Lease-to-Own lenders face significant challenges as they deal with fintech upstarts, alternatives such as BNPL, and cyclical pressures. Traditional credit assessment and repayment methods are losing their competitiveness. Highline gives lenders superior ability-to-pay information and automates payments, resulting in expanded approvals, reduced losses, and delighted borrowers.
Lenders and billers using payroll-linked payments see a 2/3rds decrease of non-repayment for the average working customer.
Lenders and billers have healthier relationships with customers because both have visibility of customers’ income.
Customers perform, on average, as if their credit score were 80 points higher, lifting about 40MM people out of subprime.
Lenders can offer loans that are generally 25% lower-priced with the same level of risk as conventional repayment methods.
Customers enjoy simplified money management as required bills paid first and 'free to spend' money in their checking account.
Minimizes product impacts by synchronizing payroll inflows/payment outflows regardless of frequencies
Minimizes operational impact by handling job changes, modifications, end of loans, and more
Maximizes coverage by accepting any income type, including 1/3rd of the time where splitting the routing is not possible (Social Security for example)
Maximizes coverage and conversions through direct API integrations with payroll platforms
Minimizes regulatory risks by accepting protected incomes and respecting UPAAD guidance
Expand Credit. Approve marginal declines with Highline as the required payment method
Offer Payment Choice. Lower prices, better terms for new borrowers that agree to use Highline
Eliminate Checks. Require new borrowers to set up either Highline or ACH/card debits before new leases are approved
Dedicated Payroll Payment Product. Offer a differentiated product that requires Highline, increasing originations from a target segment
Convert Existing Customers. Offer better terms or discounted rates to convert existing borrowers to Highline, especially in high-risk segments