Built on the foundations of legal entity data management, Fenergo’s Client & Counterparty Data Management solution achieves a logical, single source of data for all legal entities. It adopts a plug-and-play strategy that makes use of out-of-the-box adaptors for points of integration with leading system providers and enterprise service bus providers such as trading and core systems, as well as third party data providers, aggregators and document repositories. With these adaptors, it can proactively capture, track, manage and visualise all legal entities, as well as the complex matrices of legal entity hierarchies (e.g. interlinked companies, directors, shareholders, guarantors and beneficiaries etc.). In this way, the solution acts as a gatekeeper, shepherding data through the various interconnecting systems.
According to Marc Murphy, CEO of Fenergo, “The role of client and counterparty risk management is set to assume greater strategic importance in light of the new regulations (FATCA, Dodd-Frank, EMIR, MiFID II) coming on-stream over the coming months. As we’ve seen in our FATCA research from January, financial institutions are really struggling with gapped and siloed data, making the process of compliance much harder to achieve.
Our enhanced Client & Counterparty Data Management solution is designed to help financial institutions accurately measure risk exposure and comply with an ever-growing list of regulations. By making legal entity data as easily accessible as possible in the correct, standardised format and available on-demand, financial institutions can ensure they are meeting their obligations under all the various regulations”.
In line with its new product release, Fenergo has published a technical paper, Getting to Grips with Client & Counterparty Data Management, which examines how financial institutions can implement a fully optimised Client & Counterparty Data Management system. Once data is controlled, cleansed and connected to tis associated entities, performing the compliance and regulatory checks becomes considerably easier. The paper also reveals different strategies that should be undertaken for data take-one and data integration.