Financial Crime Tech Advisory

Kroll provides independent reviews and assessments of models to provide an objective and unbiased opinion on the adequacy and soundness of a model for its use case. This includes the validation of quantitative models as defined under the U.S. Federal Reserve Bank SR 11-07 and the validation of models under the Prudential Regulation Authority Model Risk Management Principles, in addition to assessment against many other standards across the world. In combining our broader risk management, data insights and financial crime subject matter experts, Kroll is positioned to perform in-depth reviews of various models, including customer due diligence, transaction monitoring, and watch-list filtering.

Our assessments are tailored and proportionate to the regulatory requirements and our clients’ needs, allowing for efficient and effective assessments, whether it is for independent validation, certification requirements, gap analysis of existing processes, supporting assurance reviews or implementation advisory services. Our reviews and assessments cover the suitability and conceptual soundness of the model, governance and management, model documentation, model implementation and testing, alignment of AML scenarios with the risk assessment, data integrity validation, rules evaluation and evaluation of the alert review process.

Having access to validated and integrated data is crucial in the fight against financial crime. The ability to access all of a customer’s relevant information, whether it be communications, risk assessments, transactions, etc., is imperative to regularly monitoring and assessing risks.

Additionally, having access to data is usually not good enough to make best use of it. It should be presented in a manner that is integrated and intuitive to ensure the most value is extracted, and processes are as efficient and cost-effective as possible. Our team of data governance and analytics experts work with clients and industries across the globe on these specific asks.

Monitoring and analytics play a crucial role in detecting and combating financial crime in today's evolving digital landscape. Advanced technologies, such as artificial intelligence, machine learning and big data analytics, enable institutions and regulatory bodies to analyze large and often disparate volumes of data in as close to real time as possible, identifying suspicious activities, patterns and trends that may indicate illicit behavior.

By continuously monitoring transactions, customer behavior and market activities, our solutions proactively identify potential risks, including money laundering, fraud, terrorist financing and other financial crimes.