Fraud Risk Management Strategy for Digital Payments Operations

The Financial Crimes in Digital Payments

Digital payments increased during the pandemic, driven by evolving customer engagement channels and advancements in payment technologies. While these innovations enhance convenience, they also introduce a few fraud risks, challenging banks, payment service providers (PSP), and payment aggregators (PA). Fraudsters are exploiting vulnerabilities across payment channels, including identity theft, transaction fraud, QR code use, account takeovers, and phishing scams. If issuer banks and acquirer banks lack a fraud risk management strategy, it leads to the risk of facing unauthorised payments, merchant fraud, and regulatory non-compliance.

Defense Against Financial Crimes: Modern Approach

In the digital payments landscape, traditional fraud detection systems are often inadequate because they depend on limited data analysis, static rules, and manual processes. These traditional fraud detection systems struggle to adapt to new fraud tactics, leading to delayed responses and making organisations vulnerable to financial losses.

On the other hand, a modern fraud risk management strategy includes advanced technologies like machine learning (ML), artificial intelligence (AI), big data analytics, and behavioral biometrics. Without compromising efficiency, a fraud risk management strategy is automated and scalable to handle high transaction volumes. The modern approach uses predictive analytics to identify emerging fraud risks to enable proactive defense. BANKiQ provides risk management solutions utilising the modern approach that serves as a reliable and trustworthy fraud risk management strategy.

Digital payment providers can enhance fraud detection, mitigate risks, and improve the customer experience by adopting a modern fraud risk management approach. In fraud risk management strategy, detecting and preventing plays a significant role in reducing financial crimes.

Detection and Prevention

Effective fraud detection and prevention are essential components of a robust fraud risk management strategy for digital payments. Modern approaches focus on real-time, data-driven solutions to identify and prevent fraud before it affects the financial landscape.

Detection

As a primary step in fraud risk management, fraud detection involves identifying suspicious activities by analysing transaction patterns and customer behaviour. Advanced techniques include:

• Machine learning (ML) and Artificial Intelligence (AI): These technologies help detect anomalies in fraud risk management strategies by continuously collecting new data and converting it into emerging fraud tactics.
• Behavioural Analytics: By tracking user behaviours, such as login patterns or spending habits, systems can spot deviations that may indicate fraud.

Prevention

Preventive measures aim to stop fraud before it occurs. These include:

• Multi-Factor Authentication (MFA): It requires multiple forms of verification to ensure that only authorised users can access accounts. (e.g., passwords and biometrics)
• Combining AI, machine learning, and preventive measures like MFA increases fraud detection, security, and customer trust in digital payments.

Real-Time Monitoring

Traditional transaction monitoring, which usually involves periodic reviews and manual checks, slows down the detection of fraudulent activities. Fraudsters carry out their plans and exploit vulnerabilities, and this lag time provides them with a window of opportunity to conduct financial crimes.

In contrast, real-time monitoring differs from traditional transaction monitoring and inherits advanced technologies such as artificial intelligence, machine learning, and big data analytics to analyse transactions immediately. This instant check enables businesses to identify and address potential threats in true real-time and also significantly reduces fraud risk.

BANKiQ’s Approach to Prevent Financial Crimes

BANKiQ is a leading fraud and risk compliance platform that helps many banks, financial institutions, and payment solution providers overcome fraudulent behavior. Its solutions address financial crimes faced by issuer banks, acquirer banks, payment solutions providers (PSP), Payment Aggregators(PA), Financial service companies, and Hybrid Fintechs.

How Does BANKiQ Prevent It?

1. FRC (Fraud Risk Compliance)

BANKiQ’s FRC is a real-time, AI-powered solution for monitoring merchant onboarding, transaction payments, and STR reporting. With a multitude of financial detection strategies, the FRC solution plays a major role for payment aggregators, providers, and other fintech operators in monitoring and preventing financial crimes and staying compliant in real-time.

2. IFRM(Inline Fraud and Risk Management)

As a fraud and risk management prevention solution, BANKiQ’s IFRM is real-time and AI-ML-powered, addressing various aspects of financial crimes. This solution supports issuers, acquirers, payment aggregators, and fintech in diagnosing fraudulent transactions in real-time and in batches.

3. Intelligent AML

With automated Suspicious Transaction Reporting (STR) and pre-packaged compliance rules, BANKiQ’s AML solution plays a crucial role in detecting and preventing money laundering and other illicit activities. This enables banks and financial institutions to streamline compliance processes, reduce operational costs, and maintain regulatory standards.

Overall, BANKiQ is a leading fraud prevention platform that proactively functions against fraud and risk transactions. It supports banks, financial institutions, and payment service providers(PSPs) in staying ahead of fraudsters and their tactical plans for conducting financial crimes.

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