The rise of real-time payments has led to an increase in social engineering frauds, where fraudsters deceive victims into sending money to fraudulent accounts. Given the rapid settlement of these transactions, retrieving the transferred funds presents a formidable challenge. Furthermore, traditional data sources, such as credit reports and transaction history, while valuable, offer a limited perspective on consumer behaviour. Immediate intervention is crucial to prevent such frauds and minimize financial losses. Prompt detection and reporting of fraudulent transactions are essential, as any delay significantly diminishes the chances of fund recovery. Additionally, leveraging alternate data sources provides a more sophisticated approach to identifying and mitigating fraudulent activities, offering deeper insights into users' behaviour, lifestyle, and financial strength.
Participants are encouraged to develop solutions which may in real-time, help in detection and prevention of frauds using AI/ML, API, Data Analytics and other cutting edge technologies. These systems should not only accurately identify fraudulent activities but also minimise false positives, using various data sources such as behavioural, biometric and social media data, quickly report and prevent further frauds, thus enhancing recovery prospects. Furthermore, participants are encouraged to utilize novel technologies to gather alternate data sources, enabling innovative use of information available in public domain to predict fraudulent transactions and identify potential red flags overlooked by traditional data sources.

In addition to ensuring safety and security of digital transactions, it is also imperative to safeguard the privacy of users to instil public trust in the system. In this regard, there is a need to follow a cautious approach to ensure balance between establishing the identity of user while at the same time preventing erosion of privacy, especially with regard to transaction details. Participants are invited to develop new technology solutions that offer robust privacy of digital tokens like CBDCs without compromising on the transaction validation mechanism, system integrity, fraud mitigation measures and reporting requirements. Solutions may employ innovative ways of safeguarding anonymity and may also include features that allow anonymity within a threshold. Beyond the threshold, the solution should facilitate compliance to applicable AML/ CFT guidelines.  Solutions should necessarily cater to the use case of digital tokens being issued within the regulated framework of India.

Mule accounts are often utilised for illicit activities such as money laundering and fraud. In cases of cyber fraud, the stolen money is frequently routed through multiple accounts before being withdrawn. The victims are duped by fraudsters into laundering stolen/illegal money via their bank account and they are unknowingly complicit in criminal activity. They also suffer financial losses if their bank accounts are closed or frozen. It is challenging for law enforcement agencies and banks/ payment system operators to take prompt action and trace various hops of transactions. Solutions may be developed using the emerging technologies for identifying the mule accounts which may trace the transaction chain and raise alerts so that funds can be blocked/ recovered, if required. The solution may also analyse transaction patterns, detect suspicious activities associated with mule accounts, identify anomalies in transaction behaviour and flag potential cases of money laundering or fraud for further investigation.

Identifying currency notes can be a significant challenge for individuals with visual impairments. The aim is to solicit and build technological solutions to assist fully or partially visually impaired persons in accurately identifying and differentiating between various denominations of Indian banknotes in circulation, for their enhanced inclusivity into the financial landscape. Participants are expected to design and develop innovative accessible, secure, cost-effective, user friendly, and adaptable devices / solutions that utilize technologies such as computer vision, machine learning, optical character recognition (OCR), haptics, or wearable devices etc. for the purpose. The solutions should be an improvement over existing features available in the market and empower visually impaired individuals to independently identify and manage currency notes in their daily lives. It may be noted that proposals for change in any design or security features (visible or invisible) of the banknotes will, however, not be accepted.