Domestic UPI Frauds: Finance Ministry Presented Data in LokSabha
Introduction
According to the Finance Ministry's data, the incidence of domestic Unified Payment Interface (UPI) fraud rose by 85% in FY 2023-24 compared to FY 2022-23. Further, as of September of FY 2024-25, 6.32 lakh fraud cases had been already reported, amounting to Rs 485 crore. The data was shared on 25th November 2024, by the Finance Ministry in response to a question in Lok Sabha’s winter session about the fraud in UPI transactions during the past three fiscal years.
Statistics

UPI Frauds and Government's Countermeasures
On the query as to measures taken by the government for safe and secure UPI transactions and prevention of fraud in the transactions, the ministry has highlighted the measures as follows:
- The Reserve Bank of India (RBI) has launched the Central Payment Fraud Information Registry (CPFIR), a web-based tool for reporting payment-related frauds, operational since March 2020, and it requires requiring all Regulated Entities (RE) to report payment-related frauds to the said CPFIR.
- The Government, RBI, and National Payments Corporation of India (NPCI) have implemented various measures to prevent payment-related frauds, including UPI transaction frauds. These include device binding, two-factor authentication through PIN, daily transaction limits, and limits on use cases.
- Further, NPCI offers a fraud monitoring solution for banks, enabling them to alert and decline transactions using AI/ML models. RBI and banks are also promoting awareness through SMS, radio, and publicity on 'cyber-crime prevention'.
- The Ministry of Home Affairs has launched a National Cybercrime Reporting Portal (NCRP) (www.cybercrime.gov.in) and a National Cybercrime Helpline Number 1930 to help citizens report cyber incidents, including financial fraud. Customers can also report fraud on the official websites of their bank or bank branches.
- The Department of Telecommunications has introduced the Digital Intelligence Platform (DIP) and 'Chakshu' facility on the Sanchar Saathi portal, enabling citizens to report suspected fraud messages via call, SMS, or WhatsApp.
Conclusion
UPI is India's most popular digital payment method. As of June 2024, there are around 350 million active users of the UPI in India. The Indian Cyber Crime Coordination Centre (I4C) report indicates that ‘Online Financial Fraud’, a cyber crime category under NCRP, is the most prevalent among others. The rise of financial fraud, particularly UPI fraud is cause for alarm, the scammers use sophisticated strategies to deceive victims. It is high time for netizens to exercise caution and care with their personal and financial information, stay aware of common tactics used by fraudsters, and adhere to best security practices for secure transactions and the safe use of UPI services.
References
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On the occasion of 20th edition of Safer Internet Day 2023, CyberPeace in collaboration with UNICEF, DELNET, NCERT, and The National Book Trust (NBT), India, took steps towards safer cyberspace by launching iSafe Multimedia Resources, CyberPeace TV, and CyberPeace Café in an event held today in Delhi.
CyberPeace also showcased its efforts, in partnership with UNICEF, to create a secure and peaceful online world through its Project iSafe, which aims to bridge the knowledge gap between emerging advancements in cybersecurity and first responders. Through Project iSafe, CyberPeace has successfully raised awareness among law enforcement agencies, education departments, and frontline workers across various fields. The event marked a significant milestone in the efforts of the foundation to create a secure and peaceful online environment for everyone.
Launching the Cyberpeace TV, café and isafe material , National Cybersecurity coordinator of Govt of India, Lt Gen Rajesh Pant interacts with the students by introducing them with the theme of this safer internet day. He launched the coword cyber challenge initiative by the countries. Content is most important in cyberspace. He also assured everyone that the government of India is taking a lot of steps at national level to make cyber space safer. He compliments CPF for their initiatives.
Ms. Zafrin Chaudhry, Chief of Communication, UNICEF addresses students with the facts that children make out 1 out of 3 in cyberspace, so they should have a safe cyberspace. They should be informed and equipped with all the information on how to deal with any kind of issues they face in cyberspace. They should share their experience with everyone to make others aware. UNICEF in partnership with CPF is extending help to children to equip them with the help and information.
Major Vineet Kumar, Founder and Global President of CPF welcomed all and introduced us about the launching of iSafe Multimedia Resources, CyberPeace TV, and CyberPeace Café . With this launch he threw some light on upcoming plans like launching a learning module of metaverse with AR and VR. He wants to make cyberspace safe even in tier 3 cities that’s why he established the first cybercafé in Ranchi.
As the internet plays a crucial role in our lives, CyberPeace has taken action to combat potential cyber threats. They introduced CyberPeace TV, the world’s first multilingual TV Channel on Jio TV focusing on Education and Entertainment, a comprehensive online platform that provides the latest in cybersecurity news, expert analysis, and a community for all stakeholders in the field. CyberPeace also launched its first CyberPeace Café for creators and innovators and released the iSafe Multimedia resource containing Flyers, Posters, E hand book and handbook on digital safety for children developed jointly by CyberPeace, UNICEF and NCERT for the public.
O.P. Singh, Former DGP, UP Police & CEO Kailash Satyarthi foundation, , started with the data of internet users in India. The Internet is used in day-to -day activities nowadays and primarily in social media. Students should have a channelized approach to cyberspace like fixed screen time, information to the right content, and usage of the internet. I really appreciate the initiates that CyberPeace is taking in this direction.
The celebration continued by iSafe Panel Discussion on “Creating Safer Cyberspace for Children.” The discussion was moderated by Dr. Sangeeta Kaul, Director of DELNET, and was attended by panellists Mr. Rakesh Maheshwari from MeitY(Ministry of electronics and information Technology, Govt. of India), Dr. Indu Kumar from CIET-NCERT, Ms. Bindu Sharma from ICMEC, and Major Vineet Kumar from CyberPeace.
The event was also graced by professional artists from the National School of Drama, who performed Nukkad Natak and Qawwali based on cyber security themes. Students from SRDAV school also entertained the audience with their performances. The attendees were also given a platform to share their experiences with online security issues, and ICT Awardees, Parents and iSafe Champions shared their insights with the guests. The event also had stalls by CyberPeace Corps, a Global volunteer initiative, and CIET-NCERT for students to explore and join the cause. The event’s highlight was the 360 Selfie Booth, where attendees lined up to have their turn.

Introduction
Advanced deepfake technology blurs the line between authentic and fake. To ascertain the credibility of the content it has become important to differentiate between genuine and manipulated or curated online content highly shared on social media platforms. AI-generated fake voice clone, videos are proliferating on the Internet and social media. There is the use of sophisticated AI algorithms that help manipulate or generate synthetic multimedia content such as audio, video and images. As a result, it has become increasingly difficult to differentiate between genuine, altered, or fake multimedia content. McAfee Corp., a well-known or popular global leader in online protection, has recently launched an AI-powered deepfake audio detection technology under Project “Mockingbird” intending to safeguard consumers against the surging threat of fabricated or AI-generated audio or voice clones to dupe people for money or unauthorisly obtaining their personal information. McAfee Corp. announced its AI-powered deepfake audio detection technology, known as Project Mockingbird, at the Consumer Electronics Show, 2024.
What is voice cloning?
To create a voice clone of anyone's, audio can be deeplyfaked, too, which closely resembles a real voice but, in actuality, is a fake voice created through deepfake technology.
Emerging Threats: Cybercriminal Exploitation of Artificial Intelligence in Identity Fraud, Voice Cloning, and Hacking Acceleration
AI is used for all kinds of things from smart tech to robotics and gaming. Cybercriminals are misusing artificial intelligence for rather nefarious reasons including voice cloning to commit cyber fraud activities. Artificial intelligence can be used to manipulate the lips of an individual so it looks like they're saying something different, it could also be used for identity fraud to make it possible to impersonate someone for a remote verification for your bank and it also makes traditional hacking more convenient. Cybercriminals have been misusing advanced technologies such as artificial intelligence, which has led to an increase in the speed and volume of cyber attacks, and that's been the theme in recent times.
Technical Analysis
To combat Audio cloning fraudulent activities, McAfee Labs has developed a robust AI model that precisely detects artificially generated audio used in videos or otherwise.
- Context-Based Recognition: Contextual assessment is used by technological devices to examine audio components in the overall setting of an audio. It improves the model's capacity to recognise discrepancies suggestive of artificial intelligence-generated audio by evaluating its surroundings information.
- Conductual Examination: Psychological detection techniques examine linguistic habits and subtleties, concentrating on departures from typical individual behaviour. Examining speech patterns, tempo, and pronunciation enables the model to identify artificially or synthetically produced material.
- Classification Models: Auditory components are categorised by categorisation algorithms for detection according to established traits of human communication. The technology differentiates between real and artificial intelligence-synthesized voices by comparing them against an extensive library of legitimate human speech features.
- Accuracy Outcomes: McAfee Labs' deepfake voice recognition solution, which boasts an impressive ninety per cent success rate, is based on a combined approach incorporating psychological, context-specific, and categorised identification models. Through examining audio components in the larger video context and examining speech characteristics, such as intonation, rhythm, and pronunciation, the system can identify discrepancies that could be signs of artificial intelligence-produced audio. Categorical models make an additional contribution by classifying audio information according to characteristics of known human speech. This all-encompassing strategy is essential for precisely recognising and reducing the risks connected to AI-generated audio data, offering a strong barrier against the growing danger of deepfake situations.
- Application Instances: The technique protects against various harmful programs, such as celebrity voice-cloning fraud and misleading content about important subjects.
Conclusion
It is important to foster ethical and responsible consumption of technology. Awareness of common uses of artificial intelligence is a first step toward broader public engagement with debates about the appropriate role and boundaries for AI. Project Mockingbird by Macafee employs AI-driven deepfake audio detection to safeguard against cyber criminals who are using fabricated AI-generated audio for scams and manipulating the public image of notable figures, protecting consumers from financial and personal information risks.
References:
- https://www.cnbctv18.com/technology/mcafee-deepfake-audio-detection-technology-against-rise-in-ai-generated-misinformation-18740471.htm
- https://www.thehindubusinessline.com/info-tech/mcafee-unveils-advanced-deepfake-audio-detection-technology/article67718951.ece
- https://lifestyle.livemint.com/smart-living/innovation/ces-2024-mcafee-ai-technology-audio-project-mockingbird-111704714835601.html
- https://news.abplive.com/fact-check/audio-deepfakes-adding-to-cacophony-of-online-misinformation-abpp-1654724

Introduction
The term ‘super spreader’ is used to refer to social media and digital platform accounts that are able to quickly transmit information to a significantly large audience base in a short duration. The analogy references the medical term, where a small group of individuals is able to rapidly amplify the spread of an infection across a huge population. The fact that a few handful accounts are able to impact and influence many is attributed to a number of factors like large follower bases, high engagement rates, content attractiveness or virality and perceived credibility.
Super spreader accounts have become a considerable threat on social media because they are responsible for generating a large amount of low-credibility material online. These individuals or groups may create or disseminate low-credibility content for a number of reasons, running from social media fame to garnering political influence, from intentionally spreading propaganda to seeking financial gains. Given the exponential reach of these accounts, identifying, tracing and categorising such accounts as the sources of misinformation can be tricky. It can be equally difficult to actually recognise the content they spread for the misinformation that it actually is.
How Do A Few Accounts Spark Widespread Misinformation?
Recent research suggests that misinformation superspreaders, who consistently distribute low-credibility content, may be the primary cause of the issue of widespread misinformation about different topics. A study[1] by a team of social media analysts at Indiana University has found that a significant portion of tweets spreading misinformation are sent by a small percentage of a given user base. The researchers conducted a review of 2,397,388 tweets posted on Twitter (now X) that were flagged as having low credibility and details on who was sending them. The study found that it does not take a lot of influencers to sway the beliefs and opinions of large numbers. This is attributed to the impact of what they describe as superspreaders. The researchers collected 10 months of data, which added up to 2,397,388 tweets sent by 448,103 users, and then reviewed it, looking for tweets that were flagged as containing low-credibility information. They found that approximately a third of the low-credibility tweets had been posted by people using just 10 accounts, and that just 1,000 accounts were responsible for posting approximately 70% of such tweets.[2]
Case Study
- How Misinformation ‘Superspreaders’ Seed False Election Theories
During the 2020 U.S. presidential election, a small group of "repeat spreaders" aggressively pushed false election claims across various social media platforms for political gain, and this even led to rallies and radicalisation in the U.S.[3] Superspreaders accounts were responsible for disseminating a disproportionately large amount of misinformation related to the election, influencing public opinion and potentially undermining the electoral process.
In the domestic context, India was ranked highest for the risk of misinformation and disinformation according to experts surveyed for the World Economic Forum’s 2024 Global Risk Report. In today's digital age, misinformation, deep fakes, and AI-generated fakes pose a significant threat to the integrity of elections and democratic processes worldwide. With 64 countries conducting elections in 2024, the dissemination of false information carries grave implications that could influence outcomes and shape long-term socio-political landscapes. During the 2024 Indian elections, we witnessed a notable surge in deepfake videos of political personalities, raising concerns about the influence of misinformation on election outcomes.
- Role of Superspreaders During Covid-19
Clarity in public health communication is important when any grey areas or gaps in information can be manipulated so quickly. During the COVID-19 pandemic, misinformation related to the virus, vaccines, and public health measures spread rapidly on social media platforms, including Twitter (Now X). Some prominent accounts or popular pages on platforms like Facebook and Twitter(now X) were identified as superspreaders of COVID-19 misinformation, contributing to public confusion and potentially hindering efforts to combat the pandemic.
As per the Center for Countering Digital Hate Inc (US), The "disinformation dozen," a group of 12 prominent anti-vaccine accounts[4], were found to be responsible for a large amount of anti-vaccine content circulating on social media platforms, highlighting the significant role of superspreaders in influencing public perceptions and behaviours during a health crisis.
There are also incidents where users are unknowingly engaged in spreading misinformation by forwarding information or content which are not always shared by the original source but often just propagated by amplifiers, using other sources, websites, or YouTube videos that help in dissemination. The intermediary sharers amplify these messages on their pages, which is where it takes off. Hence such users do not always have to be the ones creating or deliberately popularising the misinformation, but they are the ones who expose more people to it because of their broad reach. This was observed during the pandemic when a handful of people were able to create a heavy digital impact sharing vaccine/virus-related misinformation.
- Role of Superspreaders in Influencing Investments and Finance
Misinformation and rumours in finance may have a considerable influence on stock markets, investor behaviour, and national financial stability. Individuals or accounts with huge followings or influence in the financial niche can operate as superspreaders of erroneous information, potentially leading to market manipulation, panic selling, or incorrect impressions about individual firms or investments.
Superspreaders in the finance domain can cause volatility in markets, affect investor confidence, and even trigger regulatory responses to address the spread of false information that may harm market integrity. In fact, there has been a rise in deepfake videos, and fake endorsements, with multiple social media profiles providing unsanctioned investing advice and directing followers to particular channels. This leads investors into dangerous financial decisions. The issue intensifies when scammers employ deepfake videos of notable personalities to boost their reputation and can actually shape people’s financial decisions.
Bots and Misinformation Spread on Social Media
Bots are automated accounts that are designed to execute certain activities, such as liking, sharing, or retweeting material, and they can broaden the reach of misinformation by swiftly spreading false narratives and adding to the virality of a certain piece of content. They can also artificially boost the popularity of disinformation by posting phony likes, shares, and comments, making it look more genuine and trustworthy to unsuspecting users. Bots can exploit social network algorithms by establishing false identities that interact with one another and with real users, increasing the spread of disinformation and pushing it to the top of users' feeds and search results.
Bots can use current topics or hashtags to introduce misinformation into popular conversations, allowing misleading information to acquire traction and reach a broader audience. They can lead to the construction of echo chambers, in which users are exposed to a narrow variety of perspectives and information, exacerbating the spread of disinformation inside restricted online groups. There are incidents reported where bot's were found as the sharers of content from low-credibility sources.
Bots are frequently employed as part of planned misinformation campaigns designed to propagate false information for political, ideological, or commercial gain. Bots, by automating the distribution of misleading information, can make it impossible to trace the misinformation back to its source. Understanding how bots work and their influence on information ecosystems is critical for combatting disinformation and increasing digital literacy among social media users.
CyberPeace Policy Recommendations
- Recommendations/Advisory for Netizens:
- Educating oneself: Netizens need to stay informed about current events, reliable fact-checking sources, misinformation counter-strategies, and common misinformation tactics, so that they can verify potentially problematic content before sharing.
- Recognising the threats and vulnerabilities: It is important for netizens to understand the consequences of spreading or consuming inaccurate information, fake news, or misinformation. Netizens must be cautious of sensationalised content spreading on social media as it might attempt to provoke strong reactions or to mold public opinions. Netizens must consider questioning the credibility of information, verifying its sources, and developing cognitive skills to identify low-credibility content and counter misinformation.
- Practice caution and skepticism: Netizens are advised to develop a healthy skepticism towards online information, and critically analyse the veracity of all information sources. Before spreading any strong opinions or claims, one must seek supporting evidence, factual data, and expert opinions, and verify and validate claims with reliable sources or fact-checking entities.
- Good netiquette on the Internet, thinking before forwarding any information: It is important for netizens to practice good netiquette in the online information landscape. One must exercise caution while sharing any information, especially if the information seems incorrect, unverified or controversial. It's important to critically examine facts and recognise and understand the implications of sharing false, manipulative, misleading or fake information/content. Netizens must also promote critical thinking and encourage their loved ones to think critically, verify information, seek reliable sources and counter misinformation.
- Adopting and promoting Prebunking and Debunking strategies: Prebunking and debunking are two effective strategies to counter misinformation. Netizens are advised to engage in sharing only accurate information and do fact-checking to debunk any misinformation. They can rely on reputable fact-checking experts/entities who are regularly engaged in producing prebunking and debunking reports and material. Netizens are further advised to familiarise themselves with fact-checking websites, and resources and verify the information.
- Recommendations for tech/social media platforms
- Detect, report and block malicious accounts: Tech/social media platforms must implement strict user authentication mechanisms to verify account holders' identities to minimise the formation of fraudulent or malicious accounts. This is imperative to weed out suspicious social media accounts, misinformation superspreader accounts and bots accounts. Platforms must be capable of analysing public content, especially viral or suspicious content to ascertain whether it is misleading, AI-generated, fake or deliberately misleading. Upon detection, platform operators must block malicious/ superspreader accounts. The same approach must apply to other community guidelines’ violations as well.
- Algorithm Improvements: Tech/social media platform operators must develop and deploy advanced algorithm mechanisms to detect suspicious accounts and recognise repetitive posting of misinformation. They can utilise advanced algorithms to identify such patterns and flag any misleading, inaccurate, or fake information.
- Dedicated Reporting Tools: It is important for the tech/social media platforms to adopt robust policies to take action against social media accounts engaged in malicious activities such as spreading misinformation, disinformation, and propaganda. They must empower users on the platforms to flag/report suspicious accounts, and misleading content or misinformation through user-friendly reporting tools.
- Holistic Approach: The battle against online mis/disinformation necessitates a thorough examination of the processes through which it spreads. This involves investing in information literacy education, modifying algorithms to provide exposure to varied viewpoints, and working on detecting malevolent bots that spread misleading information. Social media sites can employ similar algorithms internally to eliminate accounts that appear to be bots. All stakeholders must encourage digital literacy efforts that enable consumers to critically analyse information, verify sources, and report suspect content. Implementing prebunking and debunking strategies. These efforts can be further supported by collaboration with relevant entities such as cybersecurity experts, fact-checking entities, researchers, policy analysts and the government to combat the misinformation warfare on the Internet.
References:
- https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201 {1}
- https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {2}
- https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette {3}
- https://counterhate.com/research/the-disinformation-dozen/ {4}
- https://phys.org/news/2024-05-superspreaders-responsible-large-portion-misinformation.html#google_vignette
- https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302201
- https://www.nytimes.com/2020/11/23/technology/election-misinformation-facebook-twitter.html
- https://www.wbur.org/onpoint/2021/08/06/vaccine-misinformation-and-a-look-inside-the-disinformation-dozen
- https://healthfeedback.org/misinformation-superspreaders-thriving-on-musk-owned-twitter/
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8139392/
- https://www.jmir.org/2021/5/e26933/
- https://www.yahoo.com/news/7-ways-avoid-becoming-misinformation-121939834.html