
By exposing hidden ownership‑driven sanctions risk, the dataset helps banks and asset managers avoid regulatory breaches and costly fines, improving compliance efficiency. It also supports more accurate risk pricing across capital‑raising and restructuring transactions.
Sanctions compliance has become a moving target for global financial institutions, as regulators increasingly focus on indirect exposure through complex corporate structures. Traditional watch‑list screening often misses securities tied to sanctioned entities via parent‑company ownership, leaving firms vulnerable to inadvertent violations. The rise of cross‑border capital formation and corporate restructuring amplifies this challenge, prompting a demand for data that can trace risk through multiple layers of control.
LSEG’s new Sanctioned Securities Data File, built with BIGTXN, addresses the gap by mapping each sanction designation directly to the underlying financial instruments listed on the World‑Check platform. The dataset provides granular, instrument‑level insight, flagging securities that are not themselves sanctioned but are owned or controlled by designated parties. Seamless API integration allows compliance, risk, and trading teams to embed this intelligence into existing workflows, automating detection and reducing manual investigation time. Early analysis shows that roughly one‑third of exposure originates from these ownership links, and about 60% of flagged instruments remain actively traded, underscoring the operational relevance.
For banks, asset managers, and custodians, the ability to pinpoint hidden sanctions risk translates into stronger regulatory defensibility and lower potential fines. It also enhances pricing accuracy for capital‑raising deals and restructuring transactions, where undisclosed exposure can affect deal terms. As regulators continue to broaden the scope of sanctions regimes, tools like LSEG’s data file will become essential components of a proactive compliance strategy, driving industry standards toward more transparent and data‑driven risk management.
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