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Consumer Lending Companies Valuation [2024]

    Valuation methods for consumer lending companies consist of projecting the financials from revenue down to earnings. (Note: in this analysis, consumer lending companies include personal loan companies.)

    So, in order to understand the valuation method, you must identify the revenue sources. Consumer lending companies generate revenue through various channels.

    How Do Consumer Lending Companies Make Money?

    The 2 primary revenue drivers of consumer lending companies are interest income on loans and fees such as origination and service fees.

    consumer lending lendingclub revenue
    Source: LendingClub 2023 10K MD&A
    1. Interest Income
      The main revenue source is the interest charged on loans. For instance, LendingClub offers personal loans with interest rates ranging from approximately 7% to 36%, depending on the borrower’s creditworthiness.
    2. Fees
      Lenders charge various fees, such as origination fees, service fees, late payment fees, and prepayment penalties. LendingClub, for example, charges origination fees between 3% and 6% of the loan amount.
    3. Risk-Based Pricing
      Other revenue sources include charging higher interest rates to borrowers with higher credit risk. For example, OneMain Holdings, which serves non-prime customers, offers loans with interest rates that can be higher to compensate for increased risk.
    4. Loan Sales and Securitization
      Some lenders sell loans to investors or bundle them into securities. LendingClub, for instance, sells a portion of its loans to institutional investors, generating immediate revenue and freeing up capital.
    5. Add-On Products
      Lenders may offer additional products like credit insurance. OneMain Holdings provides optional credit insurance products, adding another revenue stream.

    Consumer Lending Companies Valuation Multiples

    Similar to mortgage finance companies, the commonly used valuation multiples are the PE ratio and the P/BV multiple.

    1. Price-to-Earnings (P/E) 

    Out of 44 companies in the dataset, the median PE ratio is 10.3x as of September 30, 2024.

    2. Price-to-Book Value (P/BV) 

    Out of 44 companies in the dataset, the median P/BV multiple is 1.0x as of September 30, 2024.

    consumer lending companies valuation multiples

    Other valuation methods include:

    • DCF, which can be used to triangulate the company valuation.
    • Loan book valuation, which values the portfolio of loans based on expected future cash flows from the loans, adjusted for risks such as defaults and prepayments.
    • EV/EBITDA multiple can be an additional valuation multiple to consider.
    • Net Interest Margin (NIM) analysis can be used as a quick snapshot of a lending company’s financial health. The interest margin is the spread between the interest charged on amounts they lend to borrowers net of the interest rates they have to pay for the original loan from the large banks. Seeing the trend of whether the net interest margin is steady, has been increasing or decreasing, provides a quick view of the company’s profitability projections. But this is only one component of the company’s revenue source, so it should not be the only method to analyze a company’s financial health.

    Key Considerations in Valuing Consumer Lending Companies

    1. Risk Factors: Default rates, charge-offs, and economic sensitivity are critical.
    2. Interest Rate Environment: Rising or falling rates significantly affect borrowing and repayment behaviors.
    3. Regulatory Compliance: Consumer lending is highly regulated, and changes in laws can impact operations and valuation.
    4. Growth Trajectory: Startups or fintech lenders often command higher multiples due to growth expectations.

    Download 2024 Data

    To download the dataset consisting of 44 companies in this analysis, enter your email address below to sign-up for the mailing list and the data set will be sent to your email directly. In some cases, it takes a few hours or a day to receive the email with the data set. 

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