Razorpay Targets Profitability Ahead of IPO
Hey Payments Fanatic!
Razorpay is setting its sights on profitability as it prepares for a potential IPO within the next three years. While the company’s core payments business is already in the black, its broader operations, including neo-banking and lending services, are still working toward breaking even. “We’re 2-3 years away from IPO,” said Shashank Kumar, co-founder and managing director of Razorpay.
The India-based FinTech, last valued at $7.5 billion in 2021, reported a 360% surge in net income to $4 million for the fiscal year ending March 2024. The growth was largely driven by its payment gateway segment, which continues to be its primary revenue engine.
Looking ahead, Razorpay is expanding beyond India, recently launching in Singapore and planning future rollouts in Thailand, Vietnam, the Philippines, and the Middle East.
With $741.5 million raised from investors including GIC, Tiger Global, and Y Combinator, the company is navigating the path to sustainable growth while positioning itself for public markets.
If you’re interested in reading a bit about what’s been happening in Payments, keep scrolling!
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GOLDEN NUGGET
?????? ???? ?????????????????? ?????????? ???? ??????????????-????-?????????????? ???????????????? (#A2A)??
?????? ?????????????? ???? ??2?? ????????????????:
? Account-to-Account (A2A) payments are rapidly growing, with a forecasted 161% growth between 2024 and 2028.
? The fundamental characteristics of Real-Time Payments (RTP), such as speed, 24/7 availability, irrevocability, and lack of network visibility, contribute to the increasing fraud risks.
? Fraud is evolving with the growth of A2A payments, making it crucial for financial institutions to implement real-time fraud prevention strategies.
?????? ???? ???? ???????????????????? ?????????????????? ???? ?????????? ?????????????????????
? ?????????? ?????? ????????????????: AI enables real-time fraud detection and prevention, essential for instant payment transactions that are completed within 10 seconds.
? ?????????????? ??????????????????????: AI can recognize patterns and detect irregularities, linked to mule accounts or changed geolocation.
? ???????????????? ????????????????: AI models adjust to new fraud trends in real-time, unlike traditional rules-based systems that require post-loss analysis.
? ?????????????? ?????????? ??????????????????: AI-enhanced systems provide more accurate fraud detection, reducing the need for manual reviews and minimizing false positives.
? ??????????????-?????????? ????????????????????: AI leverages a multi-financial institution (FI) view, enabling a comprehensive view of fraud across payment networks, which is crucial for detecting cross-network fraud schemes.
??????????-?????????? vs. ????-???????????????? ??????????????:
??????????-?????????? ????????????:
1?? Transaction Initiated
2?? Massive Volume of Transactions: High volume of transactions are flagged for manual review due to basic rule triggers.
3?? Manual Review: Transactions are manually reviewed, leading to delays and operational inefficiencies.
4?? Transaction Assessed: Risk is evaluated based on pre-set rules.
5?? Transaction Authorized: If no rule is violated, the payment is authorized.
????????????????????: High false positives, time-consuming manual reviews, and delays in payment processing.
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????-???????????????? ????????????:
1?? Transaction Initiated
2?? Curated Volume of Transactions: AI intelligently filters transactions, reducing the volume that requires review.
3?? AI-Assisted Review: Transactions are reviewed with AI input, providing real-time risk assessment.
4?? Data & Model Assessment: AI evaluates transactions using data patterns and predictive models.
5?? Transaction Authorized: If deemed low-risk, the payment is instantly authorized.
????????????????: Reduced false positives, real-time risk assessment, operational efficiency, and improved customer experience.
Source: Visa
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