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Business Standard
a day ago
- Business
- Business Standard
RBI, banks to launch DPIP platform to combat rising digital payment frauds
In a bid to rein in the increasing incidence of digital payment frauds, major public and private sector banks have been roped to develop Digital Payment Intelligence Platform (DPIP) as a Digital Public Infrastructure (DPI) under the supervision and guidance of the RBI. The proposed platform seeks to bolster fraud risk management by facilitating real-time intelligence sharing and gathering, thereby preventing fraudulent digital transactions, sources said. According to sources, the institutional structure of the proposed entity would be created with the help of both public sector and private sector lenders as fraud is a common monster. Earlier this month, a high-level meeting in this regard was convened to finalise the structure of the platform where senior bank officials, RBI officials and other stakeholders were present. Since the issue is one of the top agenda for both the government and the Reserve Bank of India (RBI), sources said the platform should become operational in the next few months. Once operational, DPIP will collect and analyse data from various sources to identify potential threats and prevent fraudulent activities. By enabling real-time data sharing, the platform will help prevent scams and ensure secure transactions. Reserve Bank Innovation Hub (RBIH) has been assigned for building a prototype of DPIP in consultation with 5-10 banks. It is going to leverage advanced technologies to curb payment-related frauds. RBI, in June last year, formed a committee, chaired by A P Hota, former MD & CEO of NPCI, to examine various aspects of establishing this digital public infrastructure. According to the latest annual report of the RBI, there has been a significant surge in bank frauds, with the amount involved rising nearly three times to Rs 36,014 crore in FY25, compared to Rs 12,230 crore in the previous year. Of this, as much as Rs 25,667 crore worth of frauds were reported by public sector banks as against Rs 9,254 crore a year ago. Frauds have occurred predominantly in the category of digital payments (card/internet) in terms of the number and primarily in the loan portfolio (advances) in terms of value, it said. While card/internet frauds contributed maximum to the number of frauds reported by private sector banks, frauds in public sector banks were mainly in advances, it said.
Time of India
a day ago
- Business
- Time of India
RBI-led initiative to curb digital frauds gains momentum, banks roped in to set up DPIP
In a bid to rein in the increasing incidence of digital payment frauds , major public and private sector banks have been roped to develop Digital Payment Intelligence Platform (DPIP) as a Digital Public Infrastructure (DPI) under the supervision and guidance of the RBI . The proposed platform seeks to bolster fraud risk management by facilitating real-time intelligence sharing and gathering, thereby preventing fraudulent digital transactions, sources said. According to sources, the institutional structure of the proposed entity would be created with the help of both public sector and private sector lenders as fraud is a common monster. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Play War Thunder now for free War Thunder Play Now Earlier this month, a high-level meeting in this regard was convened to finalise the structure of the platform where senior bank officials, RBI officials and other stakeholders were present. Since the issue is one of the top agenda for both the government and the Reserve Bank of India (RBI), sources said the platform should become operational in the next few months. Live Events Once operational, DPIP will collect and analyse data from various sources to identify potential threats and prevent fraudulent activities. By enabling real-time data sharing, the platform will help prevent scams and ensure secure transactions. Reserve Bank Innovation Hub (RBIH) has been assigned for building a prototype of DPIP in consultation with 5-10 banks. It is going to leverage advanced technologies to curb payment-related frauds. RBI, in June last year, formed a committee, chaired by A P Hota, former MD & CEO of NPCI , to examine various aspects of establishing this digital public infrastructure. According to the latest annual report of the RBI, there has been a significant surge in bank frauds, with the amount involved rising nearly three times to Rs 36,014 crore in FY25, compared to Rs 12,230 crore in the previous year. Of this, as much as Rs 25,667 crore worth of frauds were reported by public sector banks as against Rs 9,254 crore a year ago. Frauds have occurred predominantly in the category of digital payments (card/internet) in terms of the number and primarily in the loan portfolio (advances) in terms of value, it said. While card/internet frauds contributed maximum to the number of frauds reported by private sector banks, frauds in public sector banks were mainly in advances, it said.
India Gazette
5 days ago
- Business
- India Gazette
"India is ahead of world in digital payments," says FM Sitharaman
New Delhi [India], June 18 (ANI): At the Digital Payment Award distribution ceremony held in the national capital, Union Minister for Finance & Corporate Affairs Nirmala Sitharaman hailed India's extraordinary achievements in digital payments and financial technology, noting that the country is now leading the world in real-time digital transactions. 'In terms of digital payments, India is not just catching up -- it is ahead of the world,' she declared, as the audience of innovators, policymakers, and industry leaders applauded. 'The pace of innovation we are witnessing in India is a dream for many developed nations.' Minister Sitharaman emphasised that India's fintech sector is not only progressing rapidly within its own ecosystem but is also redefining global paradigms. 'Several advanced countries are nowhere close to the kind of momentum our fintech companies have achieved. What is happening in India is unique -- a bold reimagination of financial infrastructure,' she noted. Quoting a World Bank study, the Minister highlighted that India's focus on Digital Public Infrastructure (DPI) has helped the nation reach 80 per cent financial inclusion in just six years -- a feat experts estimate would have otherwise taken five decades. 'With 48.5 per cent of all real-time digital payment transactions in the world now originating from India, the impact is global. The UPI ecosystem alone now connects over 35 crore users, becoming the backbone of digital payments in the country. 'During the COVID-19 pandemic, payment apps became lifelines, enabling contactless transactions and doorstep banking -- keeping the economy moving while mobility was restricted,' Sitharaman reflected. According to the Reserve Bank of India, the Digital Payments Index, a benchmark for the adoption of digital transactions, has quadrupled from 100 in 2018 to 465 in 2024. 'Our Prime Minister Narendra Modi, has always emphasised that we must not only 'Make in India', but also 'Make for the world',' the Minister said. 'In this context, India's fintech innovations are now poised to become global public goods, bringing benefits to both emerging and developed economies.' Already, international UPI merchant payments are being accepted in 7 countries Bhutan, France, Mauritius, Nepal, Singapore, Sri Lanka, and the UAE. Sitharaman called on Indian fintech firms to export their successful models, saying, 'We have the talent, the market scale, and the proven solutions to lead globally.' Looking ahead, the Finance Minister shared a bold vision for the sector: India's fintech market is projected to grow to over $400 billion by 2028-29, with an annual growth rate of over 30 per cent. 'The best chapters of India's fintech story are yet to be written. The opportunity is immense.' She urged the industry to rally behind a collective mission: 'Let us Innovate, Include, and Inspire. Innovate new solutions fearlessly, include every citizen in your vision, and inspire the world with what India can achieve.' The event also spotlighted India's achievement in Direct Benefit Transfers (DBT). Since 2014, Rs 44 lakh crore have been transferred transparently through DBT, saving Rs 3.48 lakh crore by eliminating leakages. 'This is the power of technology that drives policy and banking,' Sitharaman said. Another milestone has been the rise of the Account Aggregator (AA) framework. From just 24 entities in FY22, over 700 entities across banking, insurance, pensions, and securities have joined the AA ecosystem as of FY25. The number of accounts linked has surged from 1.5 lakh to over 15 crore, facilitating loans of over Rs 88,700 crore, while empowering nearly 1 crore individuals with better personal finance management. Concluding her address, Sitharaman encouraged fintech firms to look beyond urban markets. 'Rural India is not just a social responsibility. It is a fertile ground for innovation, inclusion, and opportunity. The next big wave of growth lies in the Bharat beyond the metros.' (ANI)
Time of India
28-05-2025
- Business
- Time of India
Microsoft and Yotta partner to boost AI innovation in India
Microsoft and Yotta Data Services have joined forces to accelerate artificial intelligence (AI) adoption across India, integrating Microsoft's Azure AI services into Yotta's Shakti Cloud, a sovereign AI cloud platform. This collaboration aims to empower developers, startups, enterprises, and public sector organizations with advanced AI capabilities. The partnership aligns with the IndiaAI Mission , an initiative by the Ministry of Electronics and Information Technology (MeitY) to foster a robust AI ecosystem in India. By combining Microsoft's AI models, applications, and development tools with Yotta's cost-effective, high-performance AI compute platform, the collaboration aims to drive innovation in critical sectors such as agriculture, healthcare, education, finance, manufacturing, retail, and media. As of May 2025, the IndiaAI Mission has attracted over 500 proposals for developing indigenous AI models. Microsoft and Yotta will work closely with government agencies, research institutions, IITs, and startups to support homegrown AI solutions, enhancing local capabilities and strengthening India's AI infrastructure in alignment with the nation's Digital Public Infrastructure. This partnership positions India as a hub for AI innovation, enabling faster model training, real-time inferencing, and scalable solutions to address pressing societal and economic challenges.
Scroll.in
28-05-2025
- Business
- Scroll.in
The hollow hype over India as the ‘AI use case capital of the world'
In February 2023, Indian Prime Minister Narendra Modi called on citizens to 'identify 10 problems of the society that can be solved by AI'. In 2024, Nandan Nilekani, the IT czar who has been a driving force behind India's digital journey over the past 15 years, declared that India would soon become the ' AI use case capital of the world '. In January 2025, the Ministry of Electronics and Information Technology's IndiaAI Mission issued a call for proposals to build Indian foundational models, the software that underlies contemporary generative AI development. One of the criteria was 'identifying and elaborating use cases that address societal challenges at scale.' And last month, the Gates Foundation and the IndiaAI Mission announced a partnership on 'AI solutions for better crops, stronger healthcare, smarter education & climate resilience'. The discourse of AI use cases for socio-economic development is one of the most distinctive features of India's AI policy. Its promise is that AI will 'solve' difficult problems in classic sites of postcolonial development: agriculture, health, and education. It discursively links socio-economic development in rural India to industrial strategy at the cutting edge of global AI technology. However, lacking an account of political economy, the 'use cases' approach makes for a poor policy programme. Instead, this seductive vision serves as a hype machine, paying lip service to development to legitimise a range of other interventions, from claims to geopolitical leadership to the marketisation of populations new to the internet. The discourse of AI use cases has been foreshadowed by the digitalisation of development that followed the Aadhaar digital identity system in India. Launched in 2009 as an intervention that promised to streamline India's rights-based welfare apparatus, Aadhaar brought hundreds of millions of Indians into the purview of digital systems. Its promoters in the software industry used the promise of financial inclusion , especially following the founding of the IndiaStack project in 2015, to legitimise granting the Indian software and financial industry access to these digitalised Indians as customers. With access to private credit, impoverished Indians would now, in the financial inclusion playbook, ' enterprise themselves out of poverty '. While poverty remains an enormous challenge , state investment in public-private infrastructure has undergirded an expansion in the software industry, spawning, for example, a new fintech industry. The targeting enabled by Aadhaar and similar systems also heralded the rise of the BJP's ' new welfarism ', shifting away from public goods like public health and primary education to the provision of cash transfers for private goods like gas cylinders. Rebranded as ' Digital Public Infrastructure ', these systems are being exported around the world as a model for the use of technology in development. Building on this approach – and promoted by a similar set of actors in the state and industry – the AI 'use case' discourse frames India's societal challenges as a resource for software capitalists. In practice, AI use cases in these domains are largely speculative. In agriculture, for example, dozens of vernacular language chatbots promise to better inform farmers about weather conditions and planting times. In healthcare and education, the promises of AI are largely in streamlining administrative processes, such as hastening India's transition to digital health records, which is supposed to improve efficiency while delivering huge amounts of data to hospitals and insurance providers. Despite the lack of tested applications, the discourse of AI use cases portrays the numerically vast market constituted by the poor as a national opportunity in the global AI arms race. The AI supply chain – composed of datasets, models, and computing power – is controlled by just a handful of US Big Tech actors, eliciting industrial policy responses from several states . In India, the poverty market – where poor people are figured both as users and providers of data – is imagined as a driver of growth that can give the nation a competitive advantage in an increasingly concentrated global AI market. To be sure, Indian AI industrial policy also relies on more traditional tools, including massive incentives to build domestic capabilities in semiconductor manufacturing, cloud resources, and models. But the national champions of the Indian AI economy are imagined in the 'use case' discourse as emerging from software applications for socio-economic development. 'To [unlock] India's potential with AI', Nilekani proclaimed in 2023 , 'the trick is not to look too hard at the technology but to look at the problems people face that existing technology has been unable to solve'. The promise of use cases, in other words, blurs the lines between the marketisation of poverty and national industrial policy that hopes to make India globally competitive in cutting edge technology. Of course, this is too good to be true. The discourse of use cases ignores the political economy of both the AI industry and of development. From the perspective of AI sovereignty – a major focus in India's technological doctrine – it will do little good to become the 'use case capital of the world' if semiconductors, cloud resources, and models remain concentrated in the hands of US Big Tech. Today's generative AI, even more than other digital technologies, runs on semiconductors sold by a single company – Nvidia – which are fabricated by a single factory in Taiwan – TSMC – on equipment made by one Dutch manufacturer – ASML. Meanwhile the cloud computing data centers and models required by AI are overwhelmingly controlled by Amazon, Microsoft, and Google. AI use cases are imagined as a way to promote the growth of the domestic startup industry, but most Indian startups in the AI space and beyond don't appear to be interested in the poverty market. A 2024 survey of over 120 generative AI startups in India, which have collectively raised over $1.2 billion in the last five years, showed that 70% are providing solutions only for enterprise clients. In keeping with Indian tech's historical bias toward enterprise services, the industry appears to be largely focused on backend software components for use in industry, not consumer-facing software products, let alone for socio-economic development use cases. This is reflected in the sectoral data. Despite the buzz, agriculture does not figure as one of the top five sectoral applications for generative AI startups. While education and healthcare do figure in the top five, these are lucrative markets for the middle and upper classes; it appears unlikely (though we need further data to definitively conclude) that AI startups in these sectors have developmental goals. This makes financial sense for startups and venture capitalists. The Indians who would be targeted by the proclaimed AI use cases are, after all, very poor with little spending power to sustain startup business models. As a recent venture capitalist report put it , the poorest billion Indians are 'unmonetisable' for startups. AI use cases are also the wrong answer to issues of socio-economic development. Entrenched developmental problems in agriculture, health, and education need structural reforms rather than the quick technical fixes promised by AI . Indeed, the evidence over the past decade shows that reliance on digital systems such as Aadhaar to solve developmental challenges may have harmed the poor more than it helped them . Perhaps most of all, after decades of economic growth concentrated in low-employment sectors like software, Indians need mass employment, which AI use cases will not provide. We should understand the focus on use cases, then, as a particularly Indian species of technology hype, an inflated promise that makes things happen. In the US, AI hype has most often been premised on the emergence of an 'Artificial General Intelligence' with unimaginable, humanity-threatening capabilities that is supposedly right around the corner. These inflated promises have driven a massive surge of speculative investment and pushed market valuations of AI companies to new highs, despite little proven demand for the technology. In contrast, development as AI hype appears to offer a reasonable and socio-economically grounded alternative. Oriented not only toward the future but also toward the periphery of the capitalist system, it promises that those who have been on the margins of economic growth can serve as a source for data and a market for AI applications. This discursive structure may not be driving massive investment similar to US AI hype. Nevertheless, it serves a range of powerful constituents: 1. For the ruling government domestically, it projects an image of benevolent, technocratic developmentalism. Alongside its Hindu nationalism, this high-tech image has been a key plank of the current government's appeal . It is no accident that the exemplary AI use cases are chatbots, which are personalised technologies that provide a one-on-one interface with citizens to access targeted services. As such, AI use cases track with the BJP's shift away from the provision of public goods like basic health and primary health to the techno-patrimonial provision of private goods under Modi. 2. Globally, the 'use case' hype enables India to claim moral leadership on behalf of the global majority in the midst of a great power rivalry. A NITI Aayog AI strategy describes India as ' the AI Garage for 40% of the world ', suggesting that the AI use cases that India develops domestically will be exported to the global south. 3. For global development funders, like the Gates Foundation, who are pushing such initiatives elsewhere in the world under the label of AI for Development, the AI use case approach is the latest in a long line of digital interventions in development. It fits neatly within the philanthrocapitalist dogma that the solution to poverty is marketisation. 4. For the domestic software industry, the discourse of use cases legitimises the state-supported marketisation of a new digital population within India. It enables the extraction of citizens' data under the guise of development, though the financial value of these data and these customers is open to question. It offers the poor as test subjects in developing their products, while also opening up potential export markets in other developing countries. 5. For global tech giants, it offers a path to legitimise their activities in India. One of the most enthusiastic supporters of AI use cases is Microsoft CEO Satya Nadella, who recently (echoing Nilekani) remarked that India had become the 'AI use case capital of the world.' One of the most widely cited examples of AI in action for socio-economic development is the Jugalbandi chatbot, developed by Microsoft and IIT Madras, which provides vernacular language information about government services, and was released amidst a PR blitz in 2023. Adoption and usage statistics for the chatbot are unavailable. No further news has been released since 2023, and the project's website is no longer active. The discourse of AI use cases is seductive because it poses an excellent question: Why shouldn't the poor benefit from the most advanced technology? Unfortunately, socio-economic development use cases as currently articulated won't succeed within the contemporary conjuncture. The hype is unlikely to benefit the poor or India's AI ambitions. It leaves dominant power structures undisturbed and doesn't challenge the monopolistic and extractive practices that undergird Big Tech-led AI. Instead, it is empowering a range of powerful actors. What would it look like to centre poor and marginalised people while challenging Big Tech in an AI age? Most of all, it would require a shift away from treating people merely as end-users, data sources, and testing grounds of AI, but as its owners and producers. While genuine alternatives to the current set-up are largely speculative, initiatives imagining and working toward AI as a commons may provide inspiration for the kinds of changes that would be required for AI development to go hand-in-hand with socio-economic justice. Mila T Samdub researches the aesthetics and political economy of digital infrastructure in India. He is a Visiting Fellow at the Information Society Project at Yale Law School, a CyberBRICS Fellow at the Center for Technology and Society, Fundacao Getulio Vargas, and an Open Future Fellow. The article was first published in India in Transition , a publication of the Center for the Advanced Study of India, University of Pennsylvania.
