Large banks helping small firms access loans

Big data has become key for the expanded reach of large banks to micro and small-scale enterprises that have never received bank loans before as the Chinese government urges banks to increase lending to small businesses－especially first-time borrowers－amid the novel coronavirus pandemic.

Online small loan products backed by big data analytics are important channels for China Construction Bank Corp, a major State-owned commercial lender, to further expand its customer base to micro and small businesses that have never received bank loans.

The bank's branch in Zhejiang, a province where micro and small enterprises flourish, signed cooperation agreements with dozens of government departments, leading companies and credible third-party platforms. They became sources of data based on which the bank developed a "quick loan" product series targeting micro and small-scale businesses.

For instance, the State Taxation Administration gave CCB access to companies' tax payment data. The bank designed a loan product based on the tax payment data and the fundamental state of each small business.

If a business owner has good credit history and pays taxes dutifully and honestly, he or she can use CCB's small business loan application software to assess how large a credit line the bank might extend to the company and later the owner can apply for a collateral-free bank loan.

The bank has developed a loan product series for small businesses through cooperation with external institutions including State Grid Corporation of China.

By digging into data provided by external institutions and its own data of transactions and settlement of enterprises in the upstream and downstream supply chain, the bank uses algorithms to decide the maximum amount of credit it extends to a small business.

At the end of May, the outstanding balance of CCB's "quick loan" product series amounted to 38.7 billion yuan ($5.5 billion) in Zhejiang province. The nonperforming loan ratio of this product series was 0.52 percent. Among the total, the balance of collateral-free loans was 8.74 billion yuan, said Yang Xizhou, chief manager of the inclusive finance department of CCB's Zhejiang branch.

"Our collateral-free loan products are very attractive to micro and small-scale enterprises. They have become an important means for us to broaden our range of customers to small businesses that have never obtained loans from banks before. Micro and small-scale businesses can apply for loans at our bank without collateral using their data collected by the government and credible third-party institutions partnering with us," Yang said.

From the beginning of this year to the end of May, 881 micro and small business clients received bank loans for the first time at CCB's Zhejiang branch. The average outstanding balance of their loans was 641,800 yuan per borrower.

The bank stepped up risk management of collateral-free small business loans after the pandemic broke out, requiring staff to pay more return visits to clients, strengthen post-loan management and pay close attention to client data cross-checking. If significant changes occur in client data, the bank will provide early warnings to its branches and subbranches.

Compared with some banks that are more willing to lend to well-established small businesses, CCB is paying more attention to those micro and small businesses that have more difficulties obtaining financial support, Yang said.

"We are inclined to help those companies that have trouble obtaining credit lines from other banks," he said.

Agricultural Bank of China Ltd, another large State-owned commercial lender, has also been using multidimensional data through partnerships with many institutions to know clients better via data cross-checking. Two years ago, however, the bank still used a traditional model of lending by conducting assessments based on financial statements and collateral offered by clients.

ABC's Zhejiang branch is now profiling clients mainly based on their existing data at the bank such as account openings, borrowings and settlements, business conditions and data from various government departments. It is also cooperating with e-commerce companies having a specific area of focus and with online government procurement platforms.

"The effects of big data on micro and small-scale enterprises at our bank, whether or not they have borrowed from banks before, are significant. Both the number of our clients with a total credit line up to 10 million yuan per borrower and the outstanding balance of their loans have doubled every year since 2018. More than 90 percent of the growth was contributed by big databased online products," said Qian Kai, manager of the inclusive finance department at ABC's Zhejiang branch.

"Without these products, we may not be able to properly assess small business clients, especially first-time borrowers, or grant loans to them. Having been in business for only a short time, they are still vulnerable and have no assets as collateral, which means the traditional way of credit evaluation and approval is unavailable to them. But now we have more data to know these clients better. This has fundamentally changed our thinking and methods of providing financial services to micro and small-scale enterprises," he said.

The online lending products of ABC's Zhejiang branch mainly target small businesses with a total credit line up to 10 million yuan per borrower. By the end of May, its average outstanding balance of loans to this kind of business was 2.13 million yuan per borrower, among which the average outstanding balance of collateral-free loans was 400,000 yuan per borrower. Its nonperforming loan ratio of online lending to micro and small enterprises is very low, two years after the branch launched this type of product in May 2018.

Although most parts of the online lending process including loan applications, credit approvals and loan repayments are completed online, client managers still need to conduct on-site investigations to find out whether a client is really producing goods or providing services at the address of his or her registered company. On-site investigations will also help client managers know business owners better, as it is hard to assess their characters and capabilities simply via big data, Qian said.

The bank will build client profiles for those who have applied for online loan products and tell them how much they can borrow without offering collateral, how much they can borrow with collateral and how much the interest rate is in each case. The clients are free to make their own choices according to their actual needs.

"The government is willing to partner with us on data sharing. It's not just because we boosted the local economy by supporting registered companies that pay taxes, but also because we offer loans to different companies at different prices based on their credibility and business conditions," Qian said.

"Those companies that do business and pay taxes honestly will receive collateral-free loans or receive loans at lower interest rates. Those having records of owing taxes or tax evasion, however, will be granted lower credit lines and obtain loans at higher rates. This will incentivize small businesses to clean up their act. In this way, we will develop benign interactions among the government, small businesses and our bank."

China's banking and insurance regulator in Zhejiang province has promoted the government's sharing of data on small businesses with banks and insurers.

"Based on our past experience, the main problem of micro finance is information asymmetry. Although some micro and small business owners have beautiful dreams and qualities of good entrepreneurs, it still takes time for banks to get to know them," said Bao Zuming, head of the China Banking and Insurance Regulatory Commission's Zhejiang office.

To solve this problem, the office launched an online provincial-level platform of comprehensive financial services on Nov 13. The platform gathered a large amount of data from 54 provincial government departments, which accounted for 70 percent of the information on a business that loan officers need to know when they conduct due diligence before making a lending decision.