Alveo Blog ESG Data Management

Tackling growing pains: ESG Data Management is coming of age

Tackling growing pains: ESG Data Management is coming of age

Until recently, investing according to ESG criteria was the remit of specialist companies known as green or impact investors. These investors would have their own in-house data collection processes and their proprietary screening or selection criteria to assess potential investments. Although there were different reporting frameworks in places such as the PRI and GRI standards, the absence of standard data collection, integration, and reporting solutions required them to create their own “ESG data hub” to provision their own analysts, front office, and client reporting teams. As ESG investing has become mainstream due to both a regulatory push as well as an investor pull, ESG information management is fast becoming mainstream for research, asset allocation, performance measurement, operations, client reporting, and regulatory reporting.

With the deadline for key ESG regulations like SFDR fast approaching, asset managers and asset owners must do more to anchor ESG data into their end to end workflow processes. Simply having a source of ESG data to feed to the front office is not sufficient as businesses need this data from across the organisation to integrate into the whole investment management process – from research to client and regulatory reporting.

 

ESG integration is needed across buy-side and sell-side business processes

Any firm that sells or distributes investment products into the European Union will have to follow the SFDR regulation. SFDR requires firms to report on 18 mandatory Principal Adverse Impact (PAI) Indicators as well as some optional ones. Paradoxically, the reporting requirements for publicly listed companies that asset managers invest in lag behind the SFDR timetable. This causes an information gap and the need to supplement corporate disclosures with third party ESG scores, expert opinion as well as internal models to come to an overall assessment of ESG criteria.

There is also a need for ESG-data on the sell-side of financial services. For instance, in corporate banking, ESG data is increasingly crucial to support customer onboarding and, in particular, Know Your Client (KYC) processes. Banks will have to report their ‘green asset ratio’ – in essence, the make-up of their loan book in terms of business activities of the companies they lend to according to the EU Taxonomy.

In the future, if a company signs up to get a loan from a bank as part of the screening criteria, it will be asked to disclose what kinds of business activities it is involved in and what kinds of sustainability benchmarks it has in place.

Banks and other sell-side financial services firms will also frequently screen their suppliers, as part of a process called Know Your Third Party (KY3P). They will want to know who they are doing business with, so they can then report this in their own Annual Report. Banks will also want to climate stress test the products they hold in their trading book for their own investment against certain climate scenarios. The ECB, MAS as well as the Bank of England have all incorporated climate stress test scenarios in their overall stress testing programmes to gauge the solvency and resilience of banks.

ESG data also has a role to play in the way banks manage their mortgage book as they are increasingly looking for geospatial data, for example to work out the flood risk of the properties they finance.

Both sell-side and buy-side financial services companies will also need to integrate ESG data with data from the more traditional pricing and reference providers to give a composite view, incorporating not just the prices of instruments and the terms and conditions but also the ESG characteristics.

ESG data now needs to spread across the whole of the organisation, integrating with all the different data sets to provide a composite picture, becoming a key source of intelligence, not just for the front office but also for multiple business functions.

ESG data challenges

Common ESG data challenges firms encounter as they develop their ESG capabilities include data availability, usability, comparability and workflow integration. Many corporates do not report the information investment managers require for their decision making or indeed their regulatory reporting. This leads to the need to combine corporate disclosures with third-party estimates and scores, as well as internal assessments.

Usability issues include the disparity in methodologies third-party firms use to estimate or score firms on ESG criteria. Rating firms have their own input sets, models and weights and often come to different conclusions. Compared to credit ratings, the correlation between the scores given to a firm by different rating agencies is lower. However, credit analysis is as old as the banking industry and the metric gauged (probability of default) is clear. It could be that, with increased global disclosure standards under IFRS, ESG scores will converge.

Comparability issues in ESG are exacerbated by different standards, different reporting frequencies or calendars and also the lack of historical data to track progress and benchmark performance over a longer time period.

The biggest issue however is how to anchor the ESG data in a range of different business processes to put users on a common footing – which requires the capability to quickly onboard users, reports and business applications onto a common set of quality-vetted ESG data.

Looking ahead

Accessing ESG data and ensuring it is of good quality, comparable with other ESG data sets and well-integrated within existing workflows can be difficult.

Organisations will need to cross-reference, match and combine the data, as well as assimilate it with traditional data on companies and their financial products. Traditional prices and security terms and conditions of financial services providers will help build a composite picture from those different sources.

However, data management solutions and Data-as-a-Service offerings are now available to help firms get the ESG information they need, the capabilities to quality-check, supplement and enrich it with their own proprietary data or methods and the integration functionality to put users and applications on a common footing. This will enable firms to have an ESG data foundation for their end-to-end investment management processes on which they can build – for asset allocation, operations, client reporting and regulatory reporting alike.

Click HERE to find out more about Alveo’s ESG solution.

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Everything you always wanted to know about data management

In the previous post in the Achieving Data Alpha series, we started to explore frequently asked questions about improving data operations in financial services.

Our goal is for financial services firms to make the most of their data assets and optimally enable their business users to make data-driven decisions. We covered five questions we commonly run into and looked at capabilities such as data lineage and data governance, how to reduce data cost, and improve data quality.

In this post, we’ll address the next handful of FAQs, including best practices om improving data operations, streamlining data management, optimizing data assets and the growing role of managed data services. In case of any questions, please do not hesitate to reach out directly to us at fixmydata@alveotech.com

1. What does Data Alpha mean?

Data Alpha is a concept by which we mean achieving competitive advantage through superior data management. From our perspective, data management has been seen too much as a control function only for too long. Data management for control, i.e. knowing where your data came from, tracking where it is going, who can touch it and who can use it and having the capabilities to aggregate and quality-check different data sources, is critical. Still, it is also table stakes in the sense that these capabilities have become required for a license to operate.

Suppose you cannot assess the accuracy, correctness and timeliness of your data sets or access it, slice and dice it and cut them up as granular as you need for risk and control purposes. How can you do what matters: make the correct business calls based on that same data?

Data management for insight is what it is really about: how easily can you access your data? How sure are you about the quality of the data going into your risk models? How quickly can you onboard new data sets, integrate and cross-reference them to your current pricing and reference data to make them actionable within your business processes?

To us at Alveo, Data Alpha simply means increasing your data management capabilities to support and drive your business optimally.

2. How can managed data services help?

Managed Services help streamline data management, improve data quality and transparency, and reduce direct and indirect costs. Direct cost includes internal software and data license cost, infrastructure cost and staff cost. Indirect cost is typically the more significant and interesting part but harder to gauge. It includes more nebulous concepts such as future cost of change, operational risk, and the opportunity cost linked to being marooned on hard-to-change or out-of-date technology infrastructure. Ironically, the more complex these indirect cost improvements would be to assess upfront, the stronger the case for managed data services in the first place.

When a firm kicks off a process to investigate or conclude a managed data services contract, this forces the organization to think more formally about KPIs and SLAs they require to support the business. Firms should first be clear about the boundaries of the target service. What kind of change do you include? Do you have just hosting and IT services (run, monitoring) or change and test services? Do you have any business operations? Firms need to think carefully about metrics on uptime, delivery times and turnaround time for small changes deemed to be “business as usual.” Doing your homework will also clarify where different notions about instrument definitions and information to be covered can be harmonized and reflect fundamentally different business requirements. This process usually is enlightening in itself and a necessary precondition to conclude a value-added services contract.

Although a third party provides managed Data Services, it should always bring transparency on the end-to-end sourcing and offer its client a complete window into the processes. On top of the essential sourcing, integrating, quality-vetting and distribution of the data sets in scope and the maintenance services around that, managed service providers can bring extra value. Having outsourced day-to-day data operations and lowering the cost of change through a faster data onboarding process can help firms reach Data Alpha.

3. What does business user enablement actually mean?

“Business user enablement” is often used, and it seems it is something nobody would disagree with. But what does it mean in terms of capabilities required in a data management solution?

First of all, there is a need for user-friendliness. The User Experience of the interface to the data user needs has to match the standards that mobile apps have set since the first iPhone. These standards include well-considered screen layouts, user journey, and product design optimized to support their workflows.

Second, it means presenting overviews of the state of the operations through ad hoc reports that anyone can access, so your users don’t need to go to IT or your Business Intelligence team for every new report, every small change or new request.

Third, it means access to data for those users that require it. This access ranges from browsing for a large subset of users to supporting data operations workflows to quality-vet information, giving sign-off for downstream or external distribution, or deriving new data.

Fourth, it means access to data programmatically via state-of-the-art APIs to integrate it with internal analytical models and the rest of the application stack.

4. How do I streamline my data management?

Streamlining data management can be part of a managed services construct – in which the burden is given to the service provider. Alternatively, it can be done internally as a step taken before outsourcing a data operation.

To paraphrase John Donne: “No database is an island.” Any place of data storage will have many connections of data going in and out, keeping track of who uses what and who changes what is nontrivial. In real-life situations, often, there is an entire archipelago of data islands, meaning that data lineage and audit trails get lost. Storing data multiple times often complicates outsourcing arrangements. To overcome these challenges, it is essential to use service providers with suitable domain expertise in financial data products.

5. What is a data catalogue?

A data catalogue is an inventory of data sets an organization has. It typically also documents who can access the data and where it can be used, what quality checks has it passed, where it comes from, whether it carries a cost, and the related or similar data sets.

A data catalogue provides clarity to all users about what data is in house and where it is used and will prevent double sourcing or searching for information. Also, a catalogue can help harmonize data dictionaries and foster a common understanding of the maintained data fields’ meaning. It will flesh out discrepancies or gaps in the coverage.

Typically, a data catalogue sits one level above a data management system, although the two can also be combined. In that case, the solution provides an overview of the data sets available, their sourcing and preparation status and distribution connections.

We hope you find this blog insightful and helpful in your journey towards achieving data alpha. Let us know of any other data management questions you have via fixmydata@alveotech.com, and stay tuned for another post soon!

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Alveo’s 360km Company Challenge – An Employee Story


It has been one year that our offices have moved into our employees’ homes. We work now on our dinner tables, ‘temporary’ desks setup in our bedrooms and some lucky people in their offices at home. Modern technology lets us talk and see each other whenever needed, and we are doing very well working remotely. No more lengthy commutes to undertake or chatty colleagues interrupting our train of thought. But something was missing! Without the daily commute, step counts decreased dramatically, and there have been so many people we haven’t talked to in ages. The only person I meet by my coffee maker these days is my husband and he is out working most of the day.

And how about the new starters who joined us this past year? We haven’t met yet because they aren’t in our department or directly involved in our projects and activities.

However, all changed when Alveo organized a global company challenge. The brief was straightforward. Sign up, join one of the international teams and move until your team reaches 360km (225 miles) to raise money for the teams chosen charity.  Once the group hit their goal distance of 360km, Alveo would donate €1,000.00 to the team’s charity. Very ambitious groups could earn their charity a bonus payment of €1,000.00 when reaching 750km (466 miles) and 1,000km (621 miles).

The result was astonishing! A total of 8,346 km (5,186 miles) were run, walked, paddled and cycled. The teams raised €18,000.00 for various charities ranging from big global to great local causes (see below for complete list). Everyone reached their goal of 360km; our winning team clocked up an impressive 1,822km! The most significant contributor to the challenge, not part of the winning team, cycled 651km by all weathers through most of the Netherlands’ north.

However, the biggest gain was us taking a break, being active and healthy, talking to each other in our cross-continental groups, chatting to colleagues we have long not seen and spoken to and meeting some of our new colleagues. Let’s keep the momentum going and continue moving and talking to each other more often…. and giving back to our communities.

If you are interested in the causes we supported through this challenge, please see the links below:

 

Red Cross:  https://www.redcross.org/

Greenpeace: https://www.greenpeace.org.uk/

Wipe Away Those Tears: https://www.facebook.com/wipeawaythosetears

Diabetes Fonds: https://www.diabetesfonds.nl/help-mee/doneren

Cure Parkinson’s: https://cureparkinsons.org.uk/

Cancer Center Marburg: https://www.ccc-marburg.de/en/about-us

St. Jude Children Hospital: https://www.stjude.org/


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Why We Changed to Alveo?

Watch the video from our CEO, Mark Hepsworth, why we changed to Alveo.

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Business User Enablement in Financial Data Management

Watch the video of our Head of Product Management Neil Sandle talk about business user enablement and facilitating easy data access for business users.

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Alveo’s Technology Strategy

Watch the video of our CTO Mark Hermeling talk about Alveo’s technology strategy, in particular, around the use of cloud and open source technology.