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AI Ab Chatbots se aage, Fintech ke Main Kaam Sambhalega!
India ki Fintech companies AI ko deep integrate kar rahi hain. Pehle jo AI sirf customer ko interact karne ke liye tha, jaise chatbots, ab woh underwriting, advanced fraud detection, KYC, debt collection, customer support aur compliance monitoring jaise critical backend operations mein bhi ja raha hai. Engineering workflows aur internal productivity ko improve karne mein bhi AI ka role badh raha hai.
Yeh AI adoption badhne ka sabse bada reason hai digital transactions ka massive growth. Sirf March mein India mein 22.64 billion se zyada UPI transactions hue, itna volume hai ki manual oversight mushkil ho gaya hai. "AI ab experimentation stage se nikal kar hamare operational aur technology framework ka ek gehra hissa ban gaya hai," aisa kaha hai Rohit Mahajan, CEO of Plutos ONE ne, jinki company AI ko compliance, onboarding aur operational support ke liye use karti hai.
Advanced Fraud Se Ladne Ke Liye AI
Naye generative AI tools se sophisticated phishing aur scam attempts ho rahe hain, jo existing fraud detection systems ke liye challenge hain. Ek study mein pata chala ki zyadaatar Indian organizations ko lagta hai ki current KYC systems AI-generated fake documents ke saamne kamzor hain, aur GenAI fraud ka ek bada threat hai. Payment provider PayU real-time fraud monitoring ke liye AI use karta hai. "Payment fraud machine speed se hota hai," batate hain Manas Mishra, Chief Product Officer at PayU and Wibmo. "Real-time monitoring layer ab zyadaतर AI-led hai, lekin governance, investigations, regulatory judgement aur complex escalations ke liye human expertise bahut zaruri hai." PayU ka AI constant monitoring aur pattern recognition karta hai, jabki human teams strategic investigations par focus karti hain.
Profitability Ke Liye AI Adoption
Funding kam hone aur market ki scrutiny badhne ke saath, fintechs AI ke through operational efficiencies aur cost reduction dhoondh rahe hain. Gaurav Gupta, Senior Vice-President at Payoneer, ne bataya ki AI product development, R&D, customer support, compliance aur growth mein deeply integrated hai. "Execution layer kaam karne ka tareeka badal raha hai, jisme AI workflow ka zyada hissa handle kar raha hai aur humans supervise kar rahe hain aur zarurat padne par final calls le rahe hain," unhone samjhaya. Jabki AI firms ko headcount increase ke proportional bina scale karne mein madad karta hai, experts kehte hain ki yeh sirf cost-cutting ka tareeka nahi hai. "Cost reduction ka strong evidence hai un areas mein jahan AI experimentation se aage badh gaya hai," aisa kaha Vijay Mani, Partner at Deloitte India ne.
AI Se Lending, Support Aur Engineering Ko Boost
Lending aur underwriting AI ke liye key areas hain. Fintech lenders credit assessment, behavioral scoring aur real-time risk monitoring ke liye alternative data use kar rahe hain. Reserve Bank of India (RBI) Governor ne banks ko customer grievance handling behtar karne ke liye AI use karne ko encourage kiya hai, jisse multilingual AI support aur conversational interfaces aa rahe hain. PayU initial merchant queries ke 30-40% ke liye AI-assisted systems use karta hai. Technology teams bhi development speed up karne ke liye AI coding assistants aur automated testing adopt kar rahe hain.
Governance Aur Accountability Ke Challenges Abhi Bhi Hain
Rapid adoption ke bawajood, AI governance aur accountability mein challenges hain. Lending mein explainability, bias aur AI hallucinations jaise issues finance mein major concerns hain. "PayU mein, responsible automation, full automation se zyada important hai," aisa Mishra ne kaha. "Money movement, regulatory compliance, sensitive data aur customer protection se jude areas mein human oversight continue rehna chahiye." Deloitte ke Mani ne add kiya ki true AI impact processes ko AI ko dhyan mein rakh kar redesign karne se aayega, jo governance ke saath balance ho. Bade platforms ko zyada data ke karan edge mil sakta hai, lekin sirf AI se solid business fundamentals ki jagah nahi le sakte.