Leveraging Big Data & Advanced Analytics for Financial Crime Detection

Big data refers to the vast and complex sets of structured, semi-structured, and unstructured data that organisations generate and collect daily. These datasets are too large for traditional data-processing tools to manage effectively. Big data analytics involves using advanced techniques to extract meaningful insights, identify patterns, and support decision-making.

Advanced analytics encompasses sophisticated methods such as machine learning, statistical modelling, and predictive analysis. By applying these techniques, financial institutions can detect anomalies, uncover hidden relationships, and enhance risk management efforts. In the context of financial crime, big data and advanced analytics enable institutions to analyse vast transaction datasets, improving fraud detection and regulatory compliance.

Our Client

Our client is a leading global banking and financial services institution, headquartered in both London and New York. With a presence in over 50 countries and more than 48 million customers worldwide, the bank operates across retail, corporate, and investment banking sectors.

Financial crime analytics plays a crucial role across the organisation, from risk assessment and detection engines to investigative tools and reporting. Leveraging big data and advanced analytics, the bank aims to better quantify and categorise risk exposure, assess the effectiveness of its financial crime controls, and detect and prevent illicit activities.

The Challenge

Traditionally, financial institutions structured their transactional data by country and business unit. However, this siloed approach is ineffective in today's financial crime landscape. Criminal networks operate globally, rapidly adapting their tactics to bypass detection mechanisms.

The client processed vast volumes of payment data daily across multiple jurisdictions. However, the fragmented nature of their data hindered their ability to track illicit financial flows across borders. The bank needed a centralised, scalable data infrastructure to:

• Aggregate and standardise payment data globally.

• Enable comprehensive analysis of transaction flows.

• Provide real-time insights into suspicious financial activities.

Without such capabilities, criminals, sanctions evaders, and money launderers could exploit gaps in monitoring, exposing the institution to regulatory and reputational risks.

Data is like garbage. You'd better know what you are going to do with it before you collect it. ~ Mark Twain

Our Approach

To address these challenges, we developed a robust and scalable data solution designed to unify global payment data and enhance financial crime detection. By integrating advanced analytics, optimised data architecture, and user-friendly interfaces, our solution enables financial institutions to detect, investigate, and prevent financial crime more effectively.

• Data Integration & Standardisation: We extracted payment information from core banking systems using SWIFT MT and ISO 20022 message formats, ensuring a comprehensive capture of transaction data across multiple financial institutions. This standardised approach facilitates seamless data consolidation and analysis, allowing for more effective monitoring of payment flows. To accommodate regulatory constraints, we established a centralised data warehouse for data storage and processing, while implementing satellite databases in jurisdictions where cross-border data export was restricted. This ensured compliance with data sovereignty laws while maintaining global oversight of financial transactions.

  
  

• Optimised Data Architecture: Our analytics-driven infrastructure was designed to support both predefined and ad-hoc queries, providing financial crime teams with the flexibility to conduct targeted investigations. The system enables searches based on various parameters, including customer profiles, transaction values, jurisdictions, currency flows, and corridor-specific patterns. This multi-dimensional search capability enhances the ability to detect suspicious activity and identify emerging financial crime threats.

  
  

• Advanced Search & Analytical Capabilities: We developed intuitive search functionalities that allow users to conduct free-text searches for identical or similar phrases, facilitating the identification of transaction patterns indicative of illicit activity. By leveraging advanced analytics, financial crime teams can detect anomalies, uncover hidden networks, and investigate suspicious activities more effectively. This proactive approach enhances the detection of money laundering, fraud, and other financial crimes, enabling faster and more informed decision-making.

  
  

• User-Centric Design: Our solution was designed with user experience in mind, providing an interactive interface tailored to the needs of financial crime teams, risk officers, and internal auditors. The platform allows users to explore and analyse data intuitively, ensuring seamless access to critical financial intelligence. Additionally, we implemented rigorous data governance and privacy controls to ensure compliance with regulatory requirements while maintaining transparency and accessibility for authorised stakeholders.

Key Benefits & Measurable Outcomes of Using Big Data & Advanced Analytics

The adoption of big data analytics enabled our client to significantly enhance financial crime detection and risk management. By integrating advanced analytics and a centralised data solution, they transitioned from a fragmented monitoring approach to a comprehensive, intelligence-driven strategy. This transformation allowed for more efficient detection, investigation, and regulatory compliance, strengthening their overall resilience against financial threats.

• Enhanced Detection Capabilities: By implementing real-time analysis of global transactions, our client improved their ability to identify suspicious activities such as money laundering, fraud, and sanctions violations. The reduction in false positives allowed investigators to focus on genuine threats, improving operational efficiency and investigative effectiveness. Additionally, the ability to analyse cross-border transaction flows provided a more holistic view of financial crime risks.

• Empowered Compliance & Audit Teams: With intuitive, self-service analytical tools, non-traditional users such as risk officers, internal auditors, and compliance teams could independently assess the effectiveness of financial crime controls and identify weaknesses. This enhanced oversight improved internal risk management and enabled a more proactive response to emerging financial crime threats.

• Faster Investigations: By unifying transaction data into a centralised repository and implementing advanced search and analytics functionalities, our client significantly streamlined their investigative processes. The time taken to identify and respond to suspicious transactions was reduced, enabling more timely interventions and better risk mitigation.

• Improved Compliance & Reporting: With enhanced accessibility to financial crime intelligence in one centralised data warehouse, our client respond swiftly to compliance inquiries and strengthened their ability to meet regulatory expectations. Automated reporting capabilities reduced the manual workload associated with regulatory submissions and audits, ensuring a more efficient and accurate reporting process.

  
  

• Stronger Risk Mitigation: Through continuous monitoring of transaction patterns and risk indicators, our client was able to implement targeted improvements in financial crime prevention. This proactive approach reduced the likelihood of financial crime incidents, ensuring a more secure and resilient financial environment.

  
  

• Scalable & Future-Proof Infrastructure: The centralised system was designed to accommodate increasing data volumes and adapt seamlessly to evolving regulatory requirements. This ensured long-term sustainability while maintaining operational continuity and compliance with jurisdiction-specific data governance policies.

  
  

By leveraging our big data-driven solution, our client successfully transitioned to an intelligence-led financial crime detection strategy. This transformation enhanced their ability to detect, investigate, and prevent financial crime while ensuring regulatory compliance and strengthening overall risk management.

Need Expert Support?

If your organisation faces similar challenges in financial crime detection, we can help. Our expertise in big data integration, advanced analytics, and compliance solutions enables financial institutions to strengthen their risk management frameworks.

Contact us today to explore how we can support your organisation in building a more robust and effective financial crime detection strategy.