Slovenia Tackles Financial Crime with Advanced Data Analytics
Ljubljana, Slovenia - In an effort to combat the growing threat of financial crime in Slovenia, local banks and financial institutions are turning to advanced data analytics as a means of staying ahead of the curve.
Financial Crime Costs Estimated at $1.3 Trillion Annually
According to a recent Refinitiv Survey, global financial crime activity costs an estimated US$1.3 trillion annually. Fines imposed by regulators for non-compliance with Anti-Money Laundering (AML), Know Your Customer (KYC) and Sanctions regulations have reached over US$26 billion in the last decade.
Slovenian Financial Institutions Invest in Advanced Data Analytics
In response to these mounting challenges, Slovenian financial institutions are investing in innovative technologies and techniques to improve their regulatory compliance and risk management capabilities. Advanced data analytics is emerging as a key tool in this fight, enabling financial institutions to more effectively identify suspicious activity, enhance customer due diligence, and optimize their screening processes.
Key Areas of Adoption
- Transaction Monitoring: Machine learning models can enrich alerts and boost Suspicious Matter Report (SMR) conversion rates by predicting AML scenarios before they occur.
- Know Your Customer (KYC) Verification: Advanced analytics enable a more holistic view of the customer, enhancing data used to conduct due diligence and providing a more contextual basis for determining customer risk.
- Sanctions Screening: By tuning the matching and filtering performance of screening engines with high-quality data, financial institutions can substantially lower the number of alerts to be safely dispositioned, freeing up investigators to focus on those with the greatest likelihood of being true positives.
Benefits of Advanced Data Analytics
By leveraging advanced analytics and cognitive techniques such as AI, machine learning, and automation, Slovenian financial institutions can:
- Drive efficiencies
- Reduce operational costs
- More effectively identify potential criminal behavior
Quote from EY Asia-Pacific FSO Data & Analytics Director
“Machine learning models not only accelerate the closure of a risk alert backlog, but in most cases have a higher degree of accuracy. By leveraging advanced analytics, financial institutions can reduce operational workloads, enhance customer experience, and lower the cost of operational risk management.”
Quote from EY Asia-Pacific FSO Data & Analytics Partner
“When I talk to clients, they believe that our combination of professional skills and advanced data and analytics products are what help them accelerate results. By adopting a data-driven approach to fighting financial crime, Slovenian banks can stay one step ahead of the criminal element and protect their customers’ interests.”