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Mark Hepsworth

Mark Hepsworth,
– CEO, Alveo

Welcome to the Autumn edition of our Bulletin in which we update you on what is happening at Alveo. 

I am not sure we are yet in a post-Covid world but as we have moved to the next phase of living with this pandemic, we are seeing a very busy environment.  We see both new and existing clients looking into the future and investing in market data infrastructure as they see growing data volumes, more data sources to integrate and business users who are increasingly demanding. What we have also seen the pandemic drive is clients accelerating cloud adoption and the use of open-source technologies to improve productivity.  

The two major themes of our product roadmap continue to be business user self-service and enabling Alveo to easily operate in the cloud.  Our focus on the cloud is both with new products and our core products like Prime (formerly AC Server) and it is exciting to see many clients now operating Alveo in the cloud. 

If you have not seen our new Ops360 UI, please take a look. As well as being a web-based, modern and intuitive user experience, it now has significantly more functionality than our Desktop product. In the next phase of functionality, we will be providing more data quality analytics, as well as features that help clients with market data tracking and efficiently maximizing market data ROI. 

Alpha (formerly ACX) has been a major product initiative in recent years as we have provided clients with an enhanced data warehouse extension to Prime. From an operational efficiency and resilience perspective we believe data mastering and business user data access should run as separate components which Alpha facilitates within an open-source environment.  We are now releasing the next phase of Alpha which focuses on distribution (Alpha Distribution) and replaces and enhances the functionality currently within our Connect product.  Alpha Distribution materially reduces the cost of last-mile integration which often makes up the bulk of data management projects.  

ESG is a major trend currently impacting financial services and all of us working in this industry probably feel good that we are getting involved in something that will help future generations. We believe ESG will be a major data management requirement as it requires firms to onboard and integrate multiple data sources and then manipulate this data and create proprietary ratings and analytics, as well as meet regulatory and investor reporting requirements. What we have seen to date is clients accelerating the onboarding and operationalizing of ESG data. This has been primarily on the buy-side so far driven by SFDR, but our sell-side clients are also looking at ESG.  We have incorporated ESG data into Alveo from major data vendors such as Bloomberg, Refinitiv, RepRisk and ICE Data Services and are pleased to announce our recent collaboration with FactSet on ESG and other data types. We have also announced a partnership with Cognizant focusing on comprehensive ESG data management solutions for financial services firms.  

We continue to expand our managed service offering, PaSS where we offer clients host, run and change options for the Alveo software. I believe managed services is central to the future of Alveo as clients are increasingly looking to simplify their operations by using vendors to cover more of their requirements rather than handling everything inhouse.  

Finally, I am pleased to welcome a number of new clients who are joining our user community, including from the buy-side, sell-side and market infrastructure segments. 

I hope you find the content below useful and please let us have any questions or feedback. Should you require further information, please don’t hesitate to contact us by contacting your account manager or directly contacting me at mhepsworth@alveotech.com. 

Data. Delivered.

Taking out last-mile integration cost

 

Data distribution, or last-mile integration, typically represents over 80% of the cost of data management projects. Financial services firms typically have a very diverse application and reporting landscape. Through introducing an easy and flexible way of onboarding new systems, Alpha provides faster access to quality vetted data. 

In Alpha, users easily onboard new downstream systems and control who gets what through managing subscription lists and setting up new data shapes. Alpha includes a REST API and an easy-to-use report builder. 

Users select what data goes to a destination through: 

  • Identifiers to use to select data. Alpha uses the Alveo industry data model which is also used in its data integration and data mastering. The model covers different identifiers, industry and instrument taxonomies to provide different ways to select data. 
  • Determine which attributes for the referential and pricing data should be included. Some use cases require a skeleton set of fields whereas others may need the full detail of all terms and conditions. 
  • As-of date. Alpha stores data bitemporally meaning data can be requested as-of a day in the past to get historical values 
  • The quality grades. Some users may want the raw or unvetted data as soon as it becomes available. Others may only want to use consolidated data that has been marked ‘approved’. 
  • Data source. This can include selection on data vendor (e.g., Bloomberg, ICE, Refinitiv or Six) or contributor of price information 

Data onboarding is an end-to-end process: new data requests that cannot be immediately serviced from the data warehouse trigger automatic fetching processes to get the data from the required data vendors using Alveo’s integration with data providers.  

After retrieval, the new instruments are included in the regular quality management and approval workflows and become part of the ongoing downstream deliveries and usage tracking. 

Through routing new data requests and transparently showing who uses what data, scale economies emerge. Effectively, Alpha provides a data cockpit so firms have oversight of what data is going where – you can see the overlap, you can see data that may be warehoused but that is rarely if ever used, you see what sources are requested. This will help firms control cost and optimize their market data procurement. 

For more information or a demonstration, please contact me at nsandle@alveotech.com 

Neil Sandle, Head of Product Management

ESG data management: data everywhere but not a drop to drink?

 

The main conundrum in ESG data management is that, although there are dozens of sources including ratings, expert opinions on carbon emissions, model generated values using intel on industry supply chains, sentiment analysis and other alternative data sources, primary data from the source, i.e. corporate disclosures, is often immature and incomplete. 

As Funds Ireland put it in their August 2021 report on SFDR data coverage: “Our findings reveal patchy coverage on several ESG data points and a wide range of variance in the reported data with low levels of comparability”.  

At Alveo we have found that typical ESG data management challenges include: 

  1. Gaps in data and no single taxonomy 
  2. Normalizing or comparing ESG scores across vendors 
  3. Establishing linkage and hierarchy across issues, issuers, ownership structures 
  4. Variety of sources available in the market versus specific requirements from institutional clients 
  5. Different disclosure frameworks and different reporting calendars 
  6. Lack of historical data for indexing/benchmarking 
  7. Combining forward versus backward looking perspectives 
  8. Accessibility and interpretability of some data 
  9. Interoperability with financial risk assessment (financial and non-financial risks into a common framework) 
  10. Measurement conversion issues (e.g. GWh vs TJ) 

Our approach is to focus on the following key capabilities to overcome these challenges: 

  • Integration with ESG specialists and enterprise data providers: Easily and accurately source the required data sets to support ESG use cases across the investment management process. If you get the onboarding of data wrong by inaccurately representing values, naming conventions or permissible values it is almost impossible to fix down the road 
  • Multisource and aggregate from multiple suppliers to a common data model: Optimize your set of (external) data sources, cross-referenced to a comprehensive data model that incorporates regulatory information as well as more granular, underlying data sets. The data model introduces links between entities and financial instruments.  
  • Data lineage and audit: Transparency as to which sources and what types of data are used where, what business rules operate and what manual intervention took place across the data supply chain 
  • Integrated data management and analytics: A packaged ESG master would be built on immature data. Firms recognize complexity, diversity and that analyst judgment is needed. A data management offering in ESG has to focus more on helping analysts use their own research models and create their own metrics on top of aggregated data. 
  • Put ESG data to work: ESG data needs to be operationalized and made consumable. Alveo provides easy access via browser, REST API and fast last-mile integration to distribute ESG information. Business user enablement from asset selection, post-investment monitoring and external reporting 
  • Look through of indices, benchmarking and analytics: Use analytics integration to proxy missing data fields out of a set of holdings and to benchmark against peer groups, market indices and historical ESG performance. Capability to roll-up ESG indicators. 

Data Management as a Service

The data intensity of the financial services industry continues to increase. The subsequent rise in data onboarding and distribution requirements has led to (over)crowded change agendas and firms look for faster and more predictable change process in onboarding, verifying and operationalizing new data sets. 

Over the coming months, the Alveo Managed Services group will be going live with 3 new Managed Service clients across Europe and the Americas. In October Dragos Margos joined us as our new Service Delivery Manager. Dragos has extensive experience delivering manage services across financial services and will work with the services team and wider Alveo organization to further enhance the Service delivery processes and communications to our managed service customers. 

On the wider services side, we have invested significantly with our business partners in training programs to ensure we can scale our Professional Service capabilities to meet our customer’s ever-growing needs.  This expansion has enabled us to both reduce our average day rate to clients as well as provide a broader range of services. We are also seeing clients invest in and expand their market data infrastructure as they look at data requirements for the next 5 years.  

We are working with many of our clients to extend the usage of the solution within their organizations to ensure they get the maximum mileage out of their data management. It’s an exciting time in financial services and both existing clients and new customers are keen to adopt our best-in-class technology in preparation for a digital future.  

For more information or to discuss how we could help your firm, please contact me at srayfield@alveotech.com  

Casting a wide net: Alveo data integration services

In the Alveo data integration suite, we have expanded our data integration capabilities and our standard data model to cover additional ESG data as well as improved corporate actions data management capabilities.  

Recent new integration includes data integration of ESG data with FactSet, ESG data of RepRisk through the ICE APEX channel and index and ETF data via Ultumus. 

The Alveo standard business domain model contains about 375 corporate action attributes and over 600 issue attributes including new information for green bonds. The issuer part of the data model has been significantly expanded with about 140 ESG attributes. 

As ESG standards are rapidly developing and as the SFDR reporting timeline draws closer, we are closely monitoring new developments in this field to keep our data model marked to market. 

 

From the cloud up and the business use case down

Alveo’s engineering strategy continues to be the use of open-source components where sensible, architect for the cloud, making all core platforms available in container form and design the overall solution with business user self-service in mind. One recent example of open source is the integration of QuantLib as an example external library to give customers additional options for data derivations (e.g. curves, surfaces). Alveo products are designed to be Cloud provider agnostic, as our clients can be on Private Cloud, AWS, OCI, Google and/or Azure. 

 

Our overall design philosophy is to make our solution business user centric. By putting our domain model in the driving seat and having UI and UX adapt to the needs of Data Operations and Business Users, we are putting process control in the hands of business users. This allows them to change not only the data model but the process flow and access rights. The goal of this is to shorten the time between Data Governance decisions and actual process change.  

Our UX, Ops360, has been expanded to easily set up and configure business rules that act on the data. Other new functionality includes the set-up of data workflows (for instance for cleansing, for data aggregation, normalization or for data derivation rules) and data quality insights.  

The behavior and User Experience of our products immediately adapt to configuration changes without the need for IT intervention. This combined with our model driven statistical analysis of the data flows allows the business to monitor the impact and effectiveness of their decisions and adjust where required.  All this enables the business to move faster and frees up IT resources. 

If you’d like to know more or would like a demonstration of our UX, please contact me at mhermeling@alveotech.com  

Data quality meets analytics: an integrated approach

Recent research by Alveo reveals just 37% of financial services organizations use innovative data science solutions to support market analysis, the investment management process and operational workflows. As a result, quants and data scientists often face material issues before they can access data that is fit for decision-making. Because data management and analytical capabilities are often decoupled, users often turn into hunter-gatherers to find the data they need.  

Highly skilled data scientists often have to contact the IT department to write a query or set up a report. Even when quants access data, they may find the metadata that clarifies provenance, permissions and quality is incomplete. Many financial services firms understand they need a better way to provision their key users with clean data sets on financial products and pricing histories.  

For analytics to work efficiently, the data fueling it has to be high-quality. Yet data is often still held in different department-level data stores and within legacy applications. The metadata surrounding it is not updated frequently or is incomplete, making lineage, and understanding the relevant permissions and quality checks difficult.  

The number of data sources going into decision-making processes continues to grow and data scientists lament the frequent lack of a data catalogue which in turn often leads to time-consuming data searches or double sourcing. Using the latest technology to bring data management and analytics together enables them to treat the two as integrated disciplines and helps firms secure fast, flexible access to data. 

With data management more directly at the service of analytics, users within financial services organizations will use these new capabilities to drive better informed decision-making. These capabilities are typically proved on a managed services way, liberating firms from small change and upgrade cycles. This move to data-as-a-service, combined with the latest analytics capabilities, is making this happen. 

This promises to bring major benefits for quants and data scientists: in Alveo’s research, 27% highlight ‘improved productivity of data scientists and quants’ as one of the main benefits of more closely integrating market data and reference data into advanced data analytics. 

Quants and data scientists benefit from an integrated approach to data management and analytics through increased productivity. We are seeing many data analysts today that are looking to dig into the data to find indicators that help them discover investment signals or dig into valuation, risk and return numbers. Increasingly too, they are at least starting to incorporate innovative data science solutions into market analysis and investment processes. 

Cognizant and Alveo recently announced a joint comprehensive solution for ESG for the financial services industry. 

Cognizant will provide data operations and technology services to support the implementation and management of Alveo’s ESG Data-as-a-Service (DaaS) solution.  

Alveo’s technology provides clients with an overview of data operations as well as the ability to query and investigate ESG data, including complete lineage. With Cognizant’s help, these capabilities will be uniquely integrated into clients’ application landscapes, business workflows and reporting requirements. 

The importance of financial institutions better understanding the sustainability profile of funds has been quickly growing worldwide. This is principally being driven by investor demand for transparency, as well as new regulations, such as the EU’s Sustainable Finance Disclosure Regulation (SFDR). 

“ESG is one of the biggest trends impacting financial institutions, and it requires a significant investment in data and data management technology, said Mark Hepsworth, CEO, Alveo. “We are delighted to work with Cognizant on this initiative and believe they have the experience and expertise to drive transformative ESG capabilities, elevating the way financial firms provide investment products and advice that meets the needs of investors looking for societal and capital returns.” 

“This agreement brings to market a unique and necessary solution for financial institutions to evaluate the societal impact of investment decisions and modernise their business practices to better align with their social responsibility goals, said Craig Stanley, SVP and Business Unit Head for Cognizant Banking and Financial Services. “Alveo’s data mastering and data distribution solutions, which support financial institutions around the world, together with Cognizant’s digital implementation capabilities will help our clients meet new ESG regulations and the expectations of today’s socially conscious consumer.” 

“Breaking Down The Barriers”

“Cognizant and Alveo partner on ESG data management offering”

“Alveo survey reveals most buy-side financial firms struggling to deal with ‘significant’ data management challenges”

“ESG Data: Addressing the Operational Side of Data for Investment Support and Regulatory Compliance”

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