Asia-Pacific’s FSI Organizations with AI Expect 41% Improvement in Competitiveness by 2021

• 52%
  of FSI organizations in Asia-Pacific have started on their AI journeys, and are
  ahead of other industries in the region
• To
  reap higher benefits from AI, FSI organizations need to improve on their
  Capabilities, Infrastructure, Strategy and Culture readiness

SINGAPORE -�Media OutReach - 24 September
2019 – Today, 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[1], 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.

“The
digital economy has resulted in demands for organizations to reinvent
themselves such that they remain relevant to their customers. To do so, FSI
organizations 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 on partnerships to drive innovation to stay ahead of the game,”
said Connie Leung, Senior Director, Financial Services Business Lead, Microsoft
Asia.

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.).

Fig
1: FSI organizations with AI are
already seeing benefits in these five areas, with expected improvements of up
to 2.1x by 2021

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.

 

“AI
is a critical technology in driving financial transformation, and it is of
great significance to tap into the convergence of AI and financial
services,” said Li Yimei, General Manager, AMC.

 

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.

 

“Companies
still face challenges in maximizing AI’s ability to accelerate their
transformation journeys. Often, they are hindered by various challenges that
spread across infrastructure, skills and culture. Hence, we need to look at AI
deployment and development from a more holistic perspective,” said Victor Lim,
Vice President, Consulting Operations, IDC Asia/Pacific.

 

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.

Fig 2: AI Readiness Model (Asia-Pacific’s AI
Leaders vs FSI Organizations). Scores indicated are metrics for FSI
organizations evaluated for the study and is based on a scale of 1.0 to 4.0

 

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.

 

“Small
business is the engine room of Australia’s economy. It’s where most people
work, and without small business, big business simply cannot function. The
vision of Moula in terms of liberating the value in small business data is
impressive, and the partnership with BizData using Microsoft technology to
bring that vision to life is a prime example of collaboration across our
ecosystem to bring about not just business transformation, but sector
transformation,” said Paul Pesavento, Chief Data Officer, Moula.

 

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

 

“To
drive transformation, AI needs to be driven at the highest levels within the
organization. Business leaders not only need to address data and infrastructure
requirements but will also need to have a clear vision and encourage a continuous
learning culture to empower staff across all levels to harness the potential of
AI,” said Lim.

 

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. “Overall, workers are more skeptical than
business leaders about cultural readiness within the organization. There is
clearly much more to be done at the top to encourage empowerment, innovation
and greater collaboration for FSI organizations to unlock the potential of AI and
deliver new revenue streams that will in turn improve bottom-line performance,”
said Leung.

Fig 3: Respondents feel that cultural traits
required for AI adoption are lacking within organizations today

 

“Today,
majority of FSI institutions have created a single customer view to drive
greater operational efficiencies with the aim of delivering more personalized
service. However, less than 20% of FSI organizations have integrated their
operational data[2],
which means that data is still sitting in siloes and not used across functions
and teams. Only business leaders who are able to bring the entire institution
together to harness data and AI seamlessly stand a chance of unlocking new
revenue sources in the long run,” added Lim.

 

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

 

“The
industry needs workers who possess the right skills to support organizations in
their AI journeys.” said Leung. “Beyond upskilling and reskilling employees, business
leaders must possess a continuous learning mindset to counter rapid changes
brought about by digital transformation. On that front, Microsoft has launched
the AI Business School to help business
leaders strategically implement AI within the organization, especially in
meeting the needs of shareholders, customers and regulators.”

 

To
learn about how AI can make a difference in FSI institutions, visit https://www.microsoft.com/en-us/enterprise/financial-services/banking-and-capital-markets

 

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