Financial Crime Data Analytics in Spain: A Growing Need for Change
The fight against financial crime has become increasingly complex, with rising compliance requirements and vast amounts of data. In Spain, the situation is no different, with financial services firms facing stringent regulatory demands.
The Cost of Financial Crime
According to a 2018 Refinitiv Survey, combating global financial crime activity costs an estimated US$1.3 trillion annually.
Challenges Faced by Spanish Banks
- Trade institutions struggle to meet compliance demands due to manual processes and legacy technologies.
- Risk alert backlogs grow faster than operations teams can handle.
- Manual regulatory reporting is inefficient and unable to keep pace with the volume of data being produced.
The Role of Advanced Analytics
Financial institutions are shifting towards more efficient and effective ways of handling regulatory reporting. Advanced data and analytics techniques, such as artificial intelligence, machine learning, natural language processing, and cognitive automation, can accelerate or automate labor-intensive work, reducing operational costs and allowing people to focus on preventative interventions.
Examples of Innovative Solutions
- Transaction Monitoring (TM): Machine learning models enrich TM data, improving the accuracy of risk detection and reducing false positives.
- Sanctions Screening: Emerging AI and analytical methods address operational efficiency issues related to case investigation.
The Future of Financial Crime Prevention
Financial service organizations are being challenged both internally and externally in keeping up with the demands of mitigating financial crime risks. To align operational effectiveness, they must seek innovative ways to address issues surrounding SMR conversion rates, KYC due diligence, and screening alert management.
Key Takeaways
- Complete and accurate data is essential for resolving these issues.
- An uplift in data quality will have immediate effects on the performance of existing monitoring and screening engines.
- Advanced analytics and cognitive techniques can help filter out false positives and improve inefficiencies in existing investigative processes.