Insights
Analytiqal shares its insights, experience and thought-leadership through frequent posts on this page to help organizations thrive and expand their thinking. Our content is targeted to those business leaders looking for hands-on discussions and solutions to challenges in data science, AI, financial crime, and regulatory domains. Feel free to contact us if you want to discuss any of these in more detail.
Featured insight
ESG Meets AML: Tracing Value-Chain Risks with Data
Money laundering doesn’t happen in a vacuum — it hides behind other crimes. With the EU tying ESG offences directly into AML rules, these once-separate compliance worlds are converging fast. This article explores how firms can move beyond box-ticking by linking ESG and AML through value-chain data. From batteries to furniture, supply chains reveal risks that impact both sustainability disclosures and financial-crime exposure. Our open-source methodology shows how to trace those risks and transla…
Read MoreDive into our thoughtware
ESG Meets AML: Tracing Value-Chain Risks with Data
Money laundering doesn’t happen in a vacuum — it hides behind other crimes. With the EU tying ESG offences directly into AML rules, these once-separate compliance worlds are converging fast. This article explores how firms can move beyond box-ticking by linking ESG and AML through value-chain data. From batteries to furniture, supply chains reveal risks that impact both sustainability disclosures …
Read More
Preparing for AMLR & AMLA: our callouts
The EU’s Anti-Money Laundering Regulation (AMLR) and the creation of the new Anti-Money Laundering Authority (AMLA) mark the largest overhaul of Europe’s financial crime compliance regime in two decades. For executives in banks, payment institutions and crypto-asset service providers (CASPs), the shift is not to be underestimated. In this article, we call out a number of areas where the AMLR bri…
Read More
Counterparty FEC risks: open data, sanctions, and shell companies
Open-source data can provide valuable insights into counterparty financial economic crime (FEC) risks, complementing traditional methods for identifying FEC exposures. By analyzing company registries, sanctions lists, and geographic data, institutions can detect key risk indicators, such as shell companies and indirect links to sanctioned entities. This approach enhances the ability to uncover hid…
Read More
Explainable AI: unlocking value in FEC operations
Adherence to AML regulations within the EU has ensured that financial institutions generate a constant stream of financial crime risk signals from various processes (e.g. Transaction Monitoring, client due diligence reviews). Contrary to industry standard black box models, Explainable predictive models can help to streamline the operational processes to address these risk signals by allowing insig…
Read MoreCommunications on Analytiqal.nl contain general information only and are intended solely for informational purposes. Analytiqal and its related entities do not, through this communication, provide professional advice or services. Before making any financial, risk-related, or business decisions, it is advisable to seek the guidance of a qualified professional adviser contracted for such purposes. This website contains links to third-party sites that are not under the control of Analytiqal or its affiliates. Reference to such information does not imply association with, endorsement of, approval of the site or its operators, as Analytiqal or its affiliates are not responsible for the products, services, or other content hosted therein.