Financial institutions therefore need tools that can detect risks in real time without disrupting the customer experience.
BPC’s SmartVista AI-powered Fraud Management platform is designed to meet this challenge through an AI/ML-driven, enterprise-wide approach. Built for full online real-time decisioning across cards, accounts, and digital channels, the platform enables banks to monitor and respond to suspicious activity as it happens, while also supporting near-online and offline analysis where required. Using artificial intelligence and link analysis, the system identifies anomalies across card-present and card-not-present transactions, mobile and internet banking, merchant payments, and e-commerce flows. Its omnichannel coverage extends across card issuing and acquiring, token provisioning, QR payments, e-commerce, mobile and internet banking, wallet payments, account-based payments, and instant payments, creating a unified 360-degree view of financial and non-financial events across the organization.
Instead of relying on static rules or manual reviews, SmartVista combines rules, list checks, behavioral profiling, and ML scoring in a single decisioning framework, who is making the payment, through which channel, and whether the activity aligns with the customer’s usual profile. It uses both supervised and unsupervised models for fraud detection, anomaly identification, and adaptive risk scoring, allowing the system to react dynamically as customer behavior changes in real time. This enables banks to detect and stop suspicious activity before funds are dispersed, while allowing legitimate transactions to proceed smoothly. The platform can also generate new rule suggestions automatically based on emerging fraud patterns, reducing the time needed to contain new attack vectors. Fraud teams can configure rules, workflows, and even UI elements rapidly, which is increasingly important as fraud typologies evolve faster and compliance expectations continue to tighten.
BPC’s checkout layout on PC. Photo courtesy of BPC |
The platform’s low-code architecture allows fraud teams to rapidly adapt strategies, test new rules against historical data, and deploy additional identity or biometric checks when needed. This flexibility is critical as fraud patterns evolve quickly and regulatory requirements continue to change. A further differentiator is SVFM’s graph-based link analysis capability, which helps institutions move beyond isolated alerts and identify coordinated fraud activity. Using a dedicated graph database, the platform maps relationships between entities such as customers, cards, accounts, devices, merchants, and terminals. Analysts can then visualize clusters, hubs, and fraud-connected paths directly within the interface, making it easier to uncover mule networks, organized attack patterns, and hidden links between seemingly unrelated events. An embedded AI assistant further accelerates investigation and decision-making by helping analysts interpret alert context, navigate related activity, and speed up triage. The result is not only faster fraud detection but also more consistent and scalable fraud operations.
SmartVista can be deployed either on-premise or in the cloud, enabling institutions to comply with local data-residency rules while benefiting from continuous system upgrades, advanced analytics, and scalable processing power. This ensures stronger protection without compromising transaction speed.
BPC has implemented SmartVista for financial institutions across Asia Pacific, Europe, and other regions. In Malaysia, Co-opbank Pertama (CBP) used a cloud-based deployment to move from manual review processes toward near real-time fraud monitoring. The bank also introduced a machine-learning module into its defence framework, using historical fraud data to refine detection mechanisms and improve the protection of customer assets. To support effective adoption, BPC provided training services that enabled the bank’s teams to make full use of the platform’s capabilities. As a result, CBP was able to meet Bank Negara Malaysia’s fraud protection mandate while strengthening customer confidence in its mobile and internet banking services. The bank has reported significant improvements in fraud detection and in blocking suspicious transactions before losses occur.
In Pakistan, Meezan Bank and Samba Bank strengthened fraud controls across their expanding digital ecosystems. The implementation in Meezan created a unified, AI-driven fraud framework spanning real-time prevention, omnichannel monitoring, and regulatory compliance. Key capabilities included AI/ML-powered analytics, link analysis, and a flexible, user-configurable rule engine, along with alerts and notifications delivered through SMS, email, and push channels to improve transparency for both the bank and its customers. Since deployment, the solution has blocked 1.5 million fraudulent POS attempts worth PKR 2.5 trillion and 2 million e-commerce attacks worth PKR 91 billion, while keeping false positives low. This demonstrates how enterprise fraud management can scale with digital growth without undermining the customer experience. While in Europe, Bulgaria’s DSK Bank consolidated fraud management into a single enterprise-grade platform, achieving savings of more than US$4 million across its channels.
Across these markets, institutions report similar outcomes: a shift toward AI-powered detection, measurable reductions in fraud exposure, and increased customer confidence in digital services.
By combining enterprise-wide visibility, real-time analytics, and rapid configuration, SmartVista helps financial organizations modernize their defenses against increasingly coordinated fraud attacks, supporting both operational efficiency and the broader goal of building a secure, trusted digital finance environment.
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