uploaded pictures and provide an estimated repair cost in seconds. This ensures that insurance inspectors focus on addressing complex claims like head-on collisions that require a skilled evaluation.
Significantly, the study found 62% of business leaders and 67% of workers agree that AI will augment — rather than displace — jobs. Despite being generally positive about the impact AI will bring to jobs in the financial services industry, the study identified an acute shortage of technological and social-emotional skills.
The top three skills identified by businesses that will face demand issues include scientific R&D, digital skills, and adaptability and continuous learning.