Case Study: BNPL and Loan Product Suite for Modena.ee

Case Study: BNPL and Loan Product Suite for Modena.ee

Modena is an Estonian-based FinTech company that provides smart payment solutions and flexible financing. They bridge the gap between merchants and consumers by offering seamless “Buy Now, Pay Later” (BNPL) integrations and traditional credit products through a fully digital, user-friendly ecosystem.

1. BNPL & Checkout Solutions (B2C)

Modena’s core strength lies in its embedded finance tools for e-commerce and retail stores, designed to increase conversion rates and average order value.

Pay in 3 (Split Pay): Customers can divide their purchase into three equal monthly installments. This is typically interest-free and fee-free for the consumer, making it a powerful alternative to credit cards.

Pay Later (30 Days): Often marketed as “Click & Try,” this allows customers to order goods, receive them, and only pay after 30 days. It is ideal for fashion and home decor where customers want to verify the quality before committing.

Modena Hire-Purchase (Järelmaks): For high-ticket items (electronics, furniture, etc.), Modena offers long-term financing for up to 48 months with instant credit decisions at the point of sale.

2. Personal Lending Products

Beyond the checkout, Modena provides direct-to-consumer financial services via their online platform.

Credit Line (Krediidiliin): A flexible “digital wallet” with a limit of up to €5,000. Users only pay interest on the amount they actually withdraw, providing a safety net for unexpected expenses.

Small Loans & Refinancing: Fixed-term loans for personal projects or the consolidation of existing high-interest debts into a single, more affordable monthly payment.

3. Business Solutions (B2B)

Modena supports the growth of small and medium-sized enterprises (SMEs) with fast, data-driven credit products.

Business Loans: Quick financing up to €50,000 for inventory, equipment, or working capital.

Merchant Portal: A dedicated dashboard for retailers to track BNPL performance, manage refunds, and analyze customer behavior in real-time.

4. Investment Opportunity: Modena Capital

Unique to Modena is their integrated investment platform, allowing retail and institutional investors to earn returns by funding the loan portfolio.

Target Returns: Investors can earn up to 11% p.a.

Safety Features: Most investments are protected by a 60-day buyback guarantee, reducing the risk for the investor.

Why Modena Stands Out?

Speed: Their proprietary credit scoring algorithm provides decisions in seconds.

Regulatory Status: Licensed as a creditor by the Estonian Financial Supervision Authority, ensuring high standards of transparency and consumer protection.

Seamless Integration: Their API allows merchants to add multiple payment options to their webshop with minimal technical effort.

In short: Modena is the Baltic answer to Klarna, offering a comprehensive suite of tools that make buying, selling, and lending more flexible and accessible for the digital age.

Problem:

• Modena needed a scalable and intelligent platform to support its Buy Now, Pay Later (BNPL) and loan offerings for both private individuals and business customers. Key challenges included real-time creditworthiness assessment, streamlining customer onboarding, providing responsive support, and enabling accurate financial forecasting. Manual processes limited growth potential and delayed decision-making in a highly competitive fintech landscape.

Solution:

• SRINI developed a full-featured BNPL and loan platform tailored to Modena’s needs. The solution includes:
• An AI-powered credit scoring engine that evaluates private and business customer risk profiles in real time using transactional and behavioral data.
• A smart customer support system using AI chatbots for fast, 24/7 assistance.
• Webshop plugins that allow merchants to easily offer Modena’s BNPL service at checkout.
• A streamlined loan application portal supporting both B2C and B2B clients.
• Integrated financial planning and forecasting tools, leveraging machine learning models to predict repayment behaviors, funding needs, and cash flow trends.