By 2026, it became clear that traditional credit scoring, based on the analysis of financial reports from past periods, had lost its relevance for e-commerce. This approach proved to be too slow and static, failing to reflect real changes in the dynamics of online business, where key metrics change daily.
In this context, predictive AI analysis emerges, focusing not on the seller's past income but on their future revenue-generating potential. This shift in approach transforms the role of financial institutions: banks and funds are increasingly becoming partners that facilitate the growth of e-commerce, rather than acting as external controllers.
From the seller's perspective, the situation appears challenging. The business is scaling up, products are successfully sold on marketplaces, and all operational data is available in real-time. However, when seeking financing, the bank still:
- requires collateral,
- relies on outdated financial reports,
- ignores seasonal factors, sales dynamics, and customer behavior.
As a result, capital is either inaccessible or arrives too late—after the peak season when it was most needed.
From the perspective of banks and funds, the situation was equally complex. E-commerce was perceived as a high-risk segment, data from marketplaces was fragmented and poorly standardized, and assessing the risks of small businesses required significant time for manual analysis. This made mass financing of sellers economically unfeasible.
However, modern AI scoring changes this paradigm. It analyzes numerous parameters in real-time and views the business as a dynamic system rather than a set of static figures from reports.
Key aspects of such analysis include the dynamics of buybacks and returns. Algorithms can detect anomalies in customer behavior before they start reflecting in revenue, allowing for proactive responses to potential risks, such as a sharp increase in returns or changes in order structure.
Analyzing reviews and ratings also plays a critical role. The sentiment of comments directly impacts sales forecasts, and AI can distinguish between short-term emotional noise and systemic problems related to the product, logistics, or service quality.
Demand forecasting is another important area of analysis. The model takes into account stock levels, seasonality, competitors' pricing strategies, and advertising efforts, helping to understand whether the current assortment can sustain growth without disruptions and cash flow gaps.
All this data forms the so-called "digital DNA" of the seller—a dynamic business profile that is constantly updated and reflects its current operational state.
The existence of such a digital profile allows fintech platforms to make credit decisions in a matter of minutes rather than weeks. Financing becomes a managed growth tool that adapts to the needs of the business.
One of the most notable trends of 2026 has been revenue-based financing. An increasing number of funds and neobanks provide capital without collateral and strict payment deadlines—in exchange for a percentage of future sales. This significantly changes the seller's approach to debt obligations: repayments are tied to turnover, the risk of cash flow gaps decreases, and the business gains the ability to grow during peak moments—such as Prime Day, Black Friday, or seasonal sales—without additional debt burdens.
Thanks to AI models, risk becomes measurable and manageable. For stable sellers, this has led to record reductions in interest rates in the history of e-commerce financing. Banks and funds, in turn, receive more accurate risk assessments, the ability to safely allocate liquidity, and continuous monitoring of the business even after financing is issued, rather than only at the approval stage.
Financing becomes a transparent and controlled process rather than a "blind" one.
In conclusion, it can be confidently stated that AI scoring has become not just an auxiliary tool but the foundation of a new financial architecture for e-commerce. The "digital DNA" of the seller creates a universal language of trust between sellers, banks, and investors. Those who have learned to speak this language gain access to scalable capital. Meanwhile, those who continue to use outdated approaches to assessing online businesses increasingly find themselves outside the rapidly evolving digital economy.
Kylych Kutaiev
Business Mentor
Founder of iSistant (AI platform for e-commerce lending)
Photo www
