When embedded finance meets smarter decisioning

• With the increased operational and technological demands of instant credit decisions and disbursements, how is the shift toward real-time, on-demand lending reshaping consumer expectations, and what infrastructure is needed to support it?
• How can seamless user experience be balanced with robust oversight within ecosystems? With embedded finance becoming ubiquitous, how can lenders maintain control over risk and compliance when credit is offered at point of sale?
• Amid regulatory uncertainty, what should be included in a proactive compliance strategy? How should BNPL providers prepare for potential regulation?
• What role does AI-driven decisioning play in enabling smarter, fairer, and faster credit approvals? How can the industry ensure transparency and accountability alongside ethical AI, explainability, and regulatory scrutiny in automated lending?
  
   

Research reveals that the global consumer credit market was valued at $13 billion in 2024, is expected to increase to 13.5 billion this year and will reach 18.8 billion by 2033. That’s a growth prediction of 4.14% CAGR in eight years alongside a spike in demand for loans from individuals and small businesses.

With the rise of e-commerce, the sharing economy, and new payment methods, new generations are evidently more open to digital credit products and alternative lending models. In 2026, more and more customers will expect lending on demand.

In order to deliver on demand, lending must be seamlessly integrated into non-financial platforms. This, embedded finance, can make financial interactions more accessible and intuitive, giving users the customer experience they prefer and ensuring financial services providers keep pace with how the industry is trending. In fact, the embedded finance market is expected to reach $7.2 trillion in size by 2030, a trend that cannot be ignored by lenders if they want remain relevant in the near future.

The time is now for financial institutions to rethink their innovation strategies; collaboration will define the organisations that do not get disintermediated. For instance, Buy-Now-Pay-Later services have surged in popularity and show an appetite for manageable payment plans. This financial model can benefit businesses too, by increasing sale likelihood, raising the average transaction size, and promoting financial inclusion among diverse groups as BNPL helps to make services more accessible.

In addition to accessibility, personalisation expectations are reaching new levels and the industry is experiencing a shift toward customer-centric, flexible and efficient lending practices. AI is also being leveraged to address inefficiencies and improve decision-making – a good example being the use of agentic AI to review client-submitted documents, detecting incomplete or incorrect information and asking customers for updates.

While AI can speed up processes, enhance accuracy and minimise manual intervention, for AI to work across consumer lending processes, financial players need to have a foundation of clean, high-quality data. This is the first hurdle to ensuring customers get the lending experiences that they desire. Whether it’s providing real-time, smarter decisioning, or complying with evolving regulations, financial players must tap into platforms that allow them to rapidly launch and scale innovative products.

Register for this Finextra webinar, hosted in association with Mambu, to join our panel of industry experts who will explore how lenders can maintain control over risk and compliance.