Eelee Koay Blog Post - 11th Feburary 2019
Reduce Risk

Reduce Risk and Reap Rewards of SME Financing through Digitised Decisioning.

Opportunity and risk. They often come together, and this can be seen in the rising force of the Southeast Asian economy. With a booming SME market, growing entrepreneurship and supportive government policies, this has also created new opportunities for financing and lending in Asia. According to ASEAN.org, SMEs make up between 88.8% and 99.9% of total establishments across Southeast Asian economies which means greater need for business financing. On the one hand it’s provided the basis for greater SME financing flexibility and the increase in P2P lending. However rapid growth in opportunities can also lead to greater risks if they are not managed with foresight. Reports of high levels of non-performing loans in the SME sector in Malaysia is just an example of the pitfalls of rushing forward without putting in place a solid and sustainable assessment process.

Banks aside, there are substantial numbers of financing companies in Southeast Asia particularly that continue to provide financing on gut instinct, business relationships and at best internal evaluation methodologies that are desperately in need of review. While any combination of these strategies have undoubtedly lent success to lenders catering to different segments of the SME market, they become increasingly difficult to monitor and are in fact exposing organisations to higher levels of risk as the focus turns towards revenue generation and obtaining a bigger slice of the SME pie.

The risk of exposing one’s business to the dreaded outcome of ‘non-performing loans’ can be tackled by addressing it head on at the very beginning of business engagements with SME’s. Credit lenders and businesses alike should be taking full advantage of the technological advances in Financial Solutions and the enhanced analytics of credit rating through agencies such as CTOS in Malaysia, which have become more accessible and affordable.

Instead of relying on pure instinct of a select few decision-makers in the organisation or reacting six months too late to risk factors in the market, employing a decisioning strategy based on expert analysis and automation will reduce the exposure to risks very early on in the business relationship and provide a stronger basis upon which to negotiate more favourable terms according to the changing economic climate. Inconsistent decision-making on credit provision in addition to high risks, also makes any manner of analysis and long-term strategic planning a challenge due to the lack of insight into trends and difficulty in identifying benchmarks of past success.

For many P2P lenders and smaller financing institutions, the thought of embarking on the complex mission of developing an internal scoring methodology can seem daunting. Understandably, the cost of setting up and maintaining a team of data experts is hard to justify for non-banks. Which is why they should be leveraging on the expertise of credit rating agencies whose core function is to continuously crunch data and formulate credit ratings based on localised trends of those markets. Credit ratings provide the foundation upon which lenders can build on to create decisioning rules specific to their needs and risk appetite, without the cost of reinventing the wheel.

Lenders are also fortunate now in that Fintech is becoming increasingly competitive, and therefore have the upper hand as the consumers as new technologies continue to emerge, pushing software costs down and making solutions more affordable across the credit management lifecycle. While before most businesses relied on disparate systems, with limited visibility to cohesive data and time-consuming cross-referencing of credit reports, now Origination and Decisioning solutions are agile and easy to integrate to multiple data sources and solutions within the overall systems environment.

By employing a decision-making strategy based on data and consistent, business-driven operating procedures, credit providers will reduce their exposure to risk without compromising on revenue. Decisioning solutions which tap into the wealth of data (otherwise unavailable to individual organisations) from credit rating agencies not only facilitates better decision-making, but reduces the significant cost of resources conventionally allocated to the tedious study of each individual credit application when they could be easily approved or rejected based on pre-defined, fundamental parameters.

The greater adoption of automation in decisioning and usage of data across the lending ecosystem in time also supports increased preparedness in the SME’s themselves for ongoing financing needs. By creating an environment in which decisions can be made subjectively and rapidly, budding enterprises are in a better position to forward plan, adapt to business changes and work towards greater credit eligibility. The benefit to the market as a whole is greater transparency and trust, as SME’s are also more likely to engage with credit providers that are not potentially operating on bias.

All round, nipping potential risks in the bud is the sensible way to go, and there’s no better time to start now with the SME market ripe for the picking .


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About the authors

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Richard is a seasoned credit expert, having spent his entire career working within the bureau and data world. He is passionate about helping companies find the best use of technology and data to improve their performance.
Richard Brooks
Product Expert, Australia & New Zealand
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Eelee is a software professional with experience ranging from enterprise software implementations to SME solutions. Eelee is an ardent proponent of marrying new technologies and process to customer problems for successful outcomes.
Eelee Koay
Product Expert, South East Asia