COVID-19 is often highlighted as the main reason for the acceleration in digital transformation and the adoption of new technologies such as AI.
However, a new IBM report noted that part of the reason is that Hong Kong financial institutions have not fully optimized the potential of customer data. Now, with customers shifting their behaviors and competition increasing, they are now re-focusing on customer data.
This one conclusion from a recent IBM report titled “Navigating the New Normal.” Billed as the first industry-focused report from IBM, it examined the business dynamics impacting Hong Kong’s banking and financial services landscape today. These included the ongoing COVID-19 pandemic, heightened market competition and lucrative yet uncertain prospects of the Greater Bay Area (GBA).
The report surveyed 35 senior banking executives from 20 traditional banks and virtual banks in Hong Kong and was conducted in the third quarter of 2020. It revealed that the top three technology investment priorities are innovations for open banking collaboration, digital marketing, and customer experience management.
Tying all these initiatives is customer data. Sixty-seven percent of respondents said this type of data will help define their digital strategy and vision. More than 70% are planning to increase technology investment to retain customers, while almost half want to strengthen their advocacy model.
Part of the reason for the refocus on customer data is the failure of financial institutions to maximize their customer data advantage before the pandemic. Seventy-five percent of surveyed financial institutions claimed to utilize less than 30% of collected customer data. As a consequence, over 90% stated that they relied on external data sources to deepen customer engagement and up-sell.
Shifts in customer spending patterns amid the pandemic have given rise to new demands for financial services. In turn, this is making data partnerships imperative to gleaning deeper market insight from external data sources.
Yet, 86% of respondents believed that data privacy will be a major challenge to forming data partnerships. IBM advised financial institutions to invest in capability such as the Federated Machine Learning Model to overcome the regulation boundary and co-develop machine learning models to create an AI that can provide insights from a more nuanced and wider perspective of the market.
“Our new reality will be punctuated by unpredictable relapses of social distancing measures, thus we can expect the banking industry to struggle with preserving the deep level of personal intimacy they once had with their customers. It is therefore critical that banks tighten customer connection across their existing digital customer journey and put humanized engagement back at the center of the product and service delivery experience by becoming cognitive enterprises,” added David Chow, general manager and partner at global business services at IBM Hong Kong.
The development of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and the Wealth Management Connect (WMC) scheme figured highly in the report. Eighty-one percent of respondents identified OpenAPI as the most relevant technology in the next two to three years as a means to capture growth opportunities in the GBA.
Given that GBA’s market size is approximately 10 times that of Hong Kong, financial institutions need to capture the expanded customer base by leveraging digitally-enabled collaborations to differentiate and extend their unique brand value beyond standard financial products and services.
The virtual bank business model which will be driven by innovation will also shape the market. However, the report noted that few virtual banks possess the adequate resources necessary to enter the market on their own.
Instead, 70% of respondents said they believe that tech giants will lead the disruption in the banking industry. Penetrating critical masses through large external platform partnerships may be key to future growth for HK financial institutions.
Image credit: iStockphoto/Andrey Suslov