SINGAPORE, October 07, 2024 /24-7PressRelease/ -- The report reveals significant growth projections across various sectors of digital lending. AI-powered lending models are expected to enhance credit risk assessment, potentially improving performance by 10-15% compared to traditional models. The global peer-to-peer lending market is projected to surpass US$705.81 billion by 2030, growing at a CAGR of 26.7% from 2022 to 2030.

Decentralised Finance (DeFi) emerges as a major trend, with the market valued at USD 13.61 billion in 2022 and expected to expand at a CAGR of 46.0% from 2023 to 2030.

The report also highlights the growing influence of open banking, noting that by January 2024, 13% of digitally active consumers in key European markets were using open banking services.

Overall the digital lending platforms market is set for significant growth with projections indicating it will reach a valuation of USD 795.34 billion by 2029, growing at a CAGR of 11.90%.

Amir Nada, ROSHI Founder and CEO, stated, "Our report shows staggering growth across the digital lending sector. With the peer-to-peer market approaching $706 billion by 2030 and DeFi expanding at 46% annually we're witnessing a seismic shift in financial services. The projection of digital lending platforms reaching nearly $800 billion by 2029 underscores the massive transformation ahead."

The report explores additional trends including the rise of green loans, the impact of personalization on lending practices and the regulatory challenges facing the industry. This comprehensive view aims to provide valuable insights for financial institutions, policymakers and consumers alike.

ROSHI launched in March 2022 and continues its mission to offer transparent and data-driven insights to help stakeholders navigate the complex and rapidly changing landscape of digital lending.

The full report is now available here.

ROSHI is a Singapore-based fintech revolutionizing digital lending across Southeast Asia. The AI-powered loan matchmaking platform has processed thousands of applications and facilitated significant loan volumes. The company's proprietary algorithms analyze hundreds of data points per application markedly improving loan qualification rates compared to traditional methods.

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