Lending is easy. Just walk along Ayala Ave. on a sunny Sunday afternoon and you will find thousands of people who will gladly accept your money. Getting paid back is when it gets tougher. However, new technologies are enabling better methods of predicting who will a good borrower. I am arguing that using innovative credit scoring and alternative data is fundamental for financial inclusion in the Philippines.
While small and medium enterprises (SMEs) constitute 99.6% of all businesses in the Philippines, only 13% have access to legitimate financing. Lending is important as this enables businesses to expand according to market demand rather than according to their current size. Meeting demand is what creates economic growth while the opposite leads to high prices and low consumption. Hence, financial inclusion is also a key challenge for the Philippine economy as a whole.
The current problem is that when uncertainty is high and information scarce, banks will choose to limit services to a select few and the rationale for choosing is surprisingly blunt. The prevailing application process to receive a loan from a bank is a tornado of identifications, verifications, certificates and permits, all by different authorities. Additionally, an inherent catch-22 exists in this system: businesses with no record of borrowing have no credit history and therefore limited opportunity to get a loan in the first place.
For banks, this application process is not only labor-intense and requires vast branch networks, it is incredibly blunt in terms of actually understanding the borrower’s business. Unfortunately, the currently dominant big banks shape the entire market when they use these traditional methods. The process leads to uninformed decisions and excludes businesses with high potential, which is detrimental to the Filipino business environment at large.
Financial institutions need to rethink how they assess businesses. Only one thing should matter if I am going to trust you with my money: the prospect of you paying me back. To guess if you will pay me back, I want to know just four things: your ability to pay, the stability of your business, your skill as a business owner and your willingness to pay.
Given rapidly-growing internet penetration, the increased processing power of modern computers and the collection of large sets of data across industries, there are definitely new ways to make better guesses.
It all comes down to relevant and reliable information. If you show me your Lazada sales, how people interact with your Facebook page and how you fill out an online application, I will be in a better position to know if you will pay me back than if we just had a meeting at a bank. Alternative data sources such as social media, utilities, telecommunication providers, the government, retail/wholesale, logistics history and psychometric testing enable predictive modeling to make superior guesses. Consequently, we will be able to give a credit-risk score to businesses who were previously rejected by banks.
Image an online fashion retailer with a high volume of incoming orders. This is an opportunity to grow the business but to fulfill the orders the owner needs to buy more stock and thus requires cash. Even though she doesn’t meet some of the bank’s many minimum requirements, everything else points to her ability to fulfill the orders and grow her business. Using alternative data and innovative credit scoring, she would be deemed creditworthy and subsequently receive a loan.
This is one of the many types of clients First Circle has been able to help. Through a digital platform and with innovative credit scoring, we are able to provide previously unbanked small businesses with access to finance. As our company grows, so does our understanding of local businesses as well as our ability to give them a credit risk score, allowing more and more Filipino businesses to grow with us.
Emil Ahlanzberg is a graduate of the Stockholm School of Economics in Sweden. He is currently working as a business analyst at First Circle, mainly focusing on risk, data and new products.