Human Managed, a prominent data and artificial intelligence (AI) platform based in Singapore, has recently released a compelling white paper titled “Better Intelligence Is Collective: Unlocking the Potential of AI with Federated Learning.” This document, developed in collaboration with industry giants such as Microsoft, Snowflake, and PayNet, explores the transformative potential of federated learning technology. Its primary focus is on guiding enterprises and business leaders in the ASEAN region towards exploiting federated learning for improved data privacy, risk assessment, and innovative business models.

In today’s digitally driven economy, many organizations face the challenging task of balancing data utilization with privacy concerns. Federated learning, a decentralized method of training machine learning models without the need to transfer sensitive data, has emerged as a viable solution. This approach allows organizations to collaborate on shared insights while keeping individual data sets secure. Banking institutions, healthcare providers, and insurance companies are just a few sectors that stand to benefit significantly from this method.

The white paper emphasizes that federated learning could significantly enhance critical business functions like credit risk scoring, digital identity authentication, fraud management, and patient confidentiality in healthcare settings. By harnessing the collaborative power of federated learning, these sectors can accelerate their digital transformation initiatives and enhance operational efficiencies.

Consider the banking industry. Traditional risk assessment often relies on centralized datasets, which can compromise both data integrity and privacy. By utilizing federated learning, banks can assess credit risk collaboratively while protecting customer information. This technique not only strengthens privacy but also enhances the accuracy of the assessments through the collective knowledge of multiple financial institutions.

The paper further highlights the role of central authorities, such as central banks and healthcare regulators, in advocating for federated learning. As data privacy demands intensify, these entities can promote a cohesive strategy that benefits entire sectors. This collaborative framework can address shared challenges and drive industry-wide improvement.

Key findings from the white paper reveal a growing interest in federated learning across various industries. With the increase in data privacy regulations like the GDPR in Europe and similar initiatives in ASEAN, businesses are searching for innovative solutions to adhere to these guidelines while still leveraging data for growth. Both the healthcare and automotive sectors, particularly in areas like autonomous vehicles, are uniquely positioned to benefit from federated learning applications. However, the white paper notes that federated learning is still in its infancy in the ASEAN region, presenting a significant opportunity for enterprises willing to explore its applications.

According to Karen Kim, the CEO of Human Managed, “Better intelligence is the result of real-time, cross-collaborative exchange and sharing among multiple parties.” This reflects a broader industry sentiment about the importance of collaborative innovation in improving services while safeguarding individual data rights. Karen’s insights underline Human Managed’s commitment to education and collaboration among stakeholders in the ASEAN region.

Rishu Saxena, Principal Specialist for AI/ML Strategy at Snowflake, stresses the economic implications of federated learning in the context of ASEAN’s growth. He notes that “regional public and private intelligence sharing… while ensuring data privacy will become increasingly important.” This combination of safeguarding privacy and enabling intelligence sharing could become a cornerstone of the ASEAN economic framework.

In the quest for improved security, Aloysius Chong Kin Faa, Head of Fraud and Projects at PayNet, emphasizes that federated learning is a game changer. “It represents a significant opportunity for enhancing intelligence across sectors while maintaining data privacy and security.” This highlights not only the technological but also the social and regulatory aspects of implementing federated learning systems.

According to market analysis, the federated learning market was valued at USD $133.1 million in 2023 and is projected to grow at a robust compound annual growth rate (CAGR) of 10.2%, possibly exceeding USD $311 million by 2032. This growth trajectory reflects the increasing recognition of the potential benefits associated with decentralized learning methods.

In conclusion, Human Managed’s white paper on federated learning serves as a timely guide for enterprises looking to navigate the complex landscape of data privacy and collaboration. As industries across ASEAN grapple with the demands of a digital economy, embracing advanced technologies like federated learning can yield not only strategic advantages but also foster a culture of trust and collaboration. Enterprises that recognize this potential will be well-positioned to thrive in an increasingly interconnected world.