The three years of the global health crisis have underlined the importance of resilience, data privacy & monetization and banking DX.

The use of Big data has become an indispensable role in the finance industry.

By 2026 big data analytics in the banking industry is expected to have registered a compounded annual growth rate of 22.97%.

Data is quickly becoming a cornerstone of increasingly personalized service and improved efficiency. With super apps, digital-native fintechs and licensed digital banks drive up competition, the most optimal use of data will become the differentiating baseline for market viability.

This is where professionals like Joe Ong, Vice President & General Manager, ASEAN, Hitachi Vantara, can offer up some industry trends that are set to become a mainstay.

DigiconAsia: With a leap in growth in the use of AI and data analytics, what is the future looking like for the finance industry?

Joe Ong (JO): Before the inclusion of advanced data algorithms to their data storage/retrieval/DR backup systems, financial institutions struggled to find effective solutions for new possibilities surrounding advancements in financial services.

However, the constantly evolving state of AI and data analytics provides them with more developed and effective methods of storing data, and an added ability to repurpose data. Additionally, the analytics generated are being used to develop new products. Advancements in AI allow for increased digitalization of transactions, and financial institutions could situate data analytics to drive the development of new data-driven products and services.

AI advancements also foresee a steady improvement in customer experience, as the evolution of data-driven innovation has raised standards of customer satisfaction. By embracing digital transformation (DX), financial institutions are better positioned to offer customer-centric experiences that help in customer recruitment and retention.

Embracing AI and data analytics is proving to be a huge benefit for the finance industry and going forward, incorporating a strong data infrastructure will help institutions to continue achieving better outcomes, leverage innovation and efficiency, reduce operational costs and improve security resilience.

Joe Ong, Vice President & General Manager, ASEAN, Hitachi Vantara

DigiconAsia: How can organizations keep up with the implementation of Big Data in their financial offerings? What are the key strategies involved?

JO: Data integration has proven to be largely beneficial for various organizations, as the ability to harness control over rapid data generation allows them to effectively integrate data into their financial offerings to better understand their customer base, product performance, and market trends.

By equipping themselves with appropriate knowledge and skills regarding data implementation, financial institutions are better positioned to modernize operations and maximize the reach of the data to benefit operations and customers.

A few key strategies for ensuring that they are able to keep pace with the implementation of Big Data in their financial offerings are:

  1. adopting effective data governance practices
  2. delegating clear protocols for gathering and validating data
  3. ensuring that there is proper data leadership, in order to make certain that big data does not complicate financial offerings
  4. modernizing IT infrastructure to maintain a consistent cloud driven operating model
  5. rethinking of financial models to continually improve adoption of big data analytics

DigiconAsia: What cutting-edge technology is best suited for financial institutions to comply with increasingly strict data privacy and protection regulations?

JO: Financial institutions with specialized commercial and investment banking operations are aware that using cutting-edge technology—AI and ML—are the most effective approach to combat fraud.

Additionally, in order to leverage these sophisticated techniques to stay one step ahead of cybercriminals, financial institutions also need to use advanced analytics and enterprise-wide data storage capabilities.

Today, in the rapidly evolving world of bank fraud where new threats are being developed daily, AI is best positioned to provide defence. Additionally, speed detection, future-proofing and reducing false positives are also key measures that can be implemented to detect fraud.

Finally, AI natural language processing techniques can be used to classify and scan data to ensure security, privacy, and regulatory compliance, which allows for data to be safely accessed across the organization and in the public cloud.

DigiconAsia: Amid rampant crypto fraud, governments warning against crypto speculation, and with geopolitical trauma causing people to be wary of some cutting edge technologies, what are your views of AI and cybersecurity trends affecting the finance industry in ASIA/APAC?

JO: As financial services in the Asia Pacific region and around the world rapidly digitalize, cybersecurity has become a top business priority. The high-profile supply chain attacks and ransomware explosions of the last year did not occur in a vacuum. Financial services are being transformed by several fast-moving trends, including a sweeping move to the cloud, new fintech businesses gaining ground on existing financial institutions, and institutional and retail investors’ rising exploration of cryptocurrencies.

Because of this confluence of trends and threats, cybersecurity principles and priorities must be reimagined for an era of perpetual change and ever-more complex cyber hazards.

Today, financial institutions are putting money into improving third-party due diligence as well as operational resilience (i.e., the ability to stay running in the face of adversity).

In this quickly changing world, the following security principles should be part of a robust and systematic protocol for controlling cyber risks:

  1. Protect data
  2. Make sure vulnerabilities are patched quickly
  3. Reinforce existing defenses
  4. Share threat intelligence
  5. Build the corporate muscle memory to respond to attacks
  6. Strengthen third-party risk management
  7. Recruit and build diverse teams

DigiconAsia thanks Joe for taking the time to share his thoughts and insights with readers.