How AI can fulfil Asia Pacific SMB funding needs
In today's fast-paced digital economy, small and medium-sized businesses (SMBs) face the pressing challenge of securing fast and reliable access to working capital. This need is driven by the constant evolution of business and consumer demands, making it essential for SMBs to stay agile and responsive.
Artificial intelligence (AI) and machine learning (ML) present transformative opportunities for these businesses by providing predictive insights that empower them to anticipate funding needs before they arise. Through real-time data analytics, these technologies enable both lenders and SMBs to make informed financial decisions quickly, thereby closing the funding gap that often hinders growth.
Anticipating funding requirements
One of the most significant advantages of AI is its ability to help SMBs anticipate their funding requirements. Early warning systems powered by AI models can detect patterns indicative of potential financial distress. For instance, initiatives like NovA!, part of Singapore’s National Artificial Intelligence Programme in Finance, have the potential to help financial institutions harness AI to generate insights on financial risk.¹ By leveraging vast datasets, including credit histories, transaction patterns, and market trends, these systems can pinpoint early signs of trouble. This capability can also be eventually extended to SMBs, helping them forecast potential crises and secure funding to mitigate risks. For example, if a system detects declining sales trends, a business can initiate cost-cutting measures or seek additional financing to stabilise operations.
In addition to early warning systems, seasonal demand forecasting is another critical area where AI can assist SMBs. Machine learning algorithms excel at analysing historical data to predict seasonal fluctuations in cash flow and funding needs. Retail businesses, for example, might experience increased sales during the holiday season. Understanding this pattern allows them to prepare adequately by securing additional inventory or financing.
Accelerate the lending process
AI also accelerates the lending process through capabilities like automated loan underwriting. Traditional methods often involve lengthy assessments that can delay access to capital, leaving SMBs in a precarious position. With ML algorithms, lenders can significantly reduce the time it takes to evaluate a borrower’s risk profile. These algorithms analyse a multitude of factors—including financial history, credit scores, and business performance metrics—resulting in a more comprehensive understanding of a borrower’s creditworthiness. This shift from traditional, manual evaluations to automated processes reduces human error and enhances decision-making speed.
Moreover, dynamic lending offers generated by ML algorithms create personalised lending solutions tailored to each SMB's unique financial situation in real time. This personalisation is crucial as it allows lenders to consider the specific circumstances of each business rather than relying solely on one-size-fits-all criteria. For example, AI systems can automate the collection and analysis of financial data, such as sales history and inventory levels, allowing a retail SMB owner to secure a loan to purchase additional stock and manage cash flow ahead of a busy holiday season.
Enhancing financial management
Intelligent financial planning tools powered by AI can also assist businesses in creating more robust financial plans by simulating various scenarios and recommending optimal strategies tailored to their specific business models and market conditions. By analysing historical data, AI can forecast future trends, helping SMBs anticipate market shifts and prepare accordingly. With ML algorithms, financial institutions and fintechs can analyse a wide range of data points, including transaction history and spending behaviour, to provide financial insights and recommendations for SMBs.
AI automation not only reduces the administrative workload but also minimises human error associated with manual data entry. AI-driven tools, combined with technologies like optical character recognition (OCR), can scan receipts and invoices, automatically populating expense report fields. Platforms like Xero offer expense management solutions that integrate OCR technology to streamline the process of capturing expenses.
AI solutions are seeing a rising demand from SMBs. By 2028, half of Asia Pacific SMBs will use services from vendors that leverage Generative AI to capitalise on the benefits of the technology more easily.² To serve the increasing demand for AI, companies like Visa are already taking steps to foster collaboration, investing USD100 million to support companies involved in exploring Generative AI for payments and commerce.³
The financial ecosystem must take the lead to help more reap the economic benefits of AI. With SMBs at the heart of Asia Pacific’s economy, more SMBs using AI to accelerate lending, access sources of working capital, and streamline business processes can spell continued economic development for the region.
¹ Monetary Authority of Singapore, AI Utility NovA! to Unlock Opportunities for Green Financing and Combat Greenwashing, 2022.
³ Visa, Enabling Small and Medium-Sized Businesses (SMBs) with Access to Funding and Financial Education, 2024.