Earnings Show AI Lending Platforms Scaling Originations

In recent weeks, FinTech lenders reported that automated underwriting systems, with AI in the mix, are enabling them to process large numbers of applications and expand loan originations across consumer and small-business credit markets.

Loan Originations Expand Across Digital Platforms

Upstart said its platform processed approximately 456,000 loan transactions during the fourth quarter, an 86% increase year over year, bringing more than 300,000 new borrowers onto the platform. Personal loan originations rose 41% from the prior year, while the company’s newer secured lending products expanded rapidly. Auto and home loan originations each increased roughly fivefold compared with the previous year.

SoFi said it originated $10.5 billion in loans in the fourth quarter alone. Personal loans accounted for $7.5 billion of that total, while student loans reached $1.9 billion and home loans totaled roughly $1.1 billion.

Small-business lending also expanded. Enova reported $2.3 billion in loan originations during the fourth quarter, representing a 32% increase from the prior year. Of that amount, $1.6 billion came from small-business lending, which grew 48% year over year and now represents the majority of the company’s lending portfolio.

The increases illustrate how digital lending platforms have expanded beyond consumer credit products into broader segments of the lending market.

Automation Is Driving Underwriting Decisions

Executives say those volumes are being enabled by increasingly automated underwriting systems.

At Upstart, machine learning models analyze borrower characteristics using large repayment datasets. The company said its underwriting models now incorporate more than 100 million repayment events, allowing the algorithms to refine approval decisions and better distinguish risk levels across applicants, according to commentary on the conference call.

OppFi described a similar trend toward automation. CEO Todd Schwartz said automated underwriting approved nearly four out of five applications during the quarter.

“The auto-approval rate in the fourth quarter was 79%, which allowed more customers to be approved without human interaction and helped increase originations 48% year over year,” Schwartz told analysts during the company earnings call.

These models are designed to speed application processing and to segment borrower risk, pricing loans accordingly.

Credit Metrics Show Mixed Signals

While origination growth has been strong, credit metrics across the sector show a more complex picture.

At SoFi, personal loan credit performance remains relatively stable. Borrowers in that portfolio have a weighted average income of roughly $158,000 and an average FICO score of 746. Charge-offs in the personal loan segment were 2.8% in the fourth quarter, up modestly from the previous quarter but still more than 50 basis points lower than a year earlier.

Enova reported similar stability in several parts of its portfolio. The company said its consolidated net charge-off ratio was 8.3% during the quarter, down 60 basis points from the prior year. Its small-business portfolio showed particularly steady performance, with net charge-offs at 4.6%, while the consumer segment posted a higher but stable 16% charge-off rate.

OppFi reported stronger profitability but acknowledged rising stress in certain loan vintages. Net charge-offs reached 45% of revenue in the fourth quarter, up from 42% in the prior year period. Executives said some of the increase reflected inflation pressures affecting borrowers’ discretionary income and repayment capacity. During the call with analysts, CFO Pamela Johnson said: “One of the benefits of short-duration loans is that loans work through the system relatively quickly. That means that by first quarter 2026, the majority of the higher default rate loans should be reflected in our earnings.”

Credit Access Remains a Key Driver of Demand

Executives also pointed to structural factors behind the growth in digital lending.

Enova cited survey data indicating that nearly three-quarters of small-business owners bypass traditional banks and instead seek financing from alternative lenders. Among those who initially approached banks, 46% reported being denied credit.

That dynamic has helped sustain demand for lending platforms that can process applications quickly and evaluate borrowers outside conventional credit scoring frameworks.

At the same time, lenders continue to emphasize risk discipline. Upstart executives told investors that recent loan vintages generated returns exceeding Treasury yields by more than 600 basis points on average, which the company attributed to improvements in underwriting models.

The Central Question for AI-Underpinned Lending

The earnings disclosures collectively illustrate how AI-driven underwriting platforms have become a meaningful source of credit in consumer and small-business markets.

Yet the data also makes clear that the central issue for these lenders moves beyond scale. The sector is producing large origination volumes, but the durability of those models will ultimately be determined by credit performance over time.