The Malaysian government’s priority is to transform the nation into a high-income digital economy leader. Their strategy centres around harnessing technology to boost productivity, foster inclusivity, and stimulate innovation. This approach entails ensuring that the advantages of digital progress reach all segments of society, enhancing competitiveness for established enterprises, and cultivating a conducive ecosystem that nurtures pioneering ventures. 

Recognising the rapid advancements in artificial intelligence worldwide, the Malaysian financial services industry is proactively transitioning to generative AI to remain competitive. By embracing this transformative technology, the country aims to drive innovation, increase productivity, and improve various sectors of the economy.  

According to IBM, despite the increasing adoption of AI, only 35% of companies have currently integrated it into their operations, while an additional 42% are actively exploring its potential. However, the financial services industry is experiencing a significant upsurge in the utilisation of Generative AI, a specialised branch of artificial intelligence focused on generating new data or content based on patterns extracted from existing data. 

The financial services industry acknowledges Generative AI’s potential in tasks like fraud detection, risk assessment, personalised customer experiences, and market analysis. With its transformative impact, including hyper-personalised content creation and streamlined processes, embracing this innovation today promises future growth, increased productivity, and limitless possibilities for the industry. 

However, the financial services industry encounters challenges, similar to other sectors, in transitioning Generative AI projects from pilot stages to successful production, with only a portion achieving the desired outcomes.  

To effectively adopt Generative AI, the financial services industry must have the capability to both understand the decision-making process of AI models and effectively communicate it to regulators, customers, and internal stakeholders.  

Transparent and interpretable AI systems play a crucial role in building trust as they allow users to understand how the AI arrives at its decisions, enabling them to validate the results and have confidence in the technology’s reliability. These systems also facilitate regulatory compliance by providing auditable and accountable processes, ensuring that AI applications adhere to the necessary rules and standards. 

AI-First Mindset: Develop Clear Focus  

The lack of proper oversight in the financial services industry prevents them from identifying, quantifying, or managing the inherent risks associated with adopting such emerging technology. To harness the potential of Generative AI safely and responsibly, the industry must first understand its goals and the necessary changes required to achieve its vision of using Generative AI.   

Large Language Models (LLM): Train, Tune and Deploy 

By refining their parameter-tuning approach, organisations can unlock the true potential of LLMs, leading to improved productivity, better decision-making, and enhanced knowledge sharing throughout the entire organisation. 

Through the process of fine-tuning LLMs, the financial services industry can customise these models to automate specific tasks and domains, ensuring they provide more precise and contextually relevant outputs. This enables its effective deployment in various applications, including semantic search, document classification, language translation and summarisation. 

Facing Threats and Security Concerns with Generative AI 
In adopting Generative AI, organisations must priotitise cybersecurity and core banking modernisation to establish governance practices to protect data privacy, mitigate adversarial attacks, manage biases, safeguard intellectual property, and ensure secure deployment. Robust data governance, model evaluation, ethical review boards, continuous monitoring, and compliance measures are essential for responsible and secure adoption. 

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