Microsoft Asia and IDC Asia-Pacific released findings specific to the Financial Services Industry (FSI) from the study Future Ready Business: Assessing Asia-Pacific’s Growth with AI , which found that organizations with AI expect to see 41% improvement in competitiveness in three years.
The study also found that more than half (52%) of the region’s FSI organizations have already started on their AI journeys. This is higher than the Asia-Pacific average of 41%, indicating that the sector is more advanced than others in the region.
FSI organizations that have already started on their AI journeys saw improvements in areas such as better customer engagement, higher competitiveness, accelerated innovation, higher margins, and improved business intelligence,recorded in the range of 17% to 26%.
By 2021, organizations expect between 35% to 45% improvements in these areas, with the biggest jump in the rate of higher margins (estimated increase by 2.1x.).
An example of a company that has started its AI journey is China Asset Management Company (AMC). AMC serves more than 46,000 institutional clients and 110 million retail investors, with US$153 billion in assets under management. When it comes to quantitative investment — a method of analyzing data like price and volume to calculate which stocks to buy or sell and when — the tricky part is collecting the right data from the mountains of information available. Additionally, financial data is “noisy,” meaning there are many potentially misleading signals that need to be filtered out.
To overcome these challenges, the company turned to Microsoft Research Asia (MSRA) to build the “AI+Index Enhancement” machine learning model for fund managers and traders. The model helps them to make better informed buy-and-sell market decisions that bring in higher returns for their investor clients. Designed to sift through and analyze vast amounts of real-time financial data, the model is now undergoing testing, and is well ahead in performance when compared against the market or specific indexes.
FSI organizations need to build on capabilities, infrastructure, strategy and culture
The study found that 9 in 10 business leaders from the FSI sector agree that AI is instrumental to an organization’s competitiveness. However, the top adoption challenges faced by FSI organizations include lack of skills, resources and continuous learning programs, lack of thought leadership and lack of advanced analytics and tools.
The study evaluated six dimensions contributing to the AI Readiness of the industry, including Strategy, Investments, Culture, Capabilities, Infrastructure and Data. While FSI organizations are ahead of the average Asia-Pacific organization in all dimensions, they are lagging AI Leaders in areas like Capabilities, Infrastructure, Strategy, and Culture.
AI Leaders make up 6% of organizations in Asia-Pacific. These Leaders have already incorporated AI into their core business strategy and nearly doubled their business benefits today as compared to other organizations.
Compared to the rest of the organizations in Asia-Pacific, AI Leaders are more likely to:
- Increase investments every year to support an organization-wide AI strategy;
- Have a centralized team of specialized roles to develop and validate AI models for the organization;
- 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.
One key example of an AI leader is Moula, an Australian founded organization that uses AI to assess business loan applications made online. Recognizing the importance of small and medium businesses to Australia’s economy — most of the country’s 2.3 million businesses are classed as SMB — the company established an Azure based real-time credit decisioning service and leveraged Azure AI and machine learning capabilities to predict the probability of the SME 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.
Another example of an AI leader is MoneySQ, a leading FinTech company in Hong Kong that has launched its K-Cash personal loan platform, leveraging AI to analyze the financial profiles of loan applicants to deliver faster loan experiences for its customers. The platform, built on Azure and coupled with homegrown AI algorithms from KBQuest’s AI-Knowie solution, assists employees by reducing the time taken 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.
ICICI Lombard partnered with Microsoft to develop India’s first AI-enabled car inspection feature in its mobile app, “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 an insurance personnel to be present for inspections. The app allows customers to buy or renew policies anytime, anywhere by uploading pictures of their car, without the need for physical inspection by insurance inspectors. 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.
With AI, the company is processing 150 to 200 renewals per day and is close to rolling out AI-enabled claim processes via the app. ICICI Lombard aims to process more than 80,000 simple claims every month with same-day turnaround when the module is live at the end of 2019.
C-level executives must adopt AI-driven culture for organizational-wide transformation
The study found that almost 50% of FSI business leaders and more than half of the sector’s workers believe that the cultural traits and behaviors that contribute to organization-wide AI adoption are not pervasive today.
Technological and social-emotional skills required in an AI-ready workforce
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 FSI industry, the study identified an acute shortage of technological and social-emotional skills. The top three skills identified by business leaders that will face demand issues include scientific research and development, digital skills, as well as adaptability and continuous learning.
To learn about how AI can make a difference in FSI institutions, click here.