MALAYSIA’s small and medium enterprises (SMEs) are the backbone of the nation’s economy, comprising about 97% of all businesses and employing nearly half of the country’s workforce. 

Given their critical role, SMEs face unique challenges, particularly a lack of economy of scale, which limits their resources for extensive data processing and strategic analysis. 

GenAI presents a significant opportunity for these businesses by automating routine tasks, enhancing accuracy, and providing valuable insights without the need for extensive resources.

This technology can level the playing field, enabling SMEs to compete more effectively with larger enterprises.

Understanding GenAI

Traditional AI systems perform tasks based on specific data sets and rules, requiring labelled data and months to develop effective models.

In contrast, GenAI operates on foundation models that can process vast amounts of unstructured data, performing multiple tasks simultaneously through “prompt engineering.”

This allows for faster development and implementation, making GenAI a powerful tool for various applications.

Impact on Finance Professionals

GenAI significantly enhances finance operations. Traditional AI applications in finance cover tasks like time and expense management, management reporting, and reconciliations. 

GenAI can go further, developing comprehensive reports, extracting critical information for credit decisions, and creating detailed investor relations documents. 

This shift allows finance professionals to focus on interpreting data, making strategic decisions, and providing value-added insights.

For example, many organisations are leveraging AI to automate routine tasks, freeing finance professionals to analyse financial trends and advise on business strategy.

GenAI Across Business Functions

The integration of generative AI is also fundamentally transforming the role of finance professionals. Historically, finance roles involved extensive manual data processing and report generation.

But with the advent of generative AI, they can automate routine tasks such as reconciliations and report generation.

This allows finance professionals to dedicate their time to interpreting data, making strategic decisions, and providing value-added insights. 

This shift has already begun, with many organisations leveraging AI to streamline their operations and leverage on their finance professionals as strategic advisors who can focus on higher-level tasks, such as analysing financial trends and advising on business strategy.

The practical applications of GenAI are already being realised in various sectors including end-to-end operations.

One of our clients was a global insurance company that used generative AI to revamp their call centre operations. 

The AI handled complex tasks such as three-way matching of accounts payable, cash, and goods received, performed rapid semantic searches, summarised key contents from contracts, invoices, and customer data, and identified anomalies. This streamlined operations and significantly improved customer satisfaction.

Future Prospects and Challenges

GenAI offers significant advantages by automating repetitive tasks, reducing human errors in data processing and reporting, and handling vast amounts of data efficiently. 

However, it also presents challenges, including security risks, potential bias and inaccuracies, and over-reliance on AI.

Robust security measures and protocols are essential to mitigate these risks. Regular audits of AI models can help ensure secure data usage and reliable outputs.

One promising approach to addressing these challenges is Retrieval-Augmented Generation (RAG). RAG ensures that AI-generated content cites reliable sources, allowing users to verify information accuracy. 

For example, a financial services firm using RAG to generate quarterly reports can ensure that every data point and statement is backed by verified financial databases and market analyses.

This not only enhances the credibility of the report but also allows auditors and stakeholders to trace back the information to its original source.

A Cultural Shift Towards AI Adoption

The successful integration of GenAI into business processes requires a cultural shift within organisations.

Leadership must champion AI initiatives and foster an environment that embraces experimentation and agile development. 

By conducting proof-of-concept projects and iterating quickly, businesses can see tangible results and build confidence in AI technologies.

The adoption of AI can be likened to the rapid shift from basic mobile phones to smartphones, revolutionising communication and productivity. 

In finance, initial applications in data summarisation and operational automation will progress to more sophisticated tasks like strategic decision-making and business forecasting.

GenAI is poised to be a game-changer in business and finance. Its ability to create new content and insights can streamline operations, enhance decision-making, and drive innovation. 

While challenges remain, with careful implementation and a supportive organisational culture, the future of GenAI looks incredibly promising.

As businesses continue to explore and harness its potential, GenAI will undoubtedly become an integral part of the corporate toolkit, shaping the future of work and finance. - Aug 14, 2024

Karen Ko

Managing Director of APAC Financial Services Transformation

Kuala Lumpur 

https://focusmalaysia.my/the-transformative-potential-of-generative-ai-in-business-and-finance/