The credit industry in the United States has been exploring the issue of financial inclusion, including how to provide financial services to people with limited credit records or no credit records. For immigrants and ethnic minorities, the lack of credit records is a major obstacle to their access to financial services.
There are currently 42 million immigrants and 3 million new immigrants each year with a growth rate of 13% a year in the U.S., and the average number of financial products that they tend to use within two years is five. Many of these immigrants have obtained H1B visas and have an average wage of US$78,000 dollars, which is higher than U.S. citizens’ average wage of 50,000 dollars. These customers are of high quality, but they cannot enjoy reasonable financial services because of the difficulty of sharing credit information across borders.
Nova Credit is committed to providing credit reporting services for these immigrants. Through the establishment of a global credit recording system, immigrants can obtain financial services in new countries using the credit history in former countries.
Nova Credit was founded in 2015 and is committed to becoming a world-class cross-border credit report agent. Nova was founded by a group of American immigrants. Founders, Loek Janssen, Nicky Goulimis, and Misha Esipov are Stanford graduates. Nova Credit’s business model stems from a research project at the Stanford Business School which was successfully incubated in the Bay Area. The platform hopes to provide credit to outsiders who have no credit history in the United States and to give them the opportunity to use financial services such as loans. In addition, the company has responded to the White House’s proposal to provide more inclusive financial services for refugees around the world.
In August 2016, Nova Credit received 120,000 dollars in seed financing from Y Combinator, and in September of the same year, it received 3.3 million dollars in seed financing from another organization and convertible bond financing from Pear Launchpad.
Nova Credit plans to establish a global credit ecosystem. The main target population is immigrants who have recently come to the United States. Their original country credit is their passport.
The platform mainly provides the borrower's credit report information, including: credit history, account balance, payment history, credit inquiry records and credit scores. From the credit report office, the user can obtain the credit score of the client and compare it with the credit score of the United States. The data comes from the foreign credit bureau. Currently, Nova Credit includes credit report information from Mexico and Canada in the America’s, from the United Kingdom in Europe, and from India in Asia.
Institutional users can use an API call to the relevant user's credit report after landing on Nova's system. Nova applies to the local credit information company in the corresponding country for the original data. In accordance with local standards and compliance requirements, Nova then translates and processes the corresponding credit information into an English-language credit report.
The platform has partnerships with local credit bureaus in Mexico, India, Canada, the United Kingdom, Australia, South Korea, the Philippines, Brazil and Germany. The earning method is the same as that of a credit bureau, and the person who uses the report is charged.
In the business model of the credit industry chain, Nova has positioned itself as a credit bureau of the B2B2C2B2B model, linking one end to local institution and the other end to local lending institution in the United States, and then docking the borrower, that is, the credit information of the borrower. Through this type of intermediary, we can build a global credit docking platform. This model is different from the traditional B2B2B, which is the mode of the credit bureau, the distributor, the small-sized lending institution, and the B2B2C, the credit bureau, the credit management service portal, and the C-end user's intermediary model.
The core strength of Nova Credit embodied in its data processing capabilities. It uses a specific data standard to convert the credit history of the original country into a model for the needs of local institutions, so that users' data can be comparable and referable. The platform also need to do this in accordance with internationally applicable laws and adjust the reporting under a cross-border regulatory framework. Data collection, storage, and use are performed strictly in accordance with compliance needs. For some non-compliant data from abroad, Nova will use alternative methods to solve it. At the same time, if the borrower has a negative record in the new country's credit reporting system, Nova will exchange this credit information with the original country of immigration.
Below is our interview with Misha Esipov, Co-Founder and CEO of Nova Credit:
What do many people in China do without a credit record, such as students?
Some graduate students do not have a credit history, but they have some accounts on internet platforms, such as Alibaba. They also have resumes and scores such as GMAT scores. We think that these can also approximate their credit status.
Do you need to buy these data?
Yes, everyone gives permission to buy, we charge from the user.
What if the top three U.S. credit bureaus landing in these countries?
We have a cooperative relationship with them, but the difference is that they can only provide partial solutions. They only have institutions in some countries and we cover more.
In fact, the cost of collecting and transmitting information is high? Is your role like an aggregator?
We provide standards to change and report, and we design how to read and compare user’s information.
How do you get the data?
Communication, persuading them to sell data, the difficulty of our business model is regulation, and how to deliver the value of this data to lending institutions.
Do you have a credit score?
We built a Nova Score by ourselves, which is the same as FICO's score range. We created the same standard. In fact, many lending institutions do not like FICO scores. They have developed their own algorithms. One you give them the data they can calculate their own scores.