China Rapid Finance (CRF) introduced a strategy to cover an untapped market on Wednesday, calling its target demographic “EMMA”, or Emerging Middle-Class Mobile Active, a potential market of 500 million.
CRF’s big data analysis found that 530 million out of the 1.4 billion people in China do not have credit history backups at the People’s Bank of China, meaning they may find it hard to get a loan on a rainy day. And among these 530 million people, nearly 500 million are EMMA – that’s 1.5 times the population of the United States!
So what exactly is EMMA? CRF gave a portrait of this group: they are obsessed with the internet and smartphones, they love online shopping, they don’t have much working experience, they are from second- or third-tier cities, they don’t own a house or a car, and most importantly, they have no credit history.
CRF’s CSO Joseph Wang mentioned that two major factors concerning lending risk control is the borrower’s level of education and profession. According to CRF, 51% of their customers have a junior college degree or above, whereas the average percentage for China’s urban population is 20%. Thus, the risk that the borrower doesn’t repay the loan are relatively low. CRF also said that 73% of their customers are self-employed or working at small private enterprises, and 84% have a monthly income above RMB three thousand (USD 463).
An interesting phenomenon is that CRF got more loan applications before Valentine’s Day, indicating that people may take out loans to buy gifts, and repaying the small amount of borrowed money is not a problem.
“China has a huge untapped market,” said Zane Wang, founder and CEO of CRF. “The bank does not deal with it because it costs too much to collect data on credit.”
Another problem is that getting loans from banks and other lenders is quite pricey for borrowers, who only turn to loans when they’re at the end of their rope, which means bad loans are more likely to happen. Therefore, CRF starts by offering products for EMMA clients that feature smaller loan sizes to help them build a credit history from scratch.
Then how does it decide who can take out a loan? Though many companies in China have databases containing over 100 million people, the data is not useful if it’s not being shared. CRF hired its chief scientist from the Silicon Valley to introduce its Predictive Selection Technology (PST), which finds potential borrowers through big data analysis, and its Automated Decisioning Technology (ADT), which helps decide whether to gradually grant a borrower higher credit scores.
Through machine learning, the technology reduces the cost of credit investigation for CRF. And by using its PST and ADT technology, CRF claims it can evaluate a borrower’s character, capacity and stability, which are the three major risk factors.
Zane Wang said that by offering a fast, affordable, and convenient way to borrow small amounts of money, the 500 million EMMAs can start building their credit history and may even be able to meet their lifetime credit needs with CRF.
The company processed five million loans this January, and was a founding member of the National Internet Finance Association of China (NIFA), established in Shanghai last week.
(Top photo from CRF)
Correction was made that CRF offers credit service instead of loans.