5. Results and Analysis
In this section, the research conducts cross-case analysis. By comparing the difference of SME lending in DBS Bank and online lending platform, OnDeck, we could understand the advantages and disadvantages of these two systems.
5.1. Cross Case Analysis
In this section, this research summarized the key differences of DBS local lending program and OnDeck.
Item DBS Local Lending Program OnDeck
Dates required to obtain the approval of a line of credit
In 5 days In few minutes
Data required to provide
11 information input by borrowers but DBS Bank required bankers to assess more data externally.
24 information input by borrowers
The size of a borrower Borrowers range from USD300 thousand to USD16 million.
Median: USD631 thousand
More than 90% of borrowers range from USD162 thousand to USD3.9 million.
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Size of a loan ranges from USD400 thousand to USD1.0 million.
Average size of Short-term loan:
USD23 thousand
Average size of long-term loan:
USD 57 thousand
The source of capital Bank’s balance sheet
9% from OnDeck’s owned capital;
30% from OnDeck’s securitization transaction;
58% from OnDeck’s facilities;
3% from online platform investors.
Average rate of NPL or provision for bad debts
4 According to DBS Bank (Taiwan) annual report of FY2017, DBS Bank (Taiwan) recognized TWD894 million of NPL out of TWD40,782 million of secured loans.
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Facility fee 1%-1.5% of loan amount
The First Loan: 2.5%-4% of loan amount;
The Second Loan: 1.25%-3% of loan amount;
After the Third Loan: 0-3% of loan amount
5.2. Analysis and Findings
Based on this research, OnDeck had a better efficiency in lending decision but the size of borrower and size of a loan were smaller. Compared to DBS Local Lending Program, OnDeck has a higher NPL or provision rate. However, OnDeck also applied for a higher pricing for both facility fee and net interest margin. Traditional banks remain competitive in this coming revolution because commercial banks and online lending platforms targeted different markets.
Efficiency and pricing were a trade-off. This research found that the worst efficiency translated into a lower default rate or provision rate. Meanwhile, OnDeck charged higher interest rate to borrowers and it has better efficiency. Size of a facility is also associated with efficiency and risk management. With better risk management or better KYC (know-your-customer), lenders were willing to grant a larger size of facility.
This study found that OnDeck has better efficiency because it adopts fully automated lending decision and collects data from borrowers or public information. Comparing to DBS Local Lending Program, when certain degree of automation is applicable, validation or
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information input by bankers are still required. Besides, OnDeck used its own algorism to grade its borrower instead of referring risk rating to external reference. Benefited by less human-driven decision, OnDeck has better efficiency than DBS.
This research also found that small-sized company suited online lending platform better because most of the time small-sized companies ask for simple working capital loan. As a company grows bigger, it requires a more structured product, which online lending platform cannot provide. Those products include documentary trade service, letter of credit, guarantee, merger and acquisition or other corporate finance related deals. Therefore, small-sized companies with stable and recurring cash flow are the optimal target customer for online lending platform.
An automated lending system is under development by DBS. By learning from OnDeck, DBS could focus on small-sized business and try to implement automation for its lending decision. To reach a better balance of risk and return, DBS could increase interest charge or facility fee for small-sized customers, who utilize DBS Online Lending Program.
5.3. Keys to improve efficiency of DBS local lending program
The key difference of DBS local lending program and OnDeck Scoring was the degree of automation of a lending process. OnDeck Scoring required fewer data input by borrowers and mainly relied on algorithm to do lending decision. However, OnDeck has to bear a higher provision rate and borrowers are required to pay a higher net interest margin compared to lending from DBS. As a lender, it is very difficult to balance risk and efficiency given information asymmetry. Even though OnDeck is able to approve a loan in minutes, OnDeck had not been profitable since establishment due to NPL.
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In this research, a cross case analysis of lending decision process of DBS Local Program and OnDeck was conducted. Four key findings are listed as below.
1. Data driven lending decision. By comparing DBS Local Lending Program and OnDeck, this research found both bank and online lending platform adopted a certain degree of automation. This research discovered that more and more information are to be input manually directly by borrowers or could be automatically retrieved from public information.
Reducing labor cost and relying less on subjective decision. In the traditional lending decision, bankers have to validate and analyze all information and then
bankers submit their analysis to credit approvers. That is to say, the traditional lending decision takes a long time to reach consensus by maker and checker. Also, the process is time-consuming and detail-oriented. Comparing to traditional lending decision process, lending by program costs less and has better efficiency.
Data integrity becomes important. In the traditional lending process, experience of individuals is more important than data quality but this situation is different from the online lending platforms or lending decision in the future. By adopting automation and relying on data inputted by applicants, how to validate data cleansing and maintain clean database becomes a new topic in new the current lending decision. With less subjective decision and higher degree of automation, clean and correct database becomes a key issue of lending decision.