PINTEC Academy: How Can Big Data Help Make Unsecured Loans to Small and Micro-sized Enterprises

Author: Sherry Zhang | 2019-04-12

This article by PINTEC Academy will explain how PINTEC’s Small and Micro-sized Enterprise Credit Team (hereinafter referred to as “SME Team”):

  • Help payment companies and e-commerce platforms utilize non-traditional credit data to support their credit decisions on small and micro-sized enterprises (SMEs);
  • Help the above two types of companies solve the “last mile problem” in acquiring customers for SMEs loans.

1. Operating flow is a “rich mine”

For small stores, operating condition is a key factor in determining whether they can obtain unsecured loans.

In the era of mobile payment, major e-commerce platforms and payment companies behind “aggregate payment” gain the most knowledge of the operating condition of small merchants. As small businesses open stores on e-commerce platforms, the platforms will have their transactional data. In terms of offline transactions, small businesses will utilize aggregate payment tools to collect payments made by mobile devices such as Alipay and WeChat Pay. Therefore, the payment companies possess a large amount of offline transaction information.

Traditionally, SMEs’ financial data will be used to assess their creditworthiness. But there exist two problems:

a. Financial data can only reflect the operating condition of the company in an indirect way;

b. There is always a lag between the data disclosure time and the current operating status.

In this case, the real transaction information possessed by e-commerce platforms and payment companies has become the best data source for assessing the credit qualification of SMEs. Jessie Song, head of PINTEC’s Small and Micro-sized Enterprises Credit Business, shared that when providing services for payment companies and e-commerce platforms, her team can obtain more operating information of small businesses from the transaction flow in a more timely way.

 2. Risk management: Focus on identifying two types of risk

Just like in a cooking scene, an experienced cook needs to select the good stuff and discard the bad from a bunch of “raw materials” to present a delicious dish with careful cooking.

To assess the credit qualification of small businesses, getting their income flow(raw materials) is only the first step. It requires professional skillset to deal with the data and turn it to be a specific credit decision.
 The SME team considers that when providing credit loans for small businesses, there are two risks that need to be focused on: fraud risk and operating risk.

Fraud risk means that businesses tend to create inauthentic transaction flows by making payments on their own to obtain a higher credit line.

For example, in the risk management model, if there are frequent large-integer-amount “payments”, it is generally considered that there is a high risk of fraud. Alternatively, a high risk can also be signaled by even small-amount “payments” for exceptional highly-concentrated transactions (for example, 50% of the turnover of business is from one buyer).

Operating risk means that if a business wants to borrow a sum of money when its operation condition deteriorates, the use of funds should be carefully assessed.

To design an effective risk management strategy, relevant industry experience is of vital importance. The reason is that according to the modeling principle, the strategy provider can only optimize the model of the customer base after accumulating enough good and bad samples.

With the familiarity of customer characteristics of a payment company, the risk management advice provider can apply the existing strategies and experience to other payment companies. Although the model needs to be adapted and further adjusted, it will be a higher starting point for the risk management advice provider than its zero-experience counterpart.

3. Measurement of credit line: Use the industry multiple skillfully

The transactional data is also useful in estimating the credit demand of a store. The transaction volume to a great extent determines the maximum funding amount that the business can bear.

When measuring the credit line, the risk management advice provider will consider various factors, including the level of debt, the scale and the stability of a business.

In practice, there is a commonplace problem that sometimes the credit line calculated according to the formula can’t fully meet the funding needs of the business. Generally, when estimating the total turnover of a business, we will use the formula: “Total turnover = Turnover of aggregate payment * Industry multiple”. Typically, the multiple of small businesses will be higher, while that of large-scale businesses is lower.

However, as the proportion of the revenue received via payment tools to the total turnover varies across industries, sometimes it is not easy to determine the industry multiple.
 Therefore, after the product is launched, PINTEC’s SME Team and Risk Management Team need to make a dynamic adjustment to the multiples based on market changes and find the balance point between “a reasonable credit line that the business can bear” and “the optimal performance of assets”.

 4. The “last mile problem” of customer acquisition

Using technical methods to judge credit risk is one thing, and finding small businesses with loaning demand is another. In China’s environment for SMEs loans, the latter may be more difficult to achieve than the former.

“There is a huge difference in the efficiency between different customer acquisition methods: The conversion rate of the most traditional street canvassing method is on the order of 1/1000, while that of the less traditional telemarketing method is on the order of 1/100. Now we can achieve a conversion rate of about 1/10 by embedding the loan function into operating and payment collection tools of small businesses (including aggregate payment products and e-commerce platforms). It proves to be a very efficient and accurate way to reach those SMEs with borrowing needs,” Jessie Song said.

In the past two years, more and more aggregate payment tools (offline scenarios) and e-commerce platforms (online scenarios) start to provide credit services to businesses on their platforms to attract small businesses to join and continue to use their payment products.

PINTEC has served a payment company with a leading market share in the industry. It provides the feedback that the loan function has become one of the highlights the ground promotion team would focus on when introducing the aggregate payment product to small businesses.

 5 . Being moderate is the cornerstone of SMEs loans

Always be noted that there is a cap on the funding needs of SMEs.

The original intention of lending to SMEs is to help address their funding needs to grow their businesses. If the needs can be served by better risk management and credit line forecasting models, payment companies can provide businesses with an appropriate credit line and risk pricing. The credit line will be neither too low nor too high and the interest rate should be within the range that the business can bear.

A benign business model of credit to SMEs is: The loan funds can meet the normal loan demand of a business at a reasonable rate and the business will turn to the payment product or e-commerce platform again for re-lending. In this way, the business’s stickiness to the payment tool and the platform will be enhanced, which is the original intention of the platform to provide the business with loan services.

On the contrary, if a business borrows an inappropriate sum of loan and then never uses the payment tool or platform again, the game is not worth the candle.

6 . Summary

To sum up, we believe that the value of utilizing big data technology to do SMEs loans lies in:

  1. By embedding credit solutions into the operating tools of businesses, customer acquisition can be achieved in a more accurate and efficient way.

  2. Small businesses have unmet credit needs. There is commercial value in the data and traffic of businesses accumulated on the operating tools and platforms. Third-party credit technology service companies can use desensitized data in a compliant and prudent manner to revitalize the value of data and traffic, meet the previously unmet market needs, and make each party of the business chain obtain profits.

This is the rationale for providing credit to SMEs.