On a scale of 1–10, how confident are you in the security and responsiveness of your real-time payments? The speed and convenience of a real-time payment system are so good that its security aspect is often overlooked. Do you know that digital payment fraud in India surged more than fivefold, reaching Rs. 14.57 billion in the fiscal year ending March 2024? The negligence of a robust real-time payment fraud prevention, detection, and reporting system is the primary cause of such concerns. The need to track fraudulent financial transactions is an on-demand requirement for banks, POs, PAs, PSPs, and payment fintechs not just to stay away from malicious attackers but also to protect user data, money, and trust.
The current security framework that exists in most financial institutions is only single-layered, serving as a seamless gateway for fraudsters and malicious attackers to rob in sensitive details. This emphasises the need for real-time fraud detection in the security framework, which acts as a key element by monitoring transactions and other financial operations in real time, alerting officials, and preventing fraud and illegal activities from happening further. Adopting a multi-layered fraud prevention solution encompassing a robust real-time fraud detection mechanism helps enhance and improve the security front of the payment landscape, keeping fraudsters and illegal attackers at bay.
This blog explores the key components of a multi-layered security system, highlights the importance of real-time fraud prevention solutions, and emphasises BANKiQ’s commitment to securing and advancing digital payments to detect fraud transactions.
Understanding the Challenges of Digital Payments
Before we delve deeper into the security framework of financial fraud detection solutions and the role of real-time fraud detection, let’s analyse the risk factors involved in new-age payments.
- Operational Efficiency: A small technical glitch or system failure can totally disrupt users’ transaction processes, affecting their experience and efficiency in utilising instant payments. This negative impact will be a major drawback for financial institutions, which will struggle to impress and protect their customers in every possible manner.
- Data Breach: Financial institutions are not well equipped to deal with the volatile nature of the new-age payment landscape, making the ecosystem vulnerable to cyber attacks, including data breaches and losses.
- Fraud and Money Laundering: Digital or instant payments, which often offer less anonymity, present more opportunities for fraudsters to engage in money laundering activities. This makes it difficult to trace the origin of funds. It also enables businesses to transfer large sums of illicit money across borders within seconds.
- Regulatory Compliance: Ensuring regulatory compliance for digital transactions is crucial not only to avoid penalties but also to uphold the integrity and security of the payment ecosystem by staying aligned with the latest regulations. This requires a robust real-time transaction monitoring system capable of identifying and adapting to new regulatory requirements.
Exploring the Role of Each Layer in Multi-Layered Security Frameworks
To understand the role of real-time payment fraud detection in a multi-layered security framework, we first need to examine the components and significance of each layer within the framework.
1. Fraud Prevention
As a primary layer, this aims to offer a proactive defence approach against fraudulent transactions, ensuring no severe harm or damage is created. The fraud prevention layer operates in real-time as an early warning system alongside other security protocols such as authentication, real-time monitoring, and compliance adherence, providing banks, POs, PAs, PSPs, and other fintech with a robust safety mechanism that’s not just protective but also preventive in detecting fraud transactions.
- The fraud prevention layer analyses users’ behaviour by studying the pattern, volume, and frequency of transactions. This helps them identify or pinpoint deviations that may be a potential hazard in the future.
- The fraud prevention layer allocates score levels for every transaction type based on various factors. Transactions with a higher risk score are kept under observation, while the ones with a lower risk score are processed immediately. This way, the layer ensures that no risky transactions are allowed for further processing.
Thus, the fraud prevention layer, with its machine learning capabilities and continuous real-time monitoring, ensures that every transaction is well analysed to detect fraud transactions and anomalies before they could indicate potential fraudulent activities.
2. Fraud Detection
There is always a question: what if a risky transaction bypasses the preliminary defence? Well, the fraud detection layer is exactly for this. The fraud prevention layer is all about halting the fraud before it happens, whereas the fraud detection layer is to identify and respond to the scam that has slipped through the prevention mechanism. This layer is the primary element in the security framework, for it not only monitors fraudulent transactions but also responds to them in a way that does not prolong the hazard to a larger extent.
- The fraud detection layer supports advanced analytics and machine learning algorithms, which meticulously examine large volumes of transaction data to flag and detect unusual and irregular fraud transactions in real-time.
- Known for its continuous monitoring, the layer generates an alert to banks and other fintech as soon as it spots an irregularity, prompting further investigation to minimise the loss or breach.
- Anomaly detection is a key technique in the fraud detection layer. It is carried out when even a slight deviation from the usual activity is signalled as a potential threat or fraud.
- The fraud detection layer enables cross-channel analyses across multiple devices, allowing banks, POs, PAs and other fintechs to cut through frauds that might occur through different vectors, such as a fraudster using stolen credentials to access accounts from various devices.
The integration with threat intelligence empowers the fraud detection layer with up-to-date or emerging threats that might not be visible in the prevention layer.
This sophisticated defensive approach by the fraud detection layer reduces the risk of fraudulent transactions, supports regulatory compliance and reassures customer trust by strengthening the security posture and integrity of the security framework. The fraud detection layer serves as a safety net for transactions and operations that skip the prevention layer. Also, the effective real-time monitoring capability and robustness of the layer are significant advantages for banks, POs, PAs, PSPs, and other fintechs to guard against both known and emerging threats effectively.
3. Fraud Reporting
As a final layer, fraud reporting serves as a critical layer in responding to the documented detected and identified malicious transactions and finally communicating to the stakeholders. The layer, in addition to response and remediation, also offers a feedback mechanism for banks and fintechs to continuously learn and enhance the security measures to contribute to a stronger and more resilient fraud prevention solution.
- In fraud detection, it is necessary to document the incident comprehensively, including the nature of fraud, how it entered, who it affects, and the financial consequences. This detailed documentation will help the reporting layer respond to fraud cases, if any, in a timely manner.
- Reporting to regulatory authorities is essential to avoid penalties and maintain a financial institution’s legal standing. For example, STR is a mandatory requirement for digital transactions, which, if not followed, will result in legal action.
- Internal reporting is one aspect of the reporting layer, where the incident is communicated to the necessary stakeholders, executives, and risk management team. This empowers them to take further action, such as reinforcing controls or adjusting security policies.
- The fraud reporting layer assists banks, POs, PAs, PSPs, and other fintech in documenting and communicating incidents and analysing the data collected. This helps to understand the threat in more detail, the existing vulnerabilities in the security framework, and the patterns and flow of payment fraud.
- Finally, the layer helps with post-review incident analysis to assess the effectiveness of the response, the gaps in communication, and the improvements to be implemented. This helps strengthen the reporting layer and emerge as a stronger and more resilient security layer.
Overall, the fraud reporting layer is a critical layer in the security framework. It ties together the entire security ecosystem by providing a mechanism for continuous learning and adaptation. The insights gained from the fraud reporting layer help study the deficiencies in the security framework, leading to a more effective prevention and detection layer.
Thus, a multilayered security framework serves as an early warning system that highlights how fraud or threats are trapped and removed before they emerge as a big challenge for banks and fintech.
Why Real-time Fraud Detection?
The most untapped component of the security framework is real-time fraud detection, whose integration has enhanced the security ecosystem of digital transactions to new levels. As a dynamic and responsive component, real-time fraud detection’s role in a security framework is beyond the scope of continuous monitoring and reporting. Let’s discuss the significance of real-time fraud detection in a multilayered security framework.
Swift Detection
The highlight feature of real-time fraud detection is its ability to respond to threats and fraudulent activities as they happen, unlike traditional approaches, where the security framework analyses the transactions in batches. Imagine if a fraudulent transaction was monitored after an hour; the transaction would have reached a point where the fraudster could seamlessly access all the sensitive data. Swift detection is achieved with the help of advanced algorithms and machine learning models, which are trained using historical datasets to identify any resembling frauds and threats.
Enhanced Layer Communication
With multiple layers in the security framework, real-time fraud detection acts as the central platform that integrates and supports each layer. While the prevention and reporting layers have distinct workflows, real-time fraud detection seamlessly interacts with both, ensuring that every process is thoroughly monitored and analysed. It mitigates any shortcomings in one layer by reinforcing the next. For instance, if a threat slips past the prevention layer, real-time fraud detection captures it and ensures that the subsequent layer is robust enough to prevent the fraud from progressing.
Immediate Response
Once the transaction has been flagged, the real-time fraud detection system does not wait for a professional to notify or initiate the next step. Instead, the system proceeds without any delay by
- Halting the transactions to proceed further.
- Triggering an alert to notify involved parties of the occurrence of fraud.
- Ensuring additional security measures are to be conducted to ensure the transaction does not get completed.
Regulatory Compliance
Adhering to the latest regulations and requirements is not just necessary but critical for banks, PAs, PSPs, POs, and other fintechs. Keeping up with updates and timely reporting incidents can be challenging. However, real-time fraud detection ensures that any fraud or threat is immediately reported to the appropriate regulatory authorities, maintaining full compliance without compromise.
Now that the significance of real-time fraud detection has been analysed and discussed, let’s see how BANKiQ’s solution contributes to this payment security ecosystem.
Safeguarding Digital Payments: BANKiQ’s Integrated Approach for Fintechs
Banks, Payment Operators (POs), Payment Aggregators (PAs), Payment Service Providers (PSPs), and other fintech companies require a robust preventive platform with comprehensive fraud detection capabilities, including real-time monitoring, reporting, and compliance. BANKiQ, renowned for its advanced ML-powered Fraud Risk Monitoring solution, offers a multi-layered security framework. This includes case management, queue and alert management, ensuring that every transaction is monitored in real-time. This approach enables swift and effective responses to threats, safeguarding not only security but also the reputation among trusted business leaders and clients.
With its prevention, real-time detection, and reporting layers, BANKiQ’s security framework is both proactive and preventive, enabling banks and fintech to stay ahead of fraud and risky transactions. Let’s explore BANKiQ’s four key solutions and how their advancements contribute to a secure and threat-free digital payment system.
- Fraud Risk Compliance (FRC): As a modern-age solution, BANKiQ’s FRC offers real-time transaction monitoring tailored for acquirer banks. It enables them to oversee customer onboarding and identify suspicious accounts. Equipped with advanced cognitive features, the FRC solution provides real-time fraud detection, safeguarding not only transactions but also ensuring customer profiles remain secure from threats.
- Intelligent Fraud Risk Management (iFRM): As a fraud prevention solution, BANKiQ’s iFRM tackles multiple facets of financial crimes across a multi-channel platform. Banks, PAs, POs, PSPs, and fintechs can all benefit from the iFRM solution, which integrates behavioural profiling with transaction risk scoring to deliver a robust and comprehensive security framework against all kinds of fraudulent transactions.
- Optimises Business Operations: Financial institutions leverage AI and ML to improve services and create comprehensive predictive models. This approach not only helps save costs but also enhances the customer experience by reducing service interruptions. AI in financial services optimises workforce management, allocating resources based on real-time demand, leading to better service delivery and increased profitability.
- PULSE: As a hosted fraud prevention solution, BANKiQ’s PULSE empowers small banks and cooperatives to combat digital payment fraud with a pre-packaged prevention approach. Featuring customised detection strategies, an alert system, and blocking capabilities, PULSE provides a robust and efficient fraud detection solution, ideal for financial institutions facing complex challenges in halting fraud in their tracks.
- Intelligent AML (IAML): Due to the narrow transaction window in digital payments, money laundering has become easier for fraudsters. Implementing a real-time payment fraud detection system can strengthen anti-money laundering efforts by identifying deviations in transaction volume and patterns from the norm.
In this way, BANKiQ demonstrates that adopting a digital payment fraud detection system with a preventive and proactive strategy enables financial institutions to stay ahead of compliance requirements and mitigate risky transactions. Since every transaction is unique, so must be the solution. Experience the security and reliability of BANKiQ firsthand and discover what it truly means to stay on the safe side of instant payments.
Conclusions
To conclude, the need for robust, multi-layered security has become a never-before-critical demand for financial institutions to safeguard their data, identity, and reputation. The adoption of real-time fraud detection serves as the cornerstone of a multilayer security framework, which ensures no fraud or threat is left behind. From preventing threats to ensuring regulatory compliance and enabling swift responses to suspicious activities, real-time fraud detection not only fortifies security but also empowers financial institutions to stay ahead of fraudsters. By adopting advanced fraud prevention solutions like BANKiQ’s offerings, banks, PAs, PSPs, POs, and fintechs can build a resilient defence, safeguarding their operations and customers in an increasingly complex digital environment.
