The NetReveal Managed Analytics Service for AML Compliance helps institutions improve the performance of their AML operations sustainably by combining human and machine intelligence through advanced analytics and machine learning.
The global banking industry has invested in technology and human resources during the past few years to improve their Bank Secrecy Act (BSA) and Anti-Money Laundering (AML) compliance programs. However, banks are still being used to launder money and regulators and enforcement bodies continue to press financial institutions to seek more effective and sophisticated approaches to detect and prevent fraud.
Dated detection scenarios have made AML processes labour-intensive and difficult to meet current demands. Corporate structures are becoming increasingly more diverse, digital business models are expanding, the speed and volume of transactions are on the increase, and today’s multi-border business activities makes it easier than ever for criminals to hide their illegal activities. Highly skilled compliance staff spend too much time on manual tasks such as low level data gathering rather than combatting the latest evolving financial crime scenarios.
Blending targeted analytics technology and data science skills
The Managed Analytics Service for AML Compliance solution from BAE Systems combines human and machine intelligence to improve the productivity and effectiveness of AML investigative teams, lowers false positive rates, and helps to uncover unrealised risk.
A team of dedicated domain experts can provide guidance to financial institutions and help investigative teams with parameter optimisation, rule induction, predictive modeling, negative investigations, alert prioritisation, automated model tuning services and much more.
The service is provided alongside the NetReveal Advanced Analytics Platform; a tailored financial crime analytics solution to allow powerful analytics techniques to be applied efficiently to the specific challenges of AML compliance.
The service can be tailored to specific institutions’ requirements – combining frequent, scheduled detection tuning, model management and governance, new risk and typology research, and operational monitoring. Robust audit features enable investigators to easily present clear evidence of their model risk governance approach to regulators.
The Managed Analytics Service for AML Compliance enables institutions to:
- Switch from a rules-based approach to a risk-based approach – avoid missing suspicious activity amongst a sea of low value alerts and investigations - move on from the limitations of the traditional rules-based methods for detection of suspicious activities to sophisticated analytical and machine learning models
- Reduce detection time and remove errors – improve detection effectiveness through lower False-Positive rates and increased True-Positive rates
- Modernise their compliance programme and regulator relationship – demonstrate controlled application of advanced analytics to build confidence and trust with regulators