CEO PT. CRIF Lembaga Informasi Keuangan (CLIK) Leonardo Lapalorcia said that credit scoring services provided by credit bureaus offer many benefits. “The OJK database for credit history is very good, but it’s designed for supervision, not for running business”.

The presence of digital financial services such as peer-to-peer (P2P) lending and digital wallets is a blessing for credit scoring providers. With the emergence of these digital financial services, PT. CRIF Lembaga Informasi Keuangan, a credit bureau, has also seen significant growth.

Since 2010, CRIF (as the company affiliate of PT. CLIK) has operated in Indonesia. At first, they were a company that provided a tool for a credit card rating system and a credit risk analysis. In 2019, PT. CLICK began working as a credit bureau after getting the license from OJK. Currently, they have more than 96 million unique individuals and businesses in their database.

Despite this, there are still many obstacles to overcome and room for improvement. The following is a complete interview of Katadata Insight Center with Chief Executive Officer of CLIK, Leonardo Lapalorcia.

What are the main reasons for establishing a credit bureau? How has it grown so far?

It has grown very little in my view, and that’s a big problem.
OJK has a system which is very good as a tool for supervision, the credit history database called Sistem Layanan Informasi Keuangan (SLIK). The SLIK OJK is available and free for the banks. There’s a lot of people employed fulfilling the data gap. Therefore, the banks rarely use credit bureau services which offer credit scoring.

Source: Katadata Insight Center

But the SLIK database is designed for supervision, not as a tool for supporting business. It doesn’t have the features that are required if a bank wants to obtain the level of efficiency that allows them to sustainably run a consumer lending business.

In SLIK OJK, there is no Service Level Agreement (SLA). The response time can be 10 minutes. It can even be 40 minutes or three hours, and the service could be down, but it’s understandable since it’s public service. There is no escalation procedure. The result can be multiple identities if there’s a typo or there are a lot of similar name results, then need to stop the process, analyze it and eventually go to a manual underwriting process.
On the other hand, Credit Bureau offers easily accessible services available through state-of-the-art APIs with predictive analytics built on top. The Credit Bureau database covers 95% of the Indonesia population that is eligible for lending.

Currently, fintech companies do not have access to SLIK. Therefore, they use credit bureau services more than banks. But if you see the lending market, the total lending of the banking industry is down, inversely proportional to the trend of fintech, especially P2P. Currently, the trend being carried out by banks has shifted, such as channeling through institutions or other collaboration partners such as fintech P2P lending. However, its growth tends to be slower than other main bank services. Meanwhile, P2P and other forms of financing have rapidly increased.
We are very happy and rewarded with this type of progression. We have been in the market as a credit bureau effectively since September 2019. We have a very significant growth on our customer base and we still have a lot of runway for future growth and expansion.

Although credit scoring offers a lot of benefits, banks are more hesitant to use third-party services for credit scoring. What do you think of what? Which industry is the most interested in using credit scoring services?

Definitely our strongest clients today are the fintechs or the P2P lending. Then, the digital banks have high potential, since they really fight for customer experience. They know that if they don’t deliver a flawless consumer experience, they will lose their business. But they’re still very careful as bankers. They do a lot of testing, a lot of development and they do a big procurement activity in a big transformation project. But they really want credit scoring products.
Multifinance is also interesting. Multifinance companies do consumer lending as their primary business, different from traditional banks who mainly make money from fee-based businesses or corporate lending.
Traditional banks are challenging; their dependance on the consumer lending business is not as dominant as it is for the multi finance company. They also have a competitive advantage that is difficult to beat. For example, I remember going island hopping in East Maluku and the only thing I could find was the post office and a BRI branch. They still rely a lot on physical presence and face to face relationship with the client.

What is your current data coverage for credit history data?

Our database has more than 96 million unique individuals and businesses. It’s close to the number of the total eligible population eligible for loan. Based on the 2020 data, the population of Indonesia is 278 million people. Then, we filter only the people between 16 and 65 years of age, people of legal age, so to speak or eligible for lending facility or only 134 million. Now there are 7 million unemployed people. And there’s about 30 million people that live below the poverty line with less than $100 per month.
If we exclude all those who are ineligible, the total eligible population for lending is about 98 million as of 2020. Our coverage today is more than 96 million unique individuals, about 95% of that total number. In addition, there is data on 29 million business subjects.

Based on various data sources, which data source that you see as the most accurate in predicting credit default?

Approximately 50% of the weight is on credit performance, the level of discipline of the debtor in repaying the loan. Other variables are the type of credit facility used, length of credit history, and social demographic attributes. These variables also play an important role in credit scoring and predicting default.

What do you think about alternative credit scoring that utilizes alternative data for credit scoring?

I think there is a misconception from many of the operators in the lending industry when it comes to predicting the credit default. They start looking for alternative data, but they haven’t yet reached an optimal balance or an optimal level of understanding of the credit data that is available and how to leverage their credit data to fuel the lending processes. They immediately jump to the alternative data.

Source: Katadata Insight Center

Credit Bureau systems are very highly regulated and they have a very wide coverage. We have strong data quality on almost everybody. The type of data we have is obviously relevant to the credit risk because it’s your loan repayment history. It makes more sense to try and predict the credit risk with credit data as opposed to phone usage or number of contacts in your phone book or the type of applications that you’ve downloaded.

Source: CLIK published at katadata.co.id