FSI players in APAC expect to be 41% more competitive thanks to AI

More than half of financial services industry (FSI) players in Asia Pacific are adopting AI and 41% of them expect to see 41% improvement in competitiveness in three years.

According to a new report from Microsoft Asia and IDC Asia Pacific, AI adoption in the region — at an average of 41% —  is more advanced compared to other regions.

The study shows that FSI firms 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, organisations expect between 35% to 45% improvements in these areas, with the biggest jump in the rate of higher margins, estimated at more than twice.

Even them, the study finds that FSI organisations need to build on capabilities, infrastructure, strategy and culture.

Findings show that while nine in every 10 business leaders from the FSI sector are keen on AI, organisations 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 organisations are ahead of the average Asia-Pacific firms in all dimensions, they are lagging AI Leaders in areas like Capabilities, Infrastructure, Strategy, and Culture.

AI Leaders make up 6% of firms in Asia-Pacific, and have already incorporated AI into their core business strategy and nearly doubled their business benefits today as compared to other organisations.

Compared to the rest of the organisations in Asia-Pacific, 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 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.