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Leading the crowd to generate wisdom - Legal and General Investment Management's data strategy in action

Mark Samuels Profile picture for user Mark Samuels July 18, 2023
The asset management firm wants to give end users the opportunity to self-serve and experiment with data in new and exciting ways.


Asset management specialist Legal & General Investment Management (LGIM) has set itself a long-term objective to provide self-service access to joined-up data, so users can generate bright ideas and then test them.  Or as Wulstan Reeve, Head of Data Marketplace at LGIM, puts it: 

We know the future is going to involve a lot more advanced analytics and machine learning. Everything flowing through LGIM involves data and the possibilities in just about every value stream are massive. We think we can lead the crowd and open up opportunities very quickly.

To that end, the firm is using the Cloudera Data Platform (CDP) to bring data together and give its employees the power to develop game-changing insights. It’s a big shift from the recent past, where different parts of the business built their own warehouses and ingested their own data. Matt Bannock, Head of Data Engineering at LGIM, says:

Our data strategy said we had to provide a central source of trusted data. On top of that, our CTO was saying we wanted to be cloud-first. Our working hypothesis was that we needed a platform to bring all our data together and enable our business to work with that information to generate new insights.

As part of the wider data strategy, LGIM is going through a big outsourcing initiative alongside external partner State Street. This project covers commoditised records and means lots of the firm’s current systems of record will be transitioning, explains Reeve: 

There's a real opportunity to build a cutting-edge approach to data that is going to be important for our business going forwards. We want to enable a much more digital view of data across the organization.

Reeve says his team wants to give people across the business an opportunity to get value out of data in a way that they couldn’t before – and that’s where Cloudera comes in:

We’ve spent a lot of money in areas such as advanced analytics and machine learning. In order to get that investment working effectively, you've got to make the right foundational moves or you’ll spend the rest of your life cleansing data.

Choosing a platform

According to Stuart Toll, Senior Enterprise Architect at LGIM, the organization took a “structured approach” to vendor selection, which drew on the opinions of the data team, but also senior managers across the technology department and the rest of the business:

We wanted to make sure everyone felt the vendor we selected would provide the capability we needed – that we could deploy the system within the organization and that it would deliver the enablers that were needed to drive our data strategy.

The requirements of the data strategy were meshed with the CTO’s demand for a cloud-first approach and a list of potential partners was created. Time-to-market was a crucial consideration when it came to the final selection process, as was an ability to scale processing power for analytics projects, such as for environmental, social and governance (ESG) scores. Toll explains: 

We're an asset management firm and we're focused on delivering business value. We wanted a solution that would work in the cloud and that could deal with big volumes of data. ESG scores take a lot of number crunching, but you don't need that computer power all of the time. 

LGIM also wanted an integrated toolset. While the data team looked at Snowflake’s cloud-based technology and other on-demand forms of provision, they eventually selected Cloudera’s data platform in May 2021. Toll recalls: 

Yes, you could use Snowflake, but we thought we’d then have to buy an ecosystem and a lot of other tools. We also looked at going down the pure cloud-native route, but that's about stitching capabilities together. We wanted a toolset that would give us fast value, which is why we ended up with Cloudera’s Data Platform.

Realizing the benefits

LGIM started implementing the technology in September and went live by the end of that year. The platform has now been in place for 18 months. Reeve says many of the original use cases for the platform are mature, citing the example of partnering with LGIM’s investment risk department to give users the ability to look at the risk profile of portfolios:

We wanted to slice and dice and visualize that data in ways that are new and exciting. I think the key differentiator is people can now get the answers they want quickly and effectively. People are consuming data as part of their processes.

Reeve’s team also worked with the finance department to build a core capability called Fund Look Through, which allows professionals to analyse the complex structure of funds. Other use cases are being developed for ESG scores and Reeve says users are now starting to access data, visualize it and experiment:

We’re giving every business function the opportunity to have their own home area. Anyone can access and start working with data. And they can ask us for help as they go on their journey. So, we're broadening adoption to lots of other departments. We started small and we're now seeing a profusion of use cases.

While there’s been big progress so far, Reeve recognizes that departments within the business start their data journeys at different positions. Challenges, including data literacy and disparate information sources need to be addressed. Orchestration of this program, he says, is a monumental task:

What we've got to do is make sure that every department is able to leverage the value in a way that makes sense to them.

Looking back on LGIM’s achievements so far, Bannock advises other digital leaders who are thinking of using a data platform like Cloudera to focus on business aims and priorities before selecting a technology partner:

Understand what you want to achieve before committing to a vendor. There's not really any bad tools on the market anymore. Look at time, budget, complexity – put that all together, create a cloud-native suite of tools and start using it quickly.

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