Hey linkedln fam👋 Let us understand the concept of Reference Data Management. Have you ever thought how businesses keeps their accuracy and consistency in their data, here enters the RDM which ensures the data management and helps in decision making. What is RDM? RDM involves the management of transactional data used to categorize the transaction and provides analytical insights. It gathers wide range of data types such as security identifier, country codes etc. 🔎The process of RDM 1) Collection - Identify the types of reference data and gather reference data from internal and external sources. 2) Consolidation - The data is being consolidated and then and provide it into common model and compile it. 3) Cleansing - Here the data is being clean and the unnecessary data is being removed from the data set. 4) Coordination - Here the data is being manually check so as to avoid the exceptional error. 5) Distribution- At this stage the data is distributed internally and externally to the relevant concerned person. Examples - Security identifier It's the unique code which is assigned to the financial instrument such as stocks and bonds. For instance, ISIN (International security identification number) the ISIN for LIC is INE0J1Y01017 this is unique identifier code for securities worldwide which ensures efficient trading and reporting. RDM plays a major role in ensuring the security identifier and other reference data are accurate, consistent, and up to date which facilitates the operations and reducing risks. #Datamanagement #Refrencedata #RDM #Imarticus #investmentbank #bnymellon #jpmorgan
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RDM(Reference Data Management) RDM is ensuring accurate and consistent information across various aspects of financial operations. This includes managing reference data related to securities, counterparties, clients, and market data. *Process of RDM Collection - Collect reference data from internal systems, data vendors, industry standards organisations. Consolidation-Consolidation in reference data management refers to the process of merging or combining multiple sources or versions of reference data into a single, unified repository or dataset Cleansing - It is basically process to remove unwanted data and execute the only daya which is required. Cordination - Is reference data management which ensures that all stakeholders, systems, and processes work together effectively to maintain the accuracy, and integrity of reference Distribution-Distribute reference data to relevant stakeholders and systems within the organization as needed for operational use. Security Identifier: CUSIP Committee on Uniform Securities Identification Procedures) It's a unique identifier assigned to financial instruments, including stocks, bonds, and other securities, to facilitate trading and settlement processes. CUSIP numbers are composed of nine characters, consisting of letters and numbers, that uniquely identify each security. They are issued by the American Bankers Association (ABA) and are widely used in North America for securities trading and tracking purposes. #imarticus #imarticuslearning#RDM
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Data is one of the most valuable assets a business can have. 𝗗𝗮𝘁𝗮 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲 𝗺𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 (DLM) governs the handling, storage, and disposal of data: effective DLM is crucial for data security and operational efficiency. How to Navigate the Challenges of Data Lifecycle Management: 𝟭. Your DLM strategy must account for structured and unstructured data. 𝟮. Secure data in all stages: transmission, storage, deletion, etc. 𝟯. Put data quality controls in place to ensure integrity. 𝟰. Define data retention and deletion timeframes. I go into further detail in my blog; https://lnkd.in/eHxkZTpb
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For wealth managers to benefit fully from self-service analytics, they need a simplified data management solution that seamlessly integrates with the systems they use. This is where the LXA analytics platform comes in. It allows users to easily build a wide range of use cases across the wealth management life cycle and is pre-integrated into popular vendor platforms such as Avaloq. Learn more: https://lnkd.in/g3g4SQyj #Banking #WealthManagement #DataAnalytics
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Three Pillars of UEBA Gartner’s definition includes three primary attributes of UEBA systems: Use cases—UEBA solutions report the behavior of entities and users in a network. It detects, monitoring and alerting of anomalies. UEBA solutions need to be relevant for multiple use cases, unlike systems that perform specialized analysis such as trusted host monitoring, fraud detection, etc. Data sources—UEBA solutions can ingest data from a general data repository. Such repositories include data warehouse, data lake or Security Information and Event Management (SIEM). UEBA tools don’t place software agents directly in the IT environment to collect the data. Analytics—UEBA solutions isolate anomalies using analytic methods, including machine learning, statistical models, rules and threat signatures.
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Are outdated data systems holding your firm back? A recent study by Coalition Greenwich and Axoni reveals that 83% of large capital markets firms struggle with extract, transfer and load (ETL) solutions due to the overwhelming volume of data. Many firms participating in the study still depend on outdated methods like Excel and FTP, costing millions annually in manual data reconciliation alone. As regulatory pressures increase, financial institutions must embrace advanced data solutions “to meet changing regulatory and operational demands while also ensuring data privacy, accuracy and efficiency." It’s time to embrace advanced data solutions to stay ahead of the curve. The cost of not upgrading could be higher than you think. Source: https://lnkd.in/eb6Avwvu #CapitalMarkets #DataManagement
Outdated Data Systems Are Costly for Capital Markets Firms - Traders Magazine
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🔍💼 Delighted to explore the transformative potential of metadata management in addressing critical business questions! 🌟📊 In today's data-driven landscape, metadata management isn't just about organizing data – it's about unlocking actionable insights and solving complex business challenges. Here are some examples of questions that metadata management can solve: 1️⃣ Trading System Identification: With robust metadata management, organizations can pinpoint which trading system is responsible for executing transactions in a particular asset class. By tracking metadata attributes such as trade execution timestamps, system identifiers, and trade IDs, firms gain visibility into their trading ecosystem and optimize performance accordingly. 2️⃣ Data Service Level Agreements (SLAs): Metadata management enables organizations to monitor and enforce SLAs governing data quality and timeliness. By capturing metadata related to data sources, transmission protocols, and processing pipelines, firms can assess whether data received from a particular system meets predefined SLA criteria, ensuring compliance and operational efficiency. 3️⃣ Trade Surveillance and Regulatory Compliance: Leveraging metadata, firms can reconstruct the lifecycle of a trade or order and conduct trade surveillance for regulatory and compliance purposes. Metadata attributes such as order IDs, trader IDs, execution timestamps, and regulatory flags enable organizations to trace the journey of a trade, detect market abuse or anomalies, and demonstrate compliance with regulatory requirements. By harnessing the power of metadata management, organizations can navigate the complexities of the financial landscape with confidence, gaining actionable insights and driving strategic decision-making. 💼💡 Let's continue the dialogue on how metadata management is transforming businesses and shaping the future of data-driven innovation! 💬🚀 #MetadataManagement #DataInsights #TradingSystems #RegulatoryCompliance #LinkedInPost
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Free, naturally immutable data elements for identifying and differentiating everything, is this even possible? I have spent over 25 years trying to find an easy low cost solution to identifying duplicates in master data. Master data provides the identification and descriptions that we need to perform transactions. Duplicate master records create drag as in “the force that opposes forward motion” and just as drag does not stop a plane, a ship or a truck, it does however increase its operating costs, duplicate master data records do the same thing, they increase cost, hence they are a drag on the business. What occurred to me is that if we combine date and location of origin using the Natural Location Identifier (NLI) and date (and time), using the ISO formats, we have a naturally occurring and immutable identifier for everything, the Natural Identifier (NI). The challenge is that our systems do not currently collect date and location of origin to the detail needed for differentiation – but they could. As we have seen with corporations created as legal entities by virtue of government registration, I expect there will need to be agreement on when an object is created and that is all we really need as the when will define the where. What do you think?
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BNP Paribas - Securities Services launches new suite of data management services The services, developed in collaboration with NeoXam, are designed to support decision-making by integrating diverse data sources into a unified framework.
BNP Paribas launches new suite of data management services
globalcustodian.com
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Data is one of the most valuable assets a business can have. Managing this data throughout its lifecycle can be challenging. Data lifecycle management (DLM) governs the handling, storage, and disposal of data. Effective DLM is crucial for data security and operational efficiency. How to Navigate the Challenges of Data Lifecycle Management Your DLM strategy must account for both structured and unstructured data. Secure data in all stages: transmission, storage, deletion, etc. Put data quality controls in place to ensure integrity. Define data retention and deletion timeframes. Reach out to us today for help with DLM solutions. https://lnkd.in/ggtfmSu9 #DataLifecycle #DataManagement #BusinessIntelligence #DataGovernance #DataStrategy #LifecycleManagement #LifecycleGovernance #DataSecurity We would love to hear from you! 661-750-8400 979 W Valley Blvd Ste 2 Tehachapi, CA 93561
Navigating the Challenges of Data Lifecycle Management
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🚀 Accelerate Your Data Compliance with Orion Governance's EIIG! 🚀 Struggling with data compliance? 🌐 Meet the Enterprise Information Intelligence Graph (EIIG) by Orion Governance – your ultimate solution for streamlined compliance! 🔍 Why EIIG? - Automated detailed data lineage for accurate traceability - Real-time quality assessment and monitoring - Comprehensive support for 70+ technologies Say goodbye to manual efforts and hello to efficiency and accuracy! Ensure your data meets regulatory standards effortlessly. Ready to take control of your data compliance? Let EIIG lead the way! 💪 Download our free case study on how EIIG helps enterprises accelerate data governance: [link to case study] #DataCompliance #DataGovernance #OrionGovernance #EIIG #DataFabric #DataLineage
Success Story: Enterprise Accelerates Data Governance with Orion Governance
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