OnEMI Technology Solutions Limited, known as Kissht, is a technology-enabled lender in India, primarily offering digital loans through its mobile application for various consumption and business needs. They provide swift, accessible and personalized credit solutions to support the customers throughout their financial journeys. They are focused on young individuals within the mass market segment. As of December 31, 2025, they had 63.73 million registered users and served 11.17 million customers, along with a net promoter score of 95. Further, they had received a rating of 4.6 on Play Store based on over 1.25 million user reviews as of March 31, 2026. In December 2025, they also launched the mobile application on the iOS operating system and its application marketplace. Company maintains a highly granular loan book with over 2.87 million active customers and Rs 59,557.53 million in assets under management ('AUM') as of December 31, 2025. In the nine months ended December 31, 2025, the customers had an average age of 32 years and a median CIBIL score of 746. Further, during the nine months ended December 31, 2025, 67.65% of the customers earned monthly incomes ranging between Rs 25,000 to Rs 75,000, and 63.38% of the customers resided in the top 50 cities in India. Company uses various online and offline channels to acquire customers, including through digital marketing on search engines and social media platforms, partnerships with small businesses (shop owners and retail outlets), and collaborations with e-commerce players and loan aggregators. They also acquire customers organically through word of mouth. Each channel significantly contributes to the growth of the customer base, thereby creating a resilient and scalable customer acquisition model. In the nine months ended December 31, 2025, digital marketing, merchant partnerships, e-commerce and organic acquisition accounted for 45.51%, 23.28%, 7.51% and 23.70%, respectively, of the total new customer acquisitions in the same period. Risk management is foundational to the business model. They utilize advanced data analytics, artificial intelligence (“AI”) and machine learning (“ML”) led statistical models for risk management across the processes from making credit decisions to collections. Set out below are the details of the three key pillars of our risk management function. Underwriting models : The proprietary AI and ML algorithms utilize over 400 key data variables as of December 31, 2025 including credit history, know-your-customer ('KYC') credentials, banking and transactional data and digi-data, within a secure and consent-driven environment, to enable rapid and accurate decisioning. As of December 31, 2025, they have employed a sophisticated underwriting framework built on 39 specialized sub-models tailored for different customer segments. These sub-models factor in multiple dimensions of a customer’s profile such as occupation type (e.g., salaried or self-employed), credit bureau data depth (e.g., thick or thin file) and banking behavior (e.g., high balance maintainers or frequent transactors), among others. The outputs from these sub-models are generated through a transformer and table attention-based decision model that determines loan approval outcomes. Further, the models are capable of estimating customer income with high precision using banking and transaction data. As of December 31, 2025, more than 85% of the new customers were presented with loan offers within 10 minutes of initiating their application, and 90% of the repeat customers received offers within six minutes. Collections : The collections infrastructure is built on the back of the proprietary Automated Collections System ('ACS'), along with a team of tele-callers and on-ground fleet-on-street. The ACS is an AI-driven platform that effectively manages collections across pre-delinquency, early delinquency and late delinquency stages, thus improving recovery outcomes. As of December 31, 2025, the collections team comprises 1,074 tele-callers, 8,291 field agents and 260 supervision staff covering over 17,000 pin codes across India. Automated system-based early warning triggers to identify high-risk customers : They actively manage the portfolio through early warning triggers that automatically curb approvals when pre-defined risk thresholds are breached. For instance, the system temporarily halts disbursements in geographies that witness sudden volume surges; they also tighten the approval thresholds for customer segments or professions showing signs of overleverage or income fluctuation. They operate a fully tech-enabled, highly scalable, cloud-hosted lending platform, with end-to-end ownership and control of product and technology. This includes the Loan Origination System ('LOS'), Loan Management System ('LMS') and ACS. The platform manages the entire loan lifecycle, i.e., from customer onboarding to underwriting, disbursement, servicing and collections, ensuring a secure and seamless experience for the customers. The AUM comprises on-book loans, i.e., loans on the balance sheet of the wholly-owned Subsidiary, Si Creva (an RBI regulated middle-layer NBFC), and off-book loans, i.e., loans on the balance sheet of the lending partners. They engage with the lending partners through three distinct arrangements, being through 100-0 arrangement pursuant to which they act as a sourcing and technology partner, co-lending arrangement and direct assignments ('DA'). The revenue from off-book loans includes sourcing fees (representing charges for originating loans through the platform), servicing fees (representing charges for managing loan servicing and collections) and other performance-linked income (representing charges based on loan performance metrics). These fees and charges are calculated in accordance with pre-agreed contractual arrangements with the lending partners and in compliance with applicable RBI regulations. As per financial performance, OnEMI Technology Solutions Limited has posted total income / net profits of Rs 1,001.50 Cr / Rs 27.66 Cr (FY23), Rs 1,700.30 Cr / Rs 197.29 Cr (FY24), Rs 1,352.68 Cr / 160.62 Cr (FY25) and Rs 1,583.92 Cr / 199.26 Cr (upto Q3 FY26). So as per previous financials data, company has shown steady results, but increase in NPA is a concern. GNPA is 0.05%, 0.79%, 2.89% and 2.90% for the years FY23, FY24, FY25 and 9M FY26. Company has an average EPS of Rs 11.99 and average RoNW of 19.62% for last three fiscals. Issue is priced at a P/BV of 0.74 as per NAV of Rs 231.84/- as on 31.12.25. If we attribute latest earnings of FY24, FY25 and annualised FY26 on equity post issue, then asking price is at a P/E of around 14.60, 17.94 and 10.84 respectively. As per RHP, comparison between listed peers are shown in the above market. On BRLM's front, JM Financial Limited, HSBC Securities and Capital Markets (India) Private Limited, Nuvama Wealth Management Limited, SBI Capital Markets Limited, Centrum Broking Limited are associated with this IPO, and has handled 108 IPOs in last three fiscal years. ( As on 27.04.26 ) As per financials, OnEMI Technology Solutions Limited has shown steady growth, RoNW is 17.74% and P/E is 14.60, 17.94 and 10.84 respectively as per FY24, FY25 and annualised FY26 earnings. So issue looks fully priced and higher GNPA is a concern, but P/B ratio is 0.74. Company is a technology-enabled lender in India, primarily offering digital loans through its mobile application for various consumption and business needs, which is highly competitive business segment. So, we give NEUTRAL rating for this IPO. Readers must consult a qualified financial advisor prior to making any actual investment decisions.
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