Razorpay, India’s leading omnichannel payments, and business banking platform, announced the launch of its AI assistant, ‘RAY,’ at the 5th edition of FTX, its flagship event. The introduction of RAY signifies Razorpay’s venture into leveraging artificial intelligence to simplify financial processes for businesses. The company claims RAY to be the first-of-its-kind in India, marking a significant step in innovating fintech solutions.
Current Challenges in AI for Finance
Challenges in Content Quality
When Gen AI and similar technologies don’t meet compliance standards, regulators worry about content accuracy. Gen AI has faced criticism for generating convincing but inaccurate responses, leading to concerns about misinformation consequences, such as in a case involving Tesla’s financial data. To make Gen AI a valuable tool, emphasising accurate content in training data is important. Regulators grapple with balancing customer convenience, broader considerations, and addressing biases from biased training data, as seen in instances like Amazon’s recruiting algorithm and Apple Card’s gender-based discrimination.
Concerns About Opaque Models and Pricing Transparency
Regulators are troubled by the opaque nature of proprietary models, especially when outcomes can’t be explained, a challenge given the iterative nature of GNI. This becomes critical for pricing transparency, illustrated by a past financial scandal involving mispriced derivatives. The inability to explain pricing methods raises concerns, particularly in India, where the Reserve Bank emphasises customer protection.
Data Privacy Challenges and Global Segmentation
Data privacy is another concern, with advanced tools making detection difficult and illicit actors engaging in deception. The complexity deepens as data gets segmented across countries with different protection laws. Affordability and accessibility of AI-driven jobs further complicate matters. Establishing ethical standards for AI in finance becomes a significant challenge for regulators and governments, reminiscent of the complexities faced in regulating cryptocurrency.
Proposed Solutions
Collaborative Approach with Regulators
Addressing these challenges requires industry collaboration with regulators, echoing the complex nature of AI regulation. Ongoing discussions provide an opportunity for the Indian AI industry to engage with regulators and formulate effective outcomes. The Reserve Bank has initiated discussions, emphasising key concerns in a recent talk on AI and Gen AI.
Primary Concerns Identified by the Reserve Bank
The Reserve Bank identifies three primary concerns in the use of AI in Generation: data bias, transparency, and governance. Transparency, including clarity and consistency, is crucial to avoiding disparate outcomes for similar cases. Governance raises questions about autonomous decision-making, proposing the possibility of human intervention, although this may impact efficiency.
Envisioning a Future Powered by Generative AI
Looking ahead, the vision is a financial sector powered by Generative AI, where employees focus on high-quality tasks, regulators use sophisticated tools for tailored supervision, and customers experience delightful, hassle-free interactions. The dynamic nature of technological advancements prompts questions about readiness and emphasises the need for responsible and ethical AI use. As we progress, staying informed and guiding technology usage appropriately becomes imperative.
About Razorpay’s RAY:
Razorpay’s new AI-assistant, RAY, powered by the company’s AI-Nucleus, is a comprehensive solution designed to offer seamless assistance in various financial operations, including payments, payouts, payroll, vendor payments, and more. RAY stands out as a versatile tool capable of understanding and resolving complex queries with plans to expand to regional languages.
In real-world scenarios, RAY emerges as a dynamic problem solver. For instance, in cases of delayed settlements due to a bank holiday, RAY not only informs but takes proactive steps to expedite the process, showcasing its commitment to prompt assistance. Similarly, when confronted with a failed payment, RAY identifies the issue and suggests practical solutions to recover lost customers.
At Razorpay, every innovation revolves around you-the business owner, entrepreneur, founder, disruptor. Our commitment to addressing your challenges is evident in products like RAY, crafted to empower and support you on your entrepreneurial journey.
Key Features of RAY:
1. RAY goes beyond information provision, it actively helps in scenarios such as delayed settlements due to holidays, ensuring a proactive approach to financial management.
2. In cases of failed payments, RAY not only identifies the issue but also suggests practical solutions, aiding in the recovery of lost customers.
3. RAY simplifies technical tasks by generating integration codes for websites, reducing the need for manual coding efforts. Businesses can instruct RAY with requests like, “Please generate an integration code for my website in Python,” and RAY promptly generates and displays the required code.
4. While currently available in English and Hindi, RAY aims to cater to a wider audience by introducing support for regional languages.
RAY: Functionality
Imagine an e-commerce entrepreneur like Ramesh facing a delayed settlement. RAY not only informs him about the bank holiday but takes a step further, proactively facilitating an immediate settlement increase. In another scenario, where Ramesh experiences a decline in customers due to payment failures, RAY not only identifies the issue but prompts him to re-engage customers through a payment link.
Harshil Mathur, CEO & Co-Founder of Razorpay, expressed his excitement about the transformative potential of RAY. “Today, we are also India’s First Fintech to have developed an AI-Assistant designed for e-commerce businesses, one that promises to resolve all things Payments, Payouts, Payroll, Vendor payments, and much more. We at Razorpay are changing every known paradigm of money movement for disruptive businesses. I believe we are not stepping into the future. We are creating it,” he said in a press release.
Shashank Kumar, MD & Co-founder, of Razorpay said, “We are heavily leveraging the true power of AI in our products, right from chargeback protection to RTO fraud detection to DoclessAI integration that enables businesses to go live in just 10 minutes, Razorpay is all in for AI.” “We will empower large retail stores to accept UPI payments through QR codes as their primary payment method because that’s what India is moving towards. We are truly excited for businesses to experience them in action and slingshot their way through their growth journeys,” he added.
Razorpay looks back on its remarkable 9-year journey as it gears up for the next phase of growth. The brand has been a leader and pioneer in digital payments and financial technology, setting industry standards along the way. Looking forward, the vision of a financial sector powered by Generative AI offers a glimpse into a future where tasks are streamlined, regulators employ sophisticated tools, and customers enjoy seamless interactions. Razorpay’s RAY stands out as a dynamic problem solver, addressing real-world scenarios with proactive assistance.
