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Enhancing growth, competitiveness via an AI journey

Sep 25. 2019
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By The Nation

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Microsoft Asia and IDC Asia/Pacific have 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 organisations with AI expect to see 41 per cent improvement in competitiveness in three years.

  The study also found that more than half (52 per cent) of the region's FSI organisations have already started on their AI journeys. This is higher than the Asia-Pacific average of 41 per cent, indicating that the sector is more advanced than others in the region.

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

  FSI organisations 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 per cent to 26 per cent.

  By 2021, organisations expect between 35 per cent to 45 per cent 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 analysing 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 analyse 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 of  AMC.

   The study found that 9 in 10 business leaders from the FSI sector agree that AI is instrumental to an organisation's competitiveness. However, the top adoption challenges faced by FSI organisations include lack of skills, resources and continuous learning programmes, lack of thought leadership and lack of advanced analytics and tools.

   "Companies still face challenges in maximising 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 organisations are ahead of the average Asia-Pacific organisation in all dimensions, they are lagging AI Leaders in areas like capabilities, infrastructure, strategy, and culture.

   AI Leaders make up 6 per cent of organisations 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 organisations.

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

  Compared to the rest of the organisations in Asia-Pacific, AI Leaders are more likely to:

  Increase investments every year to support an organization-wide AI strategy

  Have a centralised team of specialised roles to develop and validate AI models for the organisation

  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 organisation that uses AI to assess business loan applications made online. Recognising 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 analyse 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.

   "To drive transformation, AI needs to be driven at the highest levels within the organisation. 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 per cent of FSI business leaders and more than half of the sector's workers believe that the cultural traits and behaviour that contribute to organisation-wide AI adoption are not pervasive today. "Overall, workers are more skeptical than business leaders about cultural readiness within the organisation. There is clearly much more to be done at the top to encourage empowerment, innovation and greater collaboration for FSI organisations to unlock the potential of AI and deliver new revenue streams that will in turn improve bottom-line performance," said Leung.

   "Today, majority of FSI institutions have created a single customer view to drive greater operational efficiencies with the aim of delivering more personalised service. However, less than 20 per cent of FSI organisations 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.

   "The industry needs workers who possess the right skills to support organisations 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 organisation, especially in meeting the needs of shareholders, customers and regulators".

  168 business leaders and 94 workers from the FSI sector participated in this study, out of 1,605 business leaders and 1,585 workers in total.

   Business leaders: Business and IT leaders from organisations with more than 250 staff were polled.    Respondents were decision-makers involved in shaping their organization's business and digital strategy.

  15 Asia-Pacific markets were involved: Australia, China, Hong Kong, Indonesia, India, Japan, Korea, Malaysia, New Zealand, Philippines, Singapore, Sri Lanka, Taiwan, Thailand and Vietnam.

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