Blog Contact +1.212.798.7100 Company Solutions Services Resources Request a Demo Video Library Artificial Intelligence & Machine Learning use Cases in Data Operations GoldenSource is advancing on its journey towards fully fledged, productized artificial Intelligence (AI) and machine learning (ML) capabilities that will transform use cases in data operations. In this update, Tom Stock, SVP Product Management at GoldenSource, looks at a variety of use cases for which GoldenSource is developing capabilities. Take a look and see if you’d like to join a trial, put your data through the algorithms and see how the new tooling can help improve your productivity. Legal Entity Hierarchies for Central Limit Management Traditionally, each trading system in an investment bank has supported a specific asset classes or regions. Limits were managed within each trading system, creating fragmentation of the view of limits for any given legal entity. With no overall view of limits for a counterparty, oversight and control are not possible. Legal entity hierarchies are necessary to be effective at managing trading limits, currency limits and credit limits across the bank. Limit management belongs at the entity level, so the trend is now to manage legal entity hierarchies centrally, manage the limits centrally and then distribute those limits to the trading systems. But banks are struggling to achieve this capability. Neill Vanlint, Global Head of Sales & Client Operations, looks at the way forward in managing legal entity hierarchies Data Warehousing and MDM for Investment Managers With the outsourcing trend continuing, buy side firms are benefitting from best of breed solutions and services for their business. But they’re losing a connected, single view of all their investment data. To support all investment management operating models, a master data management (MDM) platform needs to be able to work as a master or a slave, or both at the same time. Hear Prashant Kumar, Head of Business Development at GoldenSource, discuss what’s driving the interest in investment data warehousing and MDM among investment managers. If you’re in a hurry, here is the timestamped content: 0:03 – The trend for outsourcing among investment managers 0:20 – Losing the single view of investment data 0:32 – An investment data warehouse for a single view across silos 0:37 – Insourcing functions such as pricing, corporate actions or fund administration 0:55 – Marrying environmental, social and governance (ESG) metrics with outsourced data 1:11 – Managing investment in differing operational environments 1:23 – MDM as master and slave 1:27 – MDM as a master for investment managers managing their portfolio internally 1:40 – MDM as a slave for outsourced or external functions 1:49 – MDM as both master and slave in the same instance GoldenSource 101: Preparing Data for Financial Market Models Front office, risk and finance models and their associated calculations have traditionally been managed separately from the data that feeds them. This is changing, because preparing data for financial market models – validating, calibrating and transforming market data – requires an understanding of how that data interacts with the market models and calculations that run through them. Hear Charlie Brown, Head of Market & Risk Solutions at GoldenSource, discuss the thinking that data professionals are putting into new approaches and standards that will unlock the value of market data across financial services organizations. If you’re in a hurry, here is the timestamped content: 0:09 – The importance of data for FRTB 0:50 – Redefining the boundary between data and financial market calculations 1:13 – Front Office vs Finance & Risk calculations 2:13 – Front Office calculations 2:40 – Finance & Risk calculations 3:18 – Understanding how the data interacts with the calculations 4:41 – Calibrating market data 5:38 – Transforming data for use in pricing models 6:31 – Data processes for calculating Daily P&L 7:51 – Standardized approaches evolving across the financial markets industry 8:19 – Enterprise use of time-series data 9:25 – Leveraging the cost of FRTB for broader enterprise benefits 10:00 – The data professional’s approach to complexity within models GoldenSource Talks: How does AI naturally lend itself to financial data management? Data management challenges are well suited to being addressed by artificial intelligence (AI), machine learning (ML) and natural language processing (NLP). Validation, exception management, mapping and matching/entity resolution are typical examples. Hear Tom Stock, SVP Product Management at GoldenSource, discuss the applications of AI, ML and NLP and also argue the case for keeping humans in the loop. If you’re in a hurry, here is the timestamped content: 0:31– Data validation – use case 1:00– Data mapping use case 1:46– Exception management use case 2:21– Matching (e.g. entity resolution) use case 3:02– (NLP) analytics on alternative data 3:47– NLP for extracting meaning from unstructured data 4:23– Data validation example – artificial intelligence (AI) to identify data anomalies 6:03– Analytics using time-sensitive alternative data 6:46– Empowering users to interpret unstructured data 7:14– Data quality driving adoption of AI and machine learning (ML) 7:47– Better data, higher quality, lower cost 8:20– Algorithms enabling automation and savings in data mapping and exception management 8:53– More data for better investment management decisions 9:59– The human in the loop GoldenSource Talks: Improving Data Quality and Reducing Costs in Financial Services There are enormous opportunities for both improving data quality and reducing costs across all of our businesses. Find out the latest ways in which GoldenSource is helping its clients. GoldenSource 101: Intro to OnDemand – Achieving SLAs Through Help Desk and Ticket Management When moving to the cloud, you need assurance that the help desk will meet your service level agreements. With business users demanding stringent service levels from operations teams, rapid response to help desk requests is more important than ever. Listen to Jon Hallam, Head of OnDemand at GoldenSource, explain how GoldenSource ensures that all its hosted and managed services clients get swift support from dedicated staff. GoldenSource 101: Intro to OnDemand – Hosting Services & Oracle License Support There’s more to hosting than your system running on a server that’s managed by someone else. Availability, latency, security, certification, contingency, location, 3rd party licensing and total cost of ownership (TCO) all come into consideration. Listen to Jon Hallam, Head of OnDemand at GoldenSource, explain the important services associated with hosting. GoldenSource Talks: Quant Library Integration Integrating your front office quant library with data management and IT processes and governance can satisfy data lineage, transparency and all calibration needs, from the front office to the back office. Hear Charlie Browne, Head of Risk and Market Data Solutions at GoldenSource, discuss how this approach can help grow profits in an environment of ever-expanding regulations. If you’re in a hurry, here is the timestamped content: 0:10 – Redefining the boundaries between data management and financial calculations 0:39 – Front office – the traditional driver of innovation in calculations 1:15 – No longer making money by building complexity into products and valuation methods 1:55 – Innovation, transparency, lineage and governance 2:31 – MiFID II, FRTB and BCBS 239 – transparency of front office, risk, finance and IPV calculations 3:13 – Quant library integration 4:01 – Industry use cases for data calibration 5:05 – Transforming raw market data to derived market data 5:39 – Side by side views of raw rates and calibrated rates for curves 6:59 – The GoldenSource strength GoldenSource 101: Intro to OnDemand – Business Assistance Data operations teams require real time assistance from their suppliers in order to meet the service level agreements (SLAs) they have with their internal customers. Listen to Jon Hallam, Head of OnDemand at GoldenSource, share examples of how firms benefit from having business analysts (BAs) immediately available to help achieve critical business deadlines. GoldenSource 101: Intro to OnDemand – Production Monitoring When a production system is running in the cloud, its operation and maintenance requires monitoring, and faults need to be resolved within agreed service levels. From go-live support, to environment tuning and patch deployment, production monitoring is key to ensure that data deadlines are met and quality is maintained. Listen to Adam Cummings, OnDemand Manager EMEA, explain the essentials of Production Monitoring. GoldenSource 101: Intro to OnDemand - Production Change Requests Changes to your data management system, such as changes to workflows and the related user interface screens, or the need to publish data to a new downstream system, are inevitable. Listen to Jon Hallam, VP and Head of OnDemand at GoldenSource, talk through the fundamentals of Production Change Requests. GoldenSource Talks: BCBS 239 It seems that the tactical solutions adopted by D-SIBs and G-SIBs to put into practice the BCBS 239 principles have not delivered the benefits they should have. Neill Vanlint, Global Head of Sales & Client Operations looks at the fundamental intentions of BCBS 239, and what is required to fulfil them and benefit from the operational efficiency of streamlined instrument and counterparty data management along with the associated risk reporting. GoldenSource Talks: Corporate Actions Lifecycles Managing corporate actions announcements well is a challenge for all players in the asset servicing space. GoldenSource’s Neill Vanlint, Global Head of Sales & Client Operations, sheds light on the elements of the corporate actions lifecycle and the challenges of managing it well. GoldenSource 101: Everything you need to know about FRTB data in 7 minutes FRTB data challenges need to be better understood by risk and finance departments and by the FRTB project teams working for them. Hear from our own Charlie Browne about how to prepare for the FRTB internal models approach (IMA), and the challenges in risk factor modellability and time series data that will prompt change. GoldenSource 101: Market Data Management These days, market data management demands speed and scalability. For FRTB, data quality at volume is the only way to go. Whether you’re handling exceptions, analyzing curves or comparing time series, you need a system that makes it easy to get the right data for your risk calculations, first time, every time. GoldenSource Talks: OTC Derivative Data A few years back, some of our clients came to us looking to manage, value, and store Over-the-Counter (OTC) Derivatives. So we heard them out, and built out models for those structured products to keep up with the industry’s business objectives and regulatory challenges. In this short video Neill Vanlint, Global Head of Sales & Client Operations, talks about how we got here, what’s driving the change, and the regulatory impact – specifically around MiFID II. If you’re in a hurry, the content is timestamped here: 0:11 – How has OTC data been traditionally stored? 1:17 – What is driving the need for change? 2:20 – How has MiFID II impacted OTC product stamping? GoldenSource 101: Data Management in The Cloud Data management in the cloud isn’t new, but if it’s new to you, this video will help. The question we get asked most by firms considering migrating their data management capabilities to the cloud is, “How?” So, here’s how. Here’s the process we’ll lead you through to ensure your data management solution is up and running in the cloud and fully integrated with all your systems. Dealing with Data Lineage Data lineage is a phrase that’s used often, but the words only convey the concept. What capabilities are people most often referring to when they say, “Data lineage”, and what are the day-to-day operational uses for such a capability? Hear from Amy Anderson, Head of Professional Services, Americas, at GoldenSource, some examples of data lineage in the GoldenSource EDM platform and the ways it supports effective data operations. Data Management for FRTB Success Banks will not only need to run the FRTB calculations, they’ll need to show that they did so with the right data in a way that conforms to the FRTB specifications. This will require complete, accurate and validated market and risk data coupled with auditable processes. The industry is comfortable with the calculations, it’s their data management capabilities that will determine success with FRTB. Hear from Charlie Browne, Head of Market Data & Risk Solutions at GoldenSource, how a data driven, bottom up approach is key for FRTB preparations. If you’re in a hurry, the content is timestamped here: 0:02 – The data approach to calculating marker risk capital 0:17 – The FRTB Calculations 0:45 – Why is FRTB important? 1:20 – The GoldenSource rationale 1:36 – The calculation is king – a false industry perception 2:05 – The GoldenSource end-to-end FRTB solution 2:46 – Prerequisites for calculating capital 3:09 – Summary – the data-driven approach GoldenSource 101: Getting started with investment data management as a service Asset managers and asset owners often ask to be guided through the process of getting started with data management as a service. Hear Jon Hallam, VP OnDemand & Global Support Services at GoldenSource, address the most common topics we are asked to address. Which data types should be set up first, how will data be loaded from external and internal sources, how will data be made available to users and systems, and how will we know that the service is delivering as good or better data accuracy and quality than our old methods? If you’re in a hurry, the content is timestamped here: 0:04 – What is the ideal sequence of data types to migrate to the cloud? 0:32 – How can I ingest the files? 1:02 – How would I push files out to my users and systems? 1:46 – How do we test that the system has been setup successfully? The Future of EDM Utilities Data utilities are a hot and divisive topic, with adoption levels at only 1% of the industry, according to a recent FIMA report. Why haven’t they been adopted? What would make them more appealing to financial services firms? Hear from Prashant Kumar, SVP Business Development for GoldenSource, what might make the difference. Regulatory Data Management Since the financial crisis, we’ve seen a growth in regulatory compliance and reporting for both the buy and the sell side. The data management response to regulation is often to break it up into teams that drill back from the actual requirement into the implications on their operation, but because these teams are distinct, it tends to lead to siloed solutions. Hear from Neill Vanlint, MD Global Head of Sales and Client Operations at GoldenSource on how to avoid digging up the same regulatory road up multiple times on the route to regulatory compliance. Data Management Across all Domains The lack of data management integration between risk and finance has caused market data discrepancies that not only require significant reconciliation efforts, but also create difficulties in cross reporting. Hear from Tom Stock, SVP Product Management at GoldenSource, how more and more firms are looking towards rationalizing their data management systems and processes to harmonise data used across multiple domains and to avoid having to bring in that data and validate it multiple times. Multiple Data Feeds for Regulatory & Business Needs In order to have the right data, any capital firm will need data feeds from multiple vendors. According to a recent FIMA report 28% of capital markets businesses expect the number and complexity of new data feeds to challenge the scalability and flexibility of their systems within the next 2 years. Hear from Stuart Smith, VP Client Operations EMEA & APAC at GoldenSource, who discusses the key to managing the end to end data processes that support the main drivers of data growth identified in the FIMA report, namely complying with regulations (35%) and taking on new areas of business (27%). Driving the Maturity of EDM Over the last few years, many capital markets firms have matured to an enterprise-wide data management approach. In 2016, for the first time, a majority of capital market firms, 54%, said they have such an approach in place, according to a recent FIMA report. Hear from John H. Eley, CEO at GoldenSource, what’s driving this maturity and what the next level of evolution might be. Cloud Services at GoldenSource Cloud services for data management are being widely adopted now that historical challenges and concerns about security, extensibility and data centre locations have been addressed. How far has GoldenSource OnDemand come in recent times? What changes in the industry are prompting firms to consider cloud services? And what’s in it for smaller capital markets participants? Hear from Jon Hallam, VP OnDemand Services at GoldenSource, the journey that GoldenSource is taking with its clients. HAVE A QUESTION? 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