Fintech Lending Landscape Amidst the Upcoming Winter
Fintech Lending Landscape Amidst the Upcoming Winter
Applying for a loan can be tempting. But at the same time, it also can be a trap for some people.
This has happened before to Riri, a 31 Finance Manager in one of Indonesian big companies.
As a manager, the amount of Riri's salary is certainly not small. She can fulfil her daily needs, save her funds in the bank, and even give some to charity. Until one day, her husband intended to borrow Rp. 200 million from her to develop another business out of the city. Not a small amount of money, yet on behalf of husband and wife, Riri gave it to him and trusted his intention.
A month later, Riri is struggling to pay back the balance, along with mounting interest. She felt terrorized to hear her phone ringing for more than 50 times a day from the debt collectors. Moreover, she was ashamed after knowing some debt collectors called and texted her family and colleagues to ask her to make a repayment.
I was scared. They called me everyday and yelled at me to make a repayment as soon as possible. They even shared my pictures to my contact list which I don't know how they got those, Riri continuously said, remembering the intense experience she got, I feel I was trapped twice. First from my husband, and second from the loan.
The narrative told in these kinds of stories often positions the borrowers as the sole victim. This couldn't further than the truth. Truth is, both lenders and borrowers suffer in situation like this. While on one hand the borrowers is stressed out due to being constantly chased by collection staff, lenders also suffers from the spiking non-performing loans ratio. Making sure that loans and pay later offers are being channeled to credit-worthy borrowers is a concern for all parties involved. For a financial institution, it's a huge dilemma as on one hand, properly conducting credit assessment is an almost impossible task but on the other hand, the demand for a quicker loan approval and pleasant customer experience keeps on rising. Additionally, increasing number of competition in the sector requires them to act fast and decisive to ensure that they capture enough market share to stay afloat. Figure 1: Google Search for 'Pinjaman Online' through the years
The demand for online lending seems to have correlated with COVID-19 outbreaks. Searches for "pinjaman online" starts dropping starting from March 2020, when the first COVID-19 case in Indonesia was announced. It continues to drop as more lockdown regulations was rolled out in the subsequent months.
As the first wave of COVID-19 starts to fade at the beginning of 2021, searches pick back up. However, when the Delta variant outbreaks started at around May 2021, demand starts cooling down. It has reached its peak again by October 2021 but subsequently drop when the third wave started at the beginning of 2022.
As the last COVID-19 wave has faded, plus the increased vaccination rate among Indonesian population, it is expected that the economic disruption from the pandemic will subside in the upcoming months, leading to a higher demand for "pinjaman online".
Increased Competition in Fintech Lending To assess the competitive landscape fairly, the pay later, consumptive cash loans and productive loans categories are separated.
Pay Later Competitive Landscape
Based on Google Trend's data over the past five years, Akulaku, Home Credit and Kredivo remains the top three most searched pay later brands. However, since its release in 2019, Shopee Paylater has quickly risen to challenge the top brands, overtaking Home Credit to the top 3 spot in recent months.
Shopee Paylater rise has been similar to its e-Wallet counterpart, which was launched long after both its biggest competitors, GoPay and Ovo, but has been able to challenge the top spot.
Consumptive Lending Competitive Landscape
Kredit Pintar has dominated the consumptive loan P2P lending category by a large margin based on Google Search Trend. The competition for spots below Kredit Pintar has been competitive over the past few years. Julo's rise in recent months should be noted as it has managed to take over the top spot for quite some time.
Productive Lending Competitive Landscape Productive loans Google Search spiked in 2019 led by Koinworks and Modalku, which has been the top brands over the last five years. However, Amartha has actually overtaken both brands in 2020, and has maintained its position ever since.
Increasing Non-Performing Loans in Fintech During the peak of COVID-19 and its related crisis, non-performing loan (TWP90) had peaked at around 8.8% during August 2020. During this time, the amount of loan disbursement has been slowing down both due to lower demand as well as fintech lending implementing stricter assessment.
Now, since the demand has been ramping up as COVID-19 has subsided, it has become of utmost important to look at the risk side to prevent another catastrophe.
According Indonesia's Financial Services Authority (OJK), the non-performing loan ratio has dropped to below 2% at the beginning of 2021. However, as seen on the chart above, the number has climbed back up to >2.5% in January 2022. If not careful, we may see the number rise to a figure close to those of 2020.
Mitigating Complacencies in Fintech Lending Given the high demand plus the needs to be competitive in the current market, it is understandable that financial institutions are conducting efforts to minimize friction in their loan application processes. However, this should not come at the expense of risk assessment.
We conducted a research to understand the processes of applying for a loan at several fintech lending platforms.
All fintech lending institutions requires eKYC verification as it was mandated by the regulators. However, the additional steps differ. Only 70% of the fintech lending platforms requires the applicants to submit a selfie, while only 40% requires a liveness detection test to ensure the authenticity of the application.
Another interesting finding was that almost all, 90% of the platforms we tested requires applicants to submit their employment information.
All platforms requires applicants to provide their income information. However, during the data input, two different methods are used. 80% of the platforms simply requires the applicants to input the data manually by filling in fields and uploading their pay slip. 20% of the platforms asked their applicants to connect an account to automatically retrieve applicant's income information.
While the applicants are asked to fill in the income information, transaction information becomes unnecessary data for half of fintech apps that we surveyed. This thereby fastens the verification processes and moves the applicants to easily apply for a loan afterward.
Based on the research we concluded that most fintech lending platform optimizes for easier and quicker customer experience, skipping some necessary data collection and verification processes. The limited amount of data collected in fintech lending platforms is not sufficient to cover the 5C of credit.
A bit of a refresher, the five C's of credit is a system used by lenders to gauge the creditworthiness of potential borrowers. The system weighs five characteristics of the borrower and conditions of the loan, attempting to estimate the chance of default and, consequently, the risk of a financial loss for the lender.
The five C's of credit are character, capacity, capital, collateral, and conditions.
Assessing 5Cs of Credit with Brick Understanding the necessities to gather enough data to truly perform a credit assessment, Brick has built various data connection to allow potential borrowers to share their financial account data easily to lender's app.
Character The most common method to measure character among Indonesian financial institution is to collect data from SLIK or BI-Checking. However, Brick can provide an alternative to this.
Brick has built a connection through a partnership with Visa, the world leader in digital payments, to provide financial institutions with access to aggregated card transaction data made using Visa debit or credit card, of course, through user consent. This additional data point can assess whether a borrower settle their credit card payments on time which paint a picture about their character.
In addition to this, Brick has also build the connection to access pay later providers data which can also assess whether a borrower is taking loan at these platform and if they always make repayment on time.
Capacity Brick allow end-users to share their income data straight from the source, removing potential document forgeries in the process.
On the other hand, powered by our machine learning transaction categorization, we can identify potential borrowers liabilities from their financial account transaction data.
With these two data sources, Brick's client can calculate potential borrowers debt-to-income ratio.
Capital Brick allow end-users to connect with various financial accounts and retrieve their account balance data. Accumulated account balance data can help financial institution understand one's total liquid assets to gauge borrower's ability to repay the loans in case of unforeseen circumstances or setbacks.
Additionally, Brick also helps clients retrieve data from investment and wealth management platforms. The data set can help financial institutions understand the borrower's investment portfolio's worth. ***
