Introduction When the Reserve Bank of India released its draft Directions on Expected Credit Loss (ECL)  on October 7, 2025, it started one of the biggest updates to India’s banking rules in decades. The draft replaces the old “incurred loss” system with a forward-looking, data-based approach  to credit risk. The goal is simple: help banks spot stress early, protect capital, and make the system stronger. The framework will start on April 1, 2027 , with a transition period until March 31, 2031 . For lenders facing pressure from unsecured retail, microfinance, and small-business loans, this move comes at the right time. Why the Change Matters India still uses the incurred loss model , where banks set aside money only after a borrower defaults. This often delays recognition of stress and makes downturns worse. Global standards such as IFRS 9  and CECL  already use an expected loss  model, which anticipates losses much earlier. RBI’s draft ECL Directions bring India in line with those standards while fitting local needs. The timing is important. Credit growth is solid, but defaults in unsecured loans, microfinance, and MSMEs  have been rising. Predictive provisioning helps banks react faster and keeps profits steadier. The draft also replaces more than 70 circulars and master directions  issued since the 1990s. It is a complete reset of how India manages loan loss provisions. What the Draft Directions Introduce The new framework gives banks a clear structure for measuring expected losses. Key features: A three-stage ECL model ○       Stage 1:  Performing assets, 12-month expected loss ○       Stage 2:  Assets with significant increase in credit risk (SICR) , lifetime expected loss ○       Stage 3:  Credit-impaired assets, lifetime expected loss with higher minimums Prudential floors  as minimum coverage levels — 0.25 to 1 % for Stage 1, 1.5 to 5 % for Stage 2, and up to 100 % for Stage 3. Governance:  Board-level oversight, model validation, and independent audit Data:  At least five years of historical loss and recovery data Macroeconomic scenarios:  Use of probability-weighted outcomes under different conditions Disclosure templates:  Detailed reconciliations and macro assumption reporting Governance, Data, and Model Requirements The draft Directions formalize a comprehensive governance framework  for ECL: Board responsibility:  Overall approval and periodic review of ECL methodology. CFO + CRO subcommittee:  Oversee implementation, controls, and disclosures. Model validation:  Mandatory independent validation before rollout and periodic revalidation. Audit trail:  End-to-end traceability of assumptions, data, and model results. Data requirement:  At least five years of granular default and recovery data . Collateral valuation:  Regular updates; once at classification and every two years thereafter for large exposures. Borrower linkage:  If one exposure of a borrower is in Stage 3, all exposures are treated as Stage 3. This is a major step toward data-driven governance  - shifting compliance from manual provisioning to continuous, analytical control. Practical Implementation and Transition Planning RBI has chosen a gradual approach so banks can adjust smoothly without any sudden strain on their capital reserves. The new system begins April 2027 , with transitional relief until March 2031 . Banks may add back part of the initial ECL shortfall  to core capital (CET 1) during this period. RBI is also revising the Standardised Approach for Credit Risk , expected to reduce risk weights for MSME and housing  loans. These measures work together. Early provisioning will raise short-term costs ( especially driven by Stage 2 assets ), but lighter risk weights and capital relief will balance it out.  By 2031, India’s banks will have cleaner balance sheets and capital buffers that match their true risk. How ECL Actually Works Under ECL, banks estimate losses for every loan when it is made Formula:   ECL = PD × LGD × EAD Example:  If a borrower has a 2% chance of default, 50% loss given default, and ₹10 lakh exposure, the expected credit loss = ₹10,000. That amount is provisioned immediately, even if the borrower is currently performing. Loans move between stages as risk rises, using triggers like payment delays or rating downgrades. This impacts ECL through the underlying components of PD and LGD. The Directions specify that if a borrower’s payment is more than 30 days past due (SMA 1 asset), the loan is automatically presumed to have undergone a significant increase in credit risk (SICR). This means it must shift from Stage 1 to Stage 2 unless the bank has documented evidence to rebut this assumption. This rule creates a uniform trigger for early warning and lifetime provisioning across the industry. Expected and Unexpected Losses – A Clear Split The ECL model formalizes the divide between expected  and unexpected  losses. Expected losses  are regular defaults that can be predicted. They are now covered fully through ECL provisions shown in the profit and loss account. Unexpected losses  are rare shocks such as recessions or sudden failures. They are absorbed by capital buffers  under Basel rules. This split helps banks plan better and price risk more fairly. Capital now protects against only extreme events, while provisions handle the usual level of credit loss. The prudential floors in the draft act as guardrails  so that models do not underestimate expected losses. Together, they create a two-layer defense : Provisions for normal, expected risks. Capital for rare, unexpected shocks. Industry Impact – Winners, Challenges, and Opportunities The new model will reshape how banks lend and monitor credit. Credit evaluation  will depend more on data — borrower behavior, repayment trends, and forward-looking indicators. Profit stability  will improve because losses are recognized early instead of in sudden waves. Portfolio management  will become dynamic, with frequent review of SICR triggers and segment performance. Governance and data  will take center stage: boards must approve models, internal teams must validate them, and all data and assumptions must be traceable. Who benefits ●       Large banks  with diversified portfolios and strong buffers are well positioned. ●       Sectors like MSME and housing  benefit from lower risk weights under revised Basel norms. Who faces pressure ●       Lenders heavy in unsecured retail, microfinance, and small business  loans will see higher provisions and model costs. ●       NBFCs and co-lenders will need to provide higher data quality  to partner banks. Where new opportunities arise ●       Growing demand for ECL models, validation tools, and provisioning automation . ●       New business for fintechs  offering credit analytics, scenario engines, and data enrichment. OneFin’s View – Ready for Predictive Provisioning At OneFin, we see ECL as the start of a wider move toward predictive and robust risk management  built on the foundations of a strong data and modeling ecosystem Our platform already supports: ECL-ready, stage-based provisioning models  and rule configurations able to handle complex DPD transition scenarios  using historical patterns. Scenario simulation features that use forecasted macroeconomic indicators to determine base, optimistic and pessimistic future states and estimate probability-weighted losses. Integrated origination, loan management, and collections modules , giving unified data for credit monitoring. Audit and reporting tools  that create traceability and data integrity for governance reviews. OneFin, based on its extensive experience in risk modelling and risk management has built out a sophisticated suite capable of handling all the implementation nuances and edge cases  for ECL as detailed in the pointers above. While each bank will still design its own regulatory models, OneFin offers the flexible, low-code base  needed to build, test, and deploy these capabilities quickly. The Road Ahead The draft ECL Directions turn India’s credit system from reactive  to predictive . Once final, they will replace nearly all provisioning and asset-classification rules issued since the 1990s - a true modernization of banking regulation. The next 18 months are the time to prepare: ●       Start ECL pilot projects  on selected portfolios. ●       Improve data capture and quality  across products. ●       Build governance and validation teams  around risk models. ●       Plan capital and disclosure processes  for the transition period. With careful preparation, lenders can meet new standards and gain an edge in credit discipline. For those ready to act early, ECL is the path to smarter, steadier growth. To know more, schedule a Demo .

1️⃣  Featured Insight - No more GST on penal charges. RBI had instructed all REs to not levy any penal interest for defaulting customers, but to only levy penal charges. This change was initially announced on  18th August 2023 (Circular Attached)  with an implementation timeline of 31st Dec 2023, which was later extended to 1st April 2024 in a  FAQ  issued by the RBI. Now the GST council has clarified in its meeting held on 21st Dec 2024, and notified on  28 Jan 2025 (Circular Attached) . that no GST would be applicable on penal charges, as it is considered a deterrent for payment, and not a payment in itself. Here are 3 things that must be implemented in your LOS and LMS accordingly, to ensure compliance against charges. 💡Change accruals and accounting of penal charges Currently, all accruals of penal charges which would be happening in the system would have been with GST. Suppose accruals were being done at say 24% annualized rate including GST, then excluding GST it must be done at 24 / 1.18 = 20.34% annualized rate. Accounting configurations should be changed to not calculate GST on the charges. Earlier IGST / CGST / SGST split would be happening, now no GST liabilities are to be created while accounting. Since, no GST is payable, no more invoices need to be generated for penal charges. Earlier invoices would have been generated and the same would have been reflected in the GST sales registers. Now penal charges should be removed from the invoice generation process and correspondingly from the GST registers. As per the existing regulations, do not apply compounding on penal charges, meaning, no penal charges no overdue penal charges should be applied. 💡Consider regulations on charging GST on bounce charges The 28 Jan 2025 circular, refers to an earlier GST circular dated  3rd August 2022 (Circular Attached) . In the August 2022 circular, it is mentioned that for “Cheque dishonor fine/ penalty”, no GST should be charged. Consider the above regulation while formulating your policy for GST on bounce charges. As a best practice, only apply bounce charges, when a cheque or NACH dishonour happens due to insufficient funds. It should not be charged when a bounce happens due to other reasons like incorrect mandate ID etc. 💡Send out customer communications, update your documents Once the changes are implemented in your LMS , update the same to customers via a one time email and sms campaign. The current sanction letters / loan agreements / KFS would also need to be updated, to reflect that penal charges are not going to include GST. Ensure that vernacular versions of the documents also reflect the same. Since, it is a change in policy and documents, take appropriate approvals within the organization, before affecting the same. 2️⃣  Industry News Roundup 🗓️ Razorpay FTX 2025 event will be held in Bangalore on 20th Feb. You can also join remotely [ Reference ] 🗓️ The role of FinTech in building Viksit Bharat: A Paper by EY with interesting data and insights [ Reference ] 3️⃣  Stats of the week 📊 RBI recently announced that the NBFC UL remains unchanged. NBFC UL accounts for 25.2% of all assets held by all NBFCs. 📊 As of September 2024, total loans and advances given by NBFCs is 42,92,708 crores, compared to 40,27,478 crores as on March 2024, showing an annualized growth rate of 13%, a slow down from 18% growth between March 2023, and March 2024. Want to get weekly content regarding new developments in banking technology? Subscribe to our newsletter  here . Are you a CXO at a bank / NBFC / fintech company interested in upgrading your technology? We would love to show you a demo of the OneFin offering. We provide end to end capabilities including configurable modules like LOS, LMS, Accounting System, Collection System, Digital Journeys etc. Schedule a Demo  here . Linkedin Post - https://www.linkedin.com/pulse/banking-technology-insights-more-gst-penal-charges-fintech-pclhf

Introduction Microfinance has long been central to India’s financial inclusion story. But recent data  shows the sector is going through a sharp correction. Disbursements are down, delinquencies are rising, and lenders are pulling back. For MFIs, this is a period to reset strategies rather than chase growth. State of the Sector: The Numbers That Matter Loan disbursements  fell 26% YoY , to ₹56,677 crore  in Q1 FY26, across 1.01 crore accounts. The broader microfinance universe (all lender types) saw sharp contractions: NBFC-MFIs (-18% YoY), Banks (-15.8%), SFBs (-23.2%), and NBFCs (-1.3%). Portfolio at Risk (PAR 31–180 days) more than doubled to 5.7% in June 2025, from 2.7% a year earlier. Long-tail stress is evident in rising >180-day buckets. The average loan ticket size  rose 14.6% YoY, to ₹56,018 per account , as lenders focused on fewer, larger loans. Within the NBFC-MFI segment, asset under management (AUM)  stood at ₹1.3 lakh crore  (June 2025), down 16.4% compared to June 2024. Client outreach  shrank: NBFC-MFI borrowers fell to 3.8 crore , 16.5% lower than June 2024 Unpacking the Underlying Pressures The decline is not only about numbers. Several structural issues are driving the correction. A “Flight to Quality” MFIs are focusing on borrowers with stronger repayment history. This has pushed up average ticket sizes  while cutting overall client volumes. The move reduces near-term risk but may create hidden stress if larger loans begin to slip. Borrower Overleveraging Low-income households face repayment pressure from multiple loans. Income shocks - from poor harvests, high rural inflation, and weak wage growth - have made matters worse. When one loan defaults, others follow. Capital and Liquidity Squeeze Debt funding for NBFC-MFIs dropped by 35.7% in FY25 , as banks scaled back wholesale credit. Equity capital also fell by 1.8%, but sector leverage (debt-to-equity ratio) improved. With tighter funding, lenders are forced to slow disbursements and focus on collections. Regulatory and Institutional Guardrails Self-Regulatory Organizations (SROs) and the RBI have nudged MFIs toward better underwriting, more borrower checks, and tighter controls on multiple lending. This has slowed growth but may help clean up risks. Regional Divergence Top states such as Tamil Nadu, Bihar, and Karnataka are under greater stress, with rising delinquencies. The share of East & North East and Central markets of the Gross Loan Portfolio (GLP) increased while that of the South reduced, highlighting a divergence. Markets like West Bengal show stability. This is not the first time microfinance has faced a deep correction. In 2010, the crisis centered around Andhra Pradesh, where heavy borrower overlap between MFIs and state-supported SHGs led to a localized collapse. The sector eventually recovered through stronger regulations and borrower checks. The difference this time is that stress is more dispersed - across multiple states and lender types - making it a national rather than regional reset. The industry’s resilience will depend on how quickly these reforms translate into consistent, nationwide stability. What This Means for Lenders Recent industry commentary suggests that the worst may be behind. While the cleanup is still ongoing, early indicators such as improved short-term repayment behavior and cautious re-entry into lending point toward gradual stabilization. Lenders across banks and NBFC-MFIs now describe their outlook as one of guarded optimism rather than distress. Those that balance caution and innovation will emerge stronger. (A) Short-Term: Cleanse, Buffer, and Triangulate Portfolio pruning : Identify and exit severely stressed accounts. Off-load exposures that are unlikely to recover to prevent contagion. Provisioning and buffers : Strengthen capital reserves. A conservative approach will give room to absorb higher delinquencies. Collection discipline : Build early-warning systems. Use borrower-level analytics to flag stress at 30–60 days before it escalates. Liquidity cushions : Secure alternate lines of funding. Maintaining liquidity buffers ensures stability in the face of uneven inflows. (B) Medium-Term: Smarter Origination and Analytics Segment-level scoring : Apply alternate data like agri indexes, weather, and mobility patterns. These indicators can give a better picture of repayment capacity. Dynamic pricing : Adjust loan pricing based on borrower risk and regional volatility. This makes lending sustainable even in stressed areas. Borrower overlap tracking : Monitor how many lenders a borrower is already exposed to. Reducing over-indebtedness helps lower systemic risk. Resilience products : Bundle micro-insurance, income smoothing, or savings with credit. This reduces vulnerability to shocks. (C) Strategic Shifts: Diversify Safely Adjacent credit verticals : Expand into MSME microcredit or livelihood loans that tie directly to income generation. Co-lending and guarantees : Use partnerships to share risk. This allows scaling without over-exposure. Fintech partnerships : Leverage digital players for origination, data, or collections. Technology can lower costs and improve reach. Geographic hedging : Spread exposure across stable and volatile regions. This balances growth with portfolio safety. OneFin’s Role In times of stress, technology platforms act as stabilizers. They help lenders monitor, manage and mitigate risk. The mature OneFin ecosystem is pioneering in this regard: Adaptive credit workflows : Configurable pipelines allow lenders to switch between growth and conservative mode as conditions change. Delinquency monitoring : Real-time dashboards highlight shifts in 30/60/90-day buckets and borrower overlaps (using bureau data like CRIF Highmark)  Co-lending management : Built-in infrastructure for handling risk-sharing agreements with banks or other lenders. Scalable integrations : Plug-and-play APIs reduce time and cost in expanding operations. These capabilities help lenders stay agile, protect portfolios, and prepare for the next growth cycle. Conclusion FY25 was a reset year for microfinance. Disbursements fell, portfolios shrank, and risks grew. But the slowdown is also an opportunity to rebuild on stronger foundations. Microfinance has always run in cycles of excess and correction, but history shows that the sector adapts and rebounds. OneFin believes this phase, too, will give rise to a more robust, data-driven ecosystem that continues to empower rural borrowers, especially women, for whom MFIs remain the most accessible path to formal credit. For lenders, the path forward lies in discipline, sharper analytics, and diversified risk. OneFin is positioned to help institutions balance risk and opportunity. By supporting resilient credit practices and scalable operations, the platform helps turn a period of stress into a springboard for the next cycle of inclusion-led growth. To know more, schedule a Demo .

Introduction Accessibility is no longer optional. In April 2025, the Supreme Court declared  that digital access is a fundamental right . At the center of the case was India’s digital KYC process. As we know, this has now become essential for opening bank accounts, buying SIM cards, accessing pensions, insurance, securities, and even government benefits. The Court found that current steps shut out people with blindness, low vision, or facial disfigurement. This violated Article 21 of the Constitution  and the Rights of Persons with Disabilities Act, 2016 . At its end, the RBI has already been proactive in enabling effective financial access to all citizens. The message is now clear: digital inclusion is a constitutional and regulatory duty . For lenders, this is not just about compliance. It is also a chance to expand reach, build trust, and lead in inclusive finance. Context: Why This Matters Over the past decade, financialization has been a key driving force of the growth of the Indian economy. At its core has been inclusion,  with ambitious efforts like the PM Jan Dhan Yojana being key in expanding basic banking services to the underserved urban poor and rural populations. As we continue to expand on the tech frontiers in finance, with activities like KYC, loan applications and management being done digitally, accessibility concerns have risen again. Digital KYC , which has become the backbone of India’s financial system, has hardly been inclusive of the millions of Indians with disabilities. For example, eye-blinking checks blocked acid attack survivors and people with eye injuries. Selfie uploads and face recognition left people with blindness dependent on others. In a similar vein, lending documentation and interfaces not being available in vernacular languages  has been deeply problematic for the vast rural, urban poor and MSME populations who are usually only literate in their own regional language. The Supreme Court’s ruling reset the rules: accessibility is no longer a choice. It is a constitutional guarantee. RBI’s Proactiveness on Inclusion The Court’s April 2025 ruling gave binding directions to regulators and service providers of which a few key ones include: Accessibility Standards : All KYC apps, websites, and devices must meet WCAG 2.1 and Indian accessibility norms. Alternative Verification : Liveness checks cannot rely only on blinking. Voice recognition, facial movements, OTP verification, and thumb impressions must be supported. Human Review : Auto-rejected KYC applications must be checked manually by trained officers. Customer Records : KYC/customer forms must capture disability type and percentage so services can be tailored. Inclusive Communication: KYC processes and notifications must support sign language, captions, audio descriptions, Braille, easy-to-read formats, and voice-enabled services. Leading from the front, in August 2025, the RBI issued the 2nd Amendment to its KYC Directions (2016) . It built accessibility into law. Key changes included: Persons with Disabilities are now directly named in the KYC Directions and hence accessibility needs to be a part of the policy. No KYC application may be rejected without proper reasoning, which needs to be documented. Liveness checks cannot exclude people with special needs. Aadhaar Face Authentication is recognized as an extra option. The RBI has actually been proactive in the matter of inclusion. In April 2025, it mandated  that the Key Fact Statements (KFS)  had to be provided in a language understood by the borrower . This was not just for the documents but also for the customer journey portals/interfaces and customer communication. The intent is to make loan and banking processes inclusive for people who are literate in only their own languages. Strategic Implications for Lenders For banks, NBFCs, fintechs, and other financial institutions, the immediate job is to comply. But the bigger story lies in the strategic impact. Expanding the Market: The traditionally overlooked markets like the rural and the disabled form a massive opportunity for forward-looking lenders. Inclusive KYC and vernacular tech lowers barriers, opening a new channel for growth. Trust and Brand Equity: Early movers will stand out as champions of customer experience through inclusion. In a sector built on trust, accessibility can be a strong differentiator. The leaders will go above and beyond the current scope to better serve other excluded market segments as well. ESG and CSR Alignment: Accessibility ties directly to the “Social” pillar of ESG. Regulators and investors expect disclosures on inclusivity. Accessible lending technology positions lenders ahead of global standards. Better Credit Quality: Inclusive processes reduce disputes and onboarding failures. That translates into lower support and legal costs, stronger repayment patterns and fewer compliance-driven NPAs. Growth Lever, Not Burden: What begins as compliance can become a growth driver . The institutions that invest today will not just be safe from penalties - they will also capture tomorrow’s inclusive lending opportunities. How OneFin Can Help OneFin is ready for this shift. As lenders adapt, we provide the tools to move fast, scale safely, and embed accessibility in financial services. Auto-Vernacular Translation : Automated translation of the user journey in 9 Indian languages  to show the information required to the user in their own language. Configurable KYC Workflows : Support for multiple KYC modes with fallback options available as needed. API-First Infrastructure : Add new features like Aadhaar Face Authentication without disruption. End-to-End Lending Suite : Origination, management, and collections built with compliance and inclusion in mind. Proven Scalability : Over 16 lakh loans processed  and 100 million API calls annually. Our Auto-Vernacular Translation feature has been developed in the true spirit of the guidelines. It will help backoffice staff, especially in rural areas, to be able to see their LOS / LMS in their regional language. That would help them serve the end customers better. As India continues to build out the vernacular ecosystem with a massive focus on Indic AI and LLMs, we are prepared to lead on that mission. Expanding the market for financial services to the millions that are still linguistically excluded will drive the next phase of economic growth. Conclusion The Supreme Court has reset the rules of India’s digital economy: accessibility is now a fundamental right . RBI’s directions and amendments mark the first step in enforcement, and other regulators will follow. For lenders, the implications are clear. Compliance is unavoidable, but those who go further - embedding accessibility into their processes and products - will win on trust, customer satisfaction, and growth. With OneFin’s modular, API-driven platform, lenders can act quickly, scale securely, and build for an inclusive future. To know more, schedule a Demo   here .

Introduction The 56th GST Council meeting in September 2025 marked the most significant set of changes since the tax was first rolled out in 2017. The reforms  aim to make essentials more affordable, simplify compliance for businesses, and strengthen the legal backbone of GST. For the financial sector, the implications extend well beyond taxation. At a time when many NBFCs are grappling with rising stress in personal loans and microfinance portfolios, and credit growth is subdued, the new measures could help reset the cycle. Lower costs for households and businesses, faster refunds, and legal clarity all point to a healthier lending environment. Importantly, SBI Research estimates the fiscal impact at only ₹3,700 crore for FY26  — minimal when set against the potential benefits of higher demand and stronger tax compliance. The question lenders must ask is not whether these changes matter, but how to position themselves to capture the opportunities and manage the risks they create . Reforms Overview – Three Pillars The GST Council’s announcements can be viewed under three broad pillars: structural reforms, rate rationalisation, and ease of operations . Structural reforms These measures strengthen the framework within which businesses operate. Key elements include: GST Appellate Tribunal (GSTAT) to become operational by December 2025, providing long-awaited dispute resolution. Risk-based refunds that will release 90% provisionally for exporters and inverted duty claims. Simplified GST registration, with automated approval within three days for low-risk entities such as small e-commerce sellers. Revised place-of-supply rules, making India more competitive for service exports. Rate rationalisation The rate changes reflect a balancing act, aiming for relief for households and MSMEs. Cuts were applied to essentials  such as milk, paneer, butter, soaps, and toothpaste. Socially important categories  like medicines and school supplies were brought down to 5% or exempted altogether. Sectoral relief  came through lower taxes on cement, textiles, renewable energy equipment, and electronics. Increases targeted sin and luxury items  including pan masala, tobacco, luxury cars, yachts, and personal aircraft. Ease of operations By simplifying rules, the Council aimed to reduce friction in daily business. Post-sale discount treatment has been clarified, reducing disputes between manufacturers and distributors. Refund processes have been streamlined, easing cashflow pressures. Valuation rules for sectors like restaurants and lotteries have been clarified. Table: GST Rate Rationalisations Snapshot Lending Impacts – The Dual Dimensions The GST reforms create two major impacts for lenders: credit boost and credit quality improvement. Credit Boost (Loan Demand) Consumers : Cheaper durables, electronics, autos, and housing materials will lift demand for personal loans, home loans, and two-wheeler or car finance. MSMEs : Input tax relief and faster refunds ease liquidity pressures, raising appetite for working capital and growth loans. Dealers & Distributors : Anticipating higher consumer sales, they will stock up ahead of the festive season, driving demand for short-term working capital, supply chain finance, and bill discounting. Caveat: Over-stocking risk if demand underperforms. Agriculture : Reduced tax on tractors and equipment will increase credit demand in rural markets. Industry experts expect a 5–20% rise in credit transaction volumes  during the festive season as well as up to 30% higher e-commerce spends. An estimated 8-10% growth in rural consumption  in the next two quarters is also expected. Credit Quality Improvement (Repayment Capacity) Consumers : Lower GST on essentials reduces household expenditure, freeing up income for EMIs. GST exemption on life and health insurance reduces vulnerability to shocks. Businesses : Stronger sales at the consumer end, combined with refund acceleration and fewer disputes, improve cashflows and repayment ability. Systemic stability : GSTAT and simpler rules create predictability, lowering NPA risks from compliance disruptions. Together, these drivers set the stage for a more balanced credit environment and the tailwinds for the next credit cycle. The Credit Flywheel Effect The most important outcome for lenders may be the creation of a self-reinforcing cycle: Lower GST makes goods cheaper. Consumers increase demand. Dealers and distributors stock more inventory. MSMEs expand production. Higher sales boost revenues. Consumers and businesses repay loans more smoothly. Lenders gain confidence to lend more ( driving both the demand and supply further ) Figure: Credit Growth Flywheel This “credit flywheel” has the potential to sustain itself for 12–18 months if demand holds. The caveat is that if consumption underperforms, excess stocking could turn into stressed credit. Lenders will need to balance growth with prudent monitoring. Takeaways for Lenders The GST reforms set the stage for new opportunities across major lending segments: Consumer Credit : Demand for housing, autos, and durables will rise with affordability. MSME & Dealer Finance : Liquidity improvements and festive stocking will drive the need for working capital and supply chain credit. Agriculture : Lower costs on tractors and equipment open room for growth in agri-finance. OneFin can be the perfect partner for a lender at this critical juncture, stepping in to provide the right infrastructure and toolkit for scaling. Its modular, low-code platform   allows rapid rollout of new products tailored to evolving demand. Proven scalability with over 16 lakh loans and 100 million API calls annually. This ensures readiness for seasonal or policy-driven surges . Integrated origination, management, and collections systems help embed risk discipline  into expansion. Conclusion GST 2.0 combines two powerful outcomes: higher credit demand  and improved repayment capacity . For banks and NBFCs, this creates the conditions for a lending revival, just as the sector faces pressure from personal loan and MFI stress. If managed prudently, these reforms can create a lending flywheel that fuels growth while reducing systemic risk. For lenders, the task is to prepare product portfolios and risk frameworks to capture this momentum responsibly. With its configurable, API-driven infrastructure, OneFin helps institutions act quickly, scale securely, and manage risk ,  turning a policy shift into a strategic advantage for sustainable lending growth. To know more, schedule a Demo here .

Introduction: A Turning Point for AI in Finance Artificial Intelligence (AI) has quickly moved from lab experiments to everyday financial applications. Chatbots now resolve customer queries, machine learning models power fraud detection, and generative AI tools prepare loan summaries. Globally, investments in AI across banking, insurance, and capital markets are expected to exceed ₹8 lakh crore by 2027 , with generative AI growing at 28% to 34% annually this decade. In India, the Reserve Bank of India (RBI) has recognized this momentum. Through the FREE-AI (Framework for Responsible and Ethical Enablement of AI) report released on 13th August, RBI set a clear vision: AI is inevitable, but it must be adopted responsibly. The framework stresses trust, fairness, accountability, explainability, and resilience as must-haves. For NBFCs and banks, especially in the mid-market segment, the choice is no longer whether to adopt AI. The real question is how to use it in lending while balancing innovation, compliance, and customer trust. Why AI in Lending Matters Now Lending is one of the most AI-ready areas in financial services: Efficiency : AI speeds up loan approvals, automates document checks, and supports 24/7 customer service through chatbots. Alternate Credit Scoring : AI uses utility bills, GST filings, mobile usage, or e-commerce history to assess “thin-file” or new-to-credit borrowers. Fraud and Risk Management : Machine learning spots anomalies faster than rules-based systems, reducing losses. Personalization : Multilingual and voice-enabled AI tools help lenders reach India’s diverse customer base. The RBI’s own survey highlights the opportunity. Top use cases include customer support (15.6%), credit underwriting (13.7%), and cybersecurity (10.6%). Source: Page 28 of FREE-AI Committee Report Among regulated entities, SCBs and NBFCs are adopting AI steadily (52% and 27% respectively). Nearly two-thirds are already testing at least one generative AI use case , often through pilots such as internal chatbots. Source: Page 26 of FREE-AI Committee Report Institutions that avoid AI risk falling behind more agile peers. They may also struggle to counter AI-driven fraud or serve the growing new-to-credit segment. RBI itself warns of the danger of “ AI inertia ” - falling behind by not adopting new technology. The Balancing Act: Innovation and Risk The RBI’s FREE-AI framework sets out seven guiding principles , or “ Sutras ,” for AI in financial services. These are further expanded into six pillars and 26 recommendations covering the two broad areas: Innovation Enablement and Risk Mitigation . Source: KPMG Insights on FREE-AI Committee Report These principles are especially important in lending, where every credit decision carries high stakes . A loan approval or rejection can shape livelihoods, businesses, and financial stability. When AI models make these decisions, institutions face key challenges: Bias and fairness : Could skewed data exclude certain groups? Explainability : Can lenders give borrowers a clear reason when a loan is declined? Accountability : Who is responsible if an AI system makes a mistake—the vendor, developer, or the bank? Operational risk : How can lenders prevent systems from drifting, failing silently, or being hacked? RBI’s position is clear: innovation and risk management must go together . A pro-innovation stance is preferred, but it must rest on accountability and consumer protection. Recommendations that Boost Adoption Some RBI recommendations that will help drive both AI adoption and sector growth include: Incentives and Funding Support : To build shared infrastructure such as compute power, data lakes, and AI labs open to all REs, not just large banks. Financial Sector Data Infrastructure : Linked with the IndiaAI “AI Kosh” initiative, this will provide standardized, high-quality datasets for training and testing AI models. Industry-Level AI Sandboxes : Safe, collaborative spaces where REs can test AI models for credit, fraud, or customer service under regulatory oversight. Light-Touch Compliance for Inclusion-Focused Lending : Reduced regulatory burden for small-ticket loans and AI models aimed at inclusion, to encourage experimentation. What Executives Should Start Preparing For Not all recommendations need immediate action, but some require early planning. Senior leaders should start preparing now: Draft a Board-Approved AI Policy Define principles, scope, and governance. Classify AI use cases by risk (low, medium, high). Assign clear responsibilities at board and senior management levels. Strengthen Data Infrastructure and Governance Map and clean internal data sources for integration with sectoral data systems Build processes for bias testing, lifecycle management, and audits. Maintain an inventory of all AI models, updated at least every six months. Pilot AI in Controlled Environments Select 1–2 use cases (e.g., underwriting, fraud detection) and test them in sandbox settings. Document learnings, risks, and consumer outcomes before live rollout. Join industry-level sandboxes once available. Build Explainability Early Work with partners to embed explainability tools in credit systems. Train staff to explain “reason codes” when loans are denied. Treat explainability as a trust driver, not just a compliance step. Invest in People and Skills Train management, risk, and product teams on AI and risk. Identify gaps needing external support (e.g., data science, governance). Encourage teams to join industry groups and RBI consultations. These steps will prepare REs to act quickly once regulations are finalized, while also building trust and resilience. Early movers will gain an advantage when adoption accelerates. OneFin as the Strategic Bridge OneFin can step in as a transformation partner for REs to help them get ahead. Some of our notable AI-powered tools include: Compliance/Regulatory Report Generator Applicant/Credit Documentation Analyzer Configuration AI Assistant GenAI Chatbot for Customer Support Our API-first lending infrastructure is designed to balance compliance with innovation. The platform is built around a few key facets: Compliance-first : Embedding governance, auditability, and transparency into the lending process. API-native and modular : Giving institutions flexibility to adopt and scale AI-enabled lending at their own pace while tapping into various tools and data sources Innovation-ready : Safe environments for testing, and support for integration with digital public infrastructure. Scalable and future-proof : Built to evolve as regulatory expectations and AI capabilities grow. For NBFCs and banks, OneFin acts as a strategic bridge. It reduces compliance risk through built-in controls, while enabling the organization to innovate. Closing Vision: Building the Bridge AI will shape the future of lending in India - but it must be responsible AI. The winning formula is innovation balanced with accountability, trust, and stability. Compliance is only the starting point. Advantage will come from going further and designing lending systems that are transparent, inclusive, and resilient. Institutions that achieve this balance will protect trust and unlock the next wave of growth in India’s financial sector. Technology partners like OneFin will play a central role in this. Modern Loan Origination (LOS) and Loan Management (LMS) systems can embed compliance guardrails, enable AI innovation, and ensure auditability. To know more, schedule a Demo here .

Executive Summary: A New Era for Collaborative Finance The Reserve Bank of India’s new Co-Lending Directions (CLA) , issued on August 6, 2025, mark a turning point for India’s lending ecosystem. Effective January 1, 2026, these rules shift co-lending from a niche, priority-sector tool to a mainstream model across loan types and sectors. By broadening eligible partners, standardizing rules, and mandating deeper tech integration, RBI has created a scalable framework for future lending. For banks and NBFCs, this is a growth catalyst. The rules improve capital efficiency, expand market reach, and reward tech-enabled players. But they also make manual, siloed systems obsolete. Winning in this new era requires modern, integrated, and automated platforms that turn compliance into a competitive advantage.   Key Changes and Their Business Impact   The new rules introduce three main shifts that affect your strategy, operations, and technology.   1.   A New Universe of Partnerships   The RBI has opened up the co-lending market significantly. Broader Partnerships: The old rules were mostly for banks and NBFCs lending to the priority sector. The new rules allow a wider range of partners, including NBFC-to-NBFC arrangements. All Loan Types Included: You can now co-lend for any loan category, such as personal loans, consumer durable loans, and unsecured business loans, not just priority sector loans. Lower Capital Lock-in:  Each partner must keep at least 10% of every loan on their books. This is down from the previous 20% rule for originators, freeing up your capital to fund more loans. 2.   Standardized Economics and Transparency   The new guidelines focus on making the process transparent and easy for the customer. Mandatory Blended Rate: Borrowers must be charged a single "blended" interest rate. This is a weighted average of each partner's rate (relevant for the risk profile), making pricing clear and simple. Upfront Disclosures:  All details about the partnership, roles, and pricing (including any additional fees) must be clearly stated in the Key Facts Statement (KFS) before the loan is signed. Single Point of Contact:  The loan agreement must name one lender as the single point of contact for all customer service and grievance issues. 3.   Tighter Operations and Risk Management   The rules make deep system integration and clear risk management essential. Unified Asset Classification: If one partner marks an account as a Non-Performing Asset (NPA), the other partner must do the same for their share of the loan. This information must be shared in near real-time. Mandatory Escrow Account: All money, including disbursements and repayments, must flow through a dedicated escrow account. This ensures all transactions are transparent. Strict 15-Day Timeline:  Partners must record their share of the loan on their books within 15 calendar days of disbursement. They also need to maintain the borrower’s account individually for their respective share. Capped Default Loss Guarantee (DLG): An originating partner can offer a DLG, but it is capped at 5% of the outstanding loan amount. This ensures all partners have "skin in the game."   Market Outlook: A Sector Poised for Growth   The RBI's new directions are expected to fuel major growth in co-lending. By expanding the model beyond the priority sector, the rules unlock new opportunities in high-growth areas. Industry experts predict the market could grow from ₹900 billion to   ₹4,000 billion by 2030 . This capital-light model is a huge advantage for tech-driven NBFCs, allowing them to scale quickly. It also helps banks reach new customers in Tier-2 and Tier-3 cities, expanding financial inclusion.   Takeaways: Your Co-lending Toolkit   To meet RBI’s requirements and capture the opportunity, executives can use the practical roadmap below to double down on the focus areas.   Phase 1: Review Your Strategy & Policy Identify new market opportunities (e.g., personal loans, unsecured MSME credit). Decide on new partnership models (e.g., with specialized HFCs or other NBFCs). Update your internal credit policy to include specific rules for co-lending, such as exposure limits, target segments, and partner selection criteria. Phase 2: Update Legal & Documentation Draft a master co-lending agreement template that complies with the new directions. Update your loan agreement template to clearly disclose all partners and their roles. Revise your Key Facts Statement (KFS) template to accurately display the blended interest rate and other mandatory disclosures. Phase 3: Prepare Technology & Operations Conduct a gap analysis of your current Loan Origination (LOS) and Management (LMS) systems. Can they support the new requirements? Start discussions with banks to plan for the setup and integration of escrow accounts. Map out your operational workflow to ensure you can meet the 15-day loan booking deadline. Design a process for real-time data synchronization with partners for unified NPA reporting. Update your credit bureau (CIC) reporting process to correctly report each lender's individual share of the loan. Phase 4: Strengthen Partner Management Create a detailed due diligence checklist for vetting potential partners, including a thorough audit of their technology stack. Establish a clear process for monitoring partner performance and compliance on an ongoing basis. The OneFin Solution: Turn Regulation into a Revenue Engine   Legacy systems are not built for this new, agile co-lending environment. OneFin provides the modern, configurable platform you need to succeed. Challenge:  Managing complex blended rates, separate partner ledgers, and automated payouts. OneFin's Solution: Our platform supports diverse fee structures, automates all calculations and manages the entire cash flow and reconciliation through integrated escrow management. We have deep expertise in the CLM-1 and (now-deprecated) CLM-2 models. Challenge:  Meeting the 15-day booking rule and syncing NPA status in real-time. OneFin's Solution: Our integrated ecosystem of LOS, LMS and accounting modules and API-first architecture ensure seamless, real­-time data exchange between you, your partners, and the escrow account, making compliance an automated, effortless process. Challenge:  Generating compliant documents like the KFS and CIC reports for every loan. OneFin's Solution: Our platform automates critical compliance tasks. From generating borrower-facing KFS with blended APRs to creating individual RE reports for Credit Information Companies (CICs), we embed regulatory adherence into your workflow, minimizing manual effort and eliminating operational risk.   Ready to Build a Future-Proof Co-Lending Engine?   Don't just comply, compete! The RBI has laid out the blueprint for a more collaborative and efficient lending future. Let us show you how OneFin's end-to-end platform including configurable modules like LOS, LMS, Accounting System, Collection System, Digital Journeys etc. can help you reduce operational friction and turn the latest co-lending directions into your next big growth opportunity. Schedule a Demo here .

The RBI governor in his address announced major changes to co-lending arrangements. It highlights the growing importance of co-lending in today’s world. It is a win-win for all parties involved. Originators have better access to distributing loans, either through specializations done by being specialists in a sector or region, or by being in some other business, which gives them access to a niche set of customers and many times specialized data, which helps them in underwriting. Funders on the other hand, may have better access to capital, which can be deployed by being in alliance with the originators.  An important thing to note, is that these are draft guidelines, and the final guidelines will come out after public consultations by the RBI. 💡Who can do co-lending & for what kind of loans? Earlier Co-Lending was allowed only for priority sector loans, that too only between banks and NBFCs. There was no definitive framework for example, for lending personal loans, between any two kinds of REs. Or even priority sector lending loans between two NBFCs. The new guidelines allow co-lending for any kind of loans between any banks and NBFCs. Although note that Small finance banks are excluded from the current guidelines again. 💡Can FLDG be given while co-lending? Earlier the FLDG guidelines were only defined for digital lending. These guidelines were devised such that the default guarantee was capped at 5%. There was no clarity on whether FLDG can be built into a co-lending structure. On the contrary, it was typically assumed that co-lending arrangements are necessarily such that the risk is shared between the two parties. Now it is clarified that the same 5% limit applies for co-lending arrangements, more importantly it gives legitimacy to FLDG within co-lending arrangements. 💡No more CLM2? Earlier there were two models for co lending, CLM 1 and CLM 2, while the CLM 1 model was allowed in the original RBI guidelines, CLM 2 guidelines were announced in 2020. CLM 2 guidelines announced in 2020, it allowed Banks and NBFCs to enter into arrangements, where the co-lending can happen post the disbursement, i.e., months or in some cases years after the disbursement. This allowed the entire process to be done post the actual disbursement of the loans, giving greater flexibility to the participating entities. CLM 1 requires the entities to give their credit decisioning in real time. The money for disbursement would be pooled in an escrow account, and all disbursements and collections would be routed through that account. In case where 100% money is being funded by the funder, the entire disbursement and collection would be routed through that REs account. 💡Setting interest rates for CLM loans Given that CLM 1 is the only allowed co-lending model now, the interest rate offered to the customer must be a blended rate between the two REs involved in co-lending. Specifically, the rate to be offered for CLM loans is a mixture of the rates set by the two REs. It is defined as: CLM Rate = CLM Ratio Funder Rate + (1 - CLM Ratio) Sourcing Rate This puts an upper cap on the maximum rate, which can be offered during CLM. As required by the regulations, each RE would have a maximum interest rate, at which they can lend, approved by their board. Max CLM Rate <= CLM Ratio Max Funder Rate + (1 - CLM Ratio) Max Sourcing Rate

1️⃣  Featured Insight - Changes in Microfinance Lending MFIN (Microfinance Institutions Network) is a Self-Regulatory Organization (SRO) for the microfinance industry in India. It primarily represents NBFC-MFIs (Non-Banking Financial Company - Microfinance Institutions) and works to ensure responsible lending practices, regulatory compliance, and industry growth. MFIN collaborates with the Reserve Bank of India (RBI) and other stakeholders to maintain transparency and protect borrower interests in the microfinance sector. Typically, all institutions involved in microfinance lending, follow these guidelines. MFIN has released new guidelines as of January 2025. Here, is all you need to know about the guidelines. 💡What are Microfinance loans? Microfinance loans are uncollateralized loans which are given to households with annual income up to 3 lakhs. To ensure accuracy of the same, microfinance lenders are required to submit the same to credit information companies every month. The income is used to ensure that the total obligations for the customer do not exceed 50% of their income. This includes all loans, not just microfinance loans. To estimate the monthly obligations, for non EMI products, specific multipliers are given, 1-1.5% for gold loans, 5% for credit cards, 1% for kisan credit cards. For the rest of loan types, by loan amount bucket, the minimum EMI estimations are recommended by MFIN. 💡Bureau reporting of microfinance loans. UCRF based credit reporting is a must. The primary method of KYC must be voter id card. All KYC information should be picked from voter id card, post verification from election commission. Weekly submission for account status changes, new loans disbursed, account closures, account number changes. Ideally, this should be done daily. Monthly submission for the full data in the UCRF format. New loans must be disbursed within 15 days of the credit report getting pulled. 💡Cross selling products Only life insurance can be bundled along with the loan product. If there is a demise of the borrower during the loan, then only the outstanding loan amount goes to the lender, rest of the amount must go to the family members / nominee. Any other cross selling of other products, can only be done after one month of disbursement of the loan. Even the processing fees should not exceed 1.5% of the loan amount.  APR must include interest rate, processing fees and life insurance only, no other charge can be deducted at time of disbursement. 💡Underwriting guidelines The maximum number of possible MFI lenders has been reduced from 4 to 3. This is effective from April 2025. The maximum indebtedness, including the proposed loan, of the borrower should not exceed 2 lakh rupees. This includes both microfinance loans and unsecured retail loans. Earlier the limit was only on microfinance loans, and not on unsecured retail loans. Any customer having a DPD of more than 60 days (earlier this limit was 90 days), with an outstanding balance more than 3000 should be rejected. With these new guidelines, expect that the MFI portfolio of the country will improve in credit quality, while this may cause a slowdown in the sector in the short term. 2️⃣  Industry News Roundup 🗓️ Spinny raises $131 million to expand NBFC arm. [ Reference ] 🗓️ Bank credit growth has been slowing down, and is down to 12% from a peak of ~17% [ Reference ] 3️⃣  Stats of the week 📊Loan against gold jewellery and loan for renewable energy are the biggest sub sectors which are showing the maximum growth in the lending sector. Loan against gold jewellery grew by 87% year over year, while loan for renewable energy grew by 45%.

1️⃣  Featured Insight - Asset Liability Management & Reporting Managing liquidity risk is one of the most critical aspects of running a financial institution. Banks and Non-Banking Financial Companies (NBFCs) are required to comply with stringent guidelines to ensure their liquidity position remains stable. In India, NBFCs with an asset size of more than ₹100 crore must adhere to regulatory norms for liquidity risk management to safeguard against potential financial instability. 💡Understanding Liquidity Risk in Financial Institutions The core business model of financial institutions revolves around borrowing money from lenders (such as depositors, banks, or bond markets) and lending that money to their own customers at a higher interest rate. While this generates profits, it also exposes financial institutions to liquidity risks. Liquidity risk refers to the possibility that a financial institution might not have enough cash or liquid assets to meet its short-term financial obligations, including loan repayments to creditors, operational expenses, and withdrawal requests from depositors. A common liquidity challenge faced by NBFCs and banks is asset-liability mismatch. Many financial institutions borrow funds for short durations, such as 1 to 2 years, but lend them out for longer periods, such as 5 to 10 years. This creates a risk where the institution needs to repay its obligations before receiving repayments from its own borrowers, potentially leading to cash flow gaps and financial distress. 💡ALM Reporting To effectively manage liquidity risk, financial institutions must maintain structured asset-liability ledgers. ALM reporting involves classifying both inflows (loan repayments from customers) and outflows (loan repayments to lenders) into different time buckets based on their tenure. For every loan disbursed, financial institutions must determine when it is expected to be repaid and classify it into appropriate buckets based on tenor. Similarly, all loans borrowed by the financial institution must be categorized based on their repayment schedule. To ensure liquidity stability, financial institutions should ideally have more inflows than outflows in the short-term buckets, particularly in the next one-month and up-to-one-year tenors. However, in longer tenors, mismatches may arise due to extended loan durations. Beyond individual time buckets, cumulative mismatches must be monitored to assess the overall liquidity health of the financial institution. A significant mismatch in near-term buckets can indicate potential liquidity distress and the need for corrective actions. 💡How to Classify Inflows in ALM Reporting? The classification of cash inflows is crucial in ALM reporting, as it helps determine liquidity availability in different time frames. The key principles for classifying inflows include: 1. Standard Loan Accounts (Non-NPA Loans) If a loan is standard (i.e., performing well) and has no overdue payments, its principal repayment is bucketed based on the original repayment schedule. If the loan has an overdue of less than one month, it is classified into the 3 to 6-month bucket and subsequent buckets. If the loan is overdue for up to 3 months, the entire outstanding amount is placed in the 1 to 3-year bucket and further buckets. 2. Non-Performing Assets (NPA) Loans NPA loans require careful classification to avoid overestimating inflows: The provision-adjusted principal amount can be considered as an inflow. Any amounts due (including current overdues) within the next three years should be placed in the 3 to 5-year bucket. Amounts due beyond three years must be placed in the over 5-year bucket. 3. Doubtful and Loss Accounts Loans classified as doubtful or loss-making should be placed entirely in the over 5-year bucket, as recoverability is uncertain. Liquidity risk management is essential for ensuring the financial stability of banks and NBFCs. By following a structured ALM framework and regulatory guidelines, financial institutions can proactively manage cash flow mismatches, maintain healthy liquidity, and prevent financial distress. Regulatory compliance, strategic borrowing, and prudent loan structuring play a crucial role in safeguarding financial institutions against liquidity risks. Financial institutions must continually monitor liquidity gaps, implement corrective measures, and align their lending and borrowing strategies to maintain financial health and sustainability in the long run. 2️⃣  Industry News Roundup 🗓️ RBI imposes ₹76.6 lakh fine on four P2P NBFCs after their audit. [ Reference ] 🗓️ IndusInd Bank’s net worth took a hit of 2.35% over discrepancies found in accounting of their derivatives portfolio. [ Reference ] 3️⃣  Stats of the week 📊Overall Credit disbursement to Priority Sectors Jumps 85% from ₹23 Lakh Crores in 2019 to ₹42.7 Lakh Crores in 2024 [ Reference ] Want to get weekly content regarding new developments in banking technology? Subscribe to our newsletter  here . Are you a CXO at a bank / NBFC / fintech company interested in upgrading your technology? We would love to show you a demo of the OneFin offering. We provide end to end capabilities including configurable modules like LOS, LMS, Accounting System, Collection System, Digital Journeys etc. Schedule a Demo  here .

Why Penny Drop Bank Account Verification is Essential for Secure and Efficient Transactions For any digital lending system or Loan Origination System (LOS), verifying bank account details before processing transactions is crucial.  Penny Drop Verification  has emerged as an efficient solution that ensures accuracy, enhances security, and improves user experience. This article highlights the key benefits of Penny Drop Verification and why businesses should adopt this method for seamless financial operations. What is Penny Drop Bank Account Verification? Simply put, it is a process where lender automatically transfer Re 1 to customer’s bank account as per bank details provided by customer. In return, the lender gets to know if the account is operational and also comes to know the customer name in the bank records. Bank Account Verification in OneFin Customer Journey / Loan Origination System (LOS) Benefits of Penny Drop Bank Account Verification 1. Eliminates Transaction Failures and Errors One of the biggest challenges businesses face while processing payouts or refunds is incorrect bank details.  Penny Drop Verification ensures that the bank account is active and capable of receiving funds , reducing the risk of transaction failures. By verifying the account holder’s name, businesses can avoid costly errors and incorrect transfers. 2. Enhances Fraud Prevention and Security With the increasing threat of identity fraud, validating the authenticity of bank account details is more important than ever. Penny Drop Verification  cross-checks the beneficiary's details with the bank, ensuring that funds are only transferred to legitimate users .  This helps lenders prevent fraudulent transactions and unauthorized payouts. The Name as per bank records must be matched with name as per PAN or Aadhaar i.e the name in the loan account in the Loan Origination System (LOS).  3. Improves Compliance with Regulatory Standards Financial institutions and businesses must comply with  Know Your Customer (KYC) and Anti-Money Laundering (AML) regulations . Penny Drop Verification acts as a compliance tool by ensuring that the bank details provided belong to the actual beneficiary, helping companies stay in line with financial regulations and avoid penalties. 4. Reduces Operational Costs Handling failed transactions and refunds due to incorrect bank details can be expensive.  By verifying accounts upfront, businesses save time and money by avoiding reversals, chargebacks, and manual corrections . Automating this verification process further reduces the need for manual intervention, cutting down administrative overhead. Name Matching Once the name as per bank record is received as part of penny drop verification, it has to be matched with other records. Match bank name with KYC name - match name on the bank account with name as per PAN or Aadhaar based KYC. A name matching threshold can by put to prevent false rejections. A commonly used threshold is around 75%. In case there are co-applicants, the name match should be run against all co-applicants because the bank details could be of an earning member applicant who may not be the main applicant.  While matching name, prefixes like Mr, Mrs, M/S should be stripped off before checking the match %. Otherwise it may reduce the match % even if the names are the same. Conclusion Penny Drop Verification is not just a simple authentication step—it is a  critical component of secure, efficient, and compliant financial transactions . By eliminating errors, preventing fraud, and enhancing the customer experience, this method offers  substantial benefits for lenders . 2️⃣  Industry News Roundup 🗓️ Education finance startup Kuhoo Finance gets NBFC licence [ Reference ] 🗓️ India’s biggest lender SBI to set up AI, fintech project finance unit [ Reference ] 🗓️ MSME Fintech Progcap to empower 10,000 women led MSMEs over the next 3 years [ Reference ] 3️⃣  Stats of the week 📊 Rs 45000 crore+ disbursements were facilitated in H1 of FY25-26 via Account Aggregator framework [ Reference ] Want to get weekly content regarding new developments in banking technology? Subscribe to our newsletter  here . Are you a CXO at a bank / NBFC / fintech company interested in upgrading your technology? We would love to show you a demo of the OneFin offering. We provide end to end capabilities including configurable modules like LOS, LMS, Accounting System, Collection System, Digital Journeys etc. Schedule a Demo  here . Penny Drop Bank Account Verification | Kuhoo Gets NBFC License & More

1️⃣ Featured Insight -  CERSAI's New CKYC Compliance Rules: Unique IPs, Masked CKYC Numbers & API Changes CERSAI (Central Registry of Securitisation Asse t Reconstruction and Security Interest of India) has been doing a lot of regulatory changes in its process over the last few months. Here is everything you need to know about them: 💡Unique IP requirement Each Reporting Entity (RE) must use a unique IP address for CKYC Search and download API and SFTP access. Ensure that you are using a dedicated IP for accessing CKYC, else your API accesses might have been blocked. Go for solutions which can deploy on your cloud / on-premise services, so that you are able to seamlessly access CKYC services.  💡Masking of CKYC number in search API response Earlier the full unmasked CKYC number was available in the response of the CKYC search API. Now, the CKYC number which comes in the API would be masked, i.e., only the last four digits of the CKYC number of the customer will be available after searching Instead of the unmasked CKYC number, the API would return a CKYC reference number. The CKYC reference number can be passed into the download API to download the KYC documents. If the CKYC download API call is successful, then you will get the full CKYC number as a response. Since CKYC search is free and the download API has a cost, there may be some extra cost implications for the RE. 💡How exactly CKYC Download is different from CKYC search? CKYC download takes two inputs: The CKYC number tag may be used to provide either the CKYC number (14-digit numeric value) or CKYC Reference ID (14- digit alphanumeric value. Authentication factor of either Date of Birth or Pincode & Year of Birth or the mobile number. A fallback mechanism must be created to do a download using all the three options, so that maximum coverage can be achieved. 2️⃣ Industry News Roundup 🗓️ RBI imposes fines to four P2P lending NBFCs. [ Reference ] 🗓️ RBI discourages NBFCs from giving perpetual credit lines to borrowers.Clarifies this is a domain of banks. [ Reference ] 3️⃣ Stats of the week 📊 In the fiscal year 2024, 63% of loans granted to the power sector originated from the three largest Infrastructure Financing Companies, a category of NBFC. This finding was highlighted in the International Monetary Fund's report, "India Financial System Stability Assessment." Want to get weekly content regarding new developments in banking technology? Subscribe to our newsletter  here . Are you a CXO at a bank / NBFC / fintech company interested in upgrading your technology? We would love to show you a demo of the OneFin offering. We provide end to end capabilities including configurable modules like LOS, LMS, Accounting System, Collection System, Digital Journeys etc. Schedule a Demo  here . #banking #bfsi #fintech #nbfc #los #lms