AI in MSME: Turning Data Shadows into Credit Access, Priyashmita Guha, CEO, PSL Association of India

By Puja Sharma

PSLAI is driving a transformative shift in MSME lending by championing ethical, AI-driven credit models powered by India’s Digital Public Infrastructure. Through initiatives like OCEN and Digital Dost, it aims to bridge data gaps, boost financial inclusion, and unlock the full potential of MSME credit access.

What critical trends will shape the future of AI-based lending in India, and how should lenders and FinTechs adapt?

The future of AI-based lending in India will be defined by a shift toward leveraging alternative data sources such as UPI transactions, GST returns, and social media footprints to assess MSME creditworthiness. This evolution heralds a new era in MSME financing, where real-time, behaviour-driven insights complement traditional credit checks. Hyper-personalised loan offerings featuring dynamic repayment structures and industry-specific terms will become the norm. As digital footprints expand, lenders will be able to craft hyper-personalised loan offerings with dynamic repayment structures and industry-specific terms tailored to the borrower’s unique context.

Seamless integration with India Stack components—will drastically reduce loan processing times while improving fraud detection and transparency. At the same time, ethical AI practices and robust bias mitigation, supported by transparent regulatory frameworks, will take centre stage in fostering trust. Ethical AI and bias mitigation, supported by transparent regulatory frameworks, will also take centre stage. Collaborations fostered by initiatives like the RBI’s Regulatory Sandbox and DPI elements such as OCEN will further fuel innovation.

To remain competitive, lenders and FinTechs must:
• Build modular AI architectures adaptable to regulatory changes.
• Invest in explainable AI to foster transparency and trust.
• Partner with India Stack-enabled platforms, especially Account Aggregators.
• Strengthen cybersecurity infrastructure to comply with the DPDP Act, 2023.

What are the key challenges in scaling AI-based lending for MSMEs, and how can stakeholders collectively address them?

Scaling AI-based lending for MSMEs involves overcoming deep-rooted systemic and infrastructural challenges that hinder credit inclusion and scalability:
• Data Fragmentation: Many MSMEs still operate informally and lack digitised financial records, making it difficult for lenders to assess creditworthiness accurately.
• Digital Literacy Gaps: Especially prevalent in rural or semi-urban areas, these gaps prevent MSMEs from effectively engaging with digital lending platforms.
• High-Risk Perception: Lenders often perceive MSMEs as high-risk borrowers due to their irregular cash flows, lack of collateral, and sectoral volatility.
• Infrastructure Deficiencies: Inconsistent internet access and limited smartphone penetration continue to pose obstacles in remote and underserved areas.

To overcome these hurdles, stakeholders must collaborate:
• Banks & FinTechs: Should collaborate on creating centralised, secure data repositories built using GST, UPI, and invoice data, enabling a more accurate borrower profile.
• The government needs to scale investment in multilingual, user-friendly digital literacy campaigns, including the use of voice-based AI interfaces to reach a broader demographic.
• NBFCs & Credit Bureaus Can play a catalytic role by adopting psychometric tools and AI models that analyse behavioural patterns to predict creditworthiness.
• Regulators: Should enhance AI integration into platforms like “PSB Loans in 59 Minutes” to facilitate rapid, low-cost, and inclusive underwriting models.
• Industry Bodies: Must champion standardised frameworks, similar to TREDS, to reduce information asymmetry and foster trust between lenders and MSMEs.

How can AI-driven credit models bridge the MSME financing gap, and what role does PSLAI play?

AI-driven credit assessment models can successfully bridge the long-standing MSME financing gap by transcending traditional hurdles in risk assessment and operational efficiency.

They tap non-traditional signals e-commerce transaction history, mobile phone usage patterns, and digital payment behaviour, previously invisible credit-worthy businesses to the formal financial system.

In addition, predictive analytics enables lenders to forecast future cash flows more precisely, which is especially valuable for MSMEs operating in seasonal industries such as agriculture, tourism, or textiles. Through automating underwriting procedures, AI has the potential to bring down loan turnaround times from weeks to a few hours, enhancing access and experience.

PSLAI is committed to promoting financial inclusion and supporting India’s growing MSME ecosystem through ethical AI lending practices by –
• Driving responsible AI adoption aligned with RBI norms.
• Facilitating capacity-building initiatives through advanced AI tools.
• Encouraging innovation via partnerships with FinTechs and pilot programs.

What are PSLAI’s short- and long-term goals, and which areas is it focusing on?

PSLAI aims to enable a robust, inclusive ecosystem to tap into India’s $1.47 trillion MSME lending opportunity, ensuring credit access for all viable MSMEs. The vision is to ensure every viable MSME, regardless of geography or scale, can access timely and affordable credit.

Our Short-term objectives:
• Creating rapid, grassroots-level impact through initiatives like Digital Dost, which will help MSMEs get access to a repository of queries about borrowing and will eventually offer MSMEs digital
onboarding support
• Encouraging lender–MSME interaction through curated events like MSME Sabha, designed to bridge gaps in understanding and intent.
• Strengthening channels of collaboration between financial institutions, tech providers, and digital lending platforms to build a cohesive ecosystem.

Our long-term vision:
• Advocate for policy reforms, including:
• Establishing a distinct category for NBFCs focused on priority sector lending.
• Revising NPA classifications and risk-weight norms to align better with MSME realities.
• Expanding the scope and scale of credit guarantee schemes to de-risk lenders.
• Simplifying KYC and documentation norms to encourage formalisation without increasing burdens.

How is PSLAI promoting digital credit access through initiatives like OCEN and DPI?
PSLAI is championing the adoption of the Open Credit Enablement Network (OCEN) and India’s Digital Public Infrastructure (DPI) to improve MSME credit access. By advocating OCEN’s API-led model, PSLAI encourages seamless integration of credit into MSME-facing platforms such as e-commerce and supply chain networks. This enables real-time, data-driven lending decisions powered by inputs like GST invoices and transaction data.

In parallel, PSLAI is working to promote the building blocks of DPI Aadhaar for secure identity verification, UPI for real-time payments, and the Account Aggregator framework for secure, consent-based data sharing. These tools unlock flow-based, rather than asset-based, lending and help in mainstreaming underserved borrowers.

While PSLAI is not a developer of these technologies, it acts as an influential enabler through awareness drives, ecosystem alignment, stakeholder partnerships, and policy advocacy, facilitating adoption through awareness, advocacy, and stakeholder alignment, thus ensuring that digital credit access is not just scalable but sustainable