FinText worked closely with the LSEG content team to create their flagship annual AI/ML report
The London Stock Exchange Group (LSEG) is a diversified global financial markets infrastructure and data provider.
Following LSEG’s acquisition of Refinitiv, it’s now home to LSEG Labs, which acts as an in-house fintech. LSEG Labs collaborates internally across product lines, helping deploy machine-learning solutions in financial services.
LSEG Labs publishes an annual Artificial Intelligence/Machine Learning (AI/ML) report, now in its third year. The report draws findings from an extensive survey of machine-learning practitioners within the financial services industry.
The report would form the core of a major campaign, whose objectives were:
In 2021, with Refinitiv now part of LSEG, the report offered the potential to engage an even wider range of clients on the added value of data and machine learning for financial services companies.
The report’s target market mirrors the survey’s demographics: data scientists, data engineers, and – increasingly – deployers and integration analysts. This community now has a large (and growing) influence on data-services procurement. Decision makers, such as heads of innovation and heads of engineering, were a secondary target demographic.
As it commenced work on its research for the report, LSEG sought a professional writer with experience at the intersection of financial services and applied machine learning.
The client wanted their writer to provide informed input into designing the survey and data-discovery stages, to increase the potential value of the insights generated.
This demanded the writer have a practitioner’s understanding of financial machine learning and the interests of experts in the field. Since FinText’s own systems use machine learning to analyse financial content, we had sufficient internal expertise to suitably consult on this phase.
2. From data to narratives
Once the data was collected and presented, FinText set out to map how the data points coalesce into stories. Our writers interviewed Labs team-members for their thoughts on the collected data and conflated different data points from across the research to infer bigger-picture narratives.
As per our process, we then presented the team with a skeletal draft, along the main themes.
3. Development and refinement
The client had specified the final report was to be 2500-3000 words long, presenting data findings that trigger interest in the target market.
Our writers created the report to spec. Once the structure of the report was agreed, our writers set to combine data and words into the full narrative. The benefit of working off a skeletal draft made sure the client knew exactly what to expect.
To show how well this works in practice, below are screenshots from the first full draft delivered to the client, vs. the corresponding pages out of the final report.
Despite this being a large, data-heavy report, the client required only minor changes, and the editing process was by all accounts swift.
4. Account Based Marketing
For some of its key clients, LSEG wished to further personalise the report, by writing dedicated forwards.
Our writers engaged with the ABM team to understand what matters to each of these strategic clients. Depending on the client’s current business focus, our writers singled out key themes from the report, and used these to write tailored forwards.
1. The report: The Defining Moment for Data Scientists
The complete, 55-page report was titled The Defining Moment for Data Scientists. It points to 2021 being an inflection point, where data science is no longer merely an area of experimentation. Instead, AI and machine learning were now becoming core to launching new financial products and services.
2. Additional content
As part of the wider campaign to promote the report, LSEG also required writers for satellite content including regional reports, blogs and infographics. Sample outputs include:
A blog, titled 2022: How can financial services enhance data with AI/ML?
It explored the opportunities made available by machine learning becoming easier to get right, compared with just two or three years ago.
An Infographic, titled Everyone wants to do machine learning… but few get it right. Why?
It was a pleasure working with FinText on our flagship AI/ML report. Their writers really understood what we were looking for, and their deep domain knowledge made everything a big improvement on previous years’ efforts.
The writer’s ability to communicate complex analyses and communicate them in an accessible and interesting way to our target readership has been invaluable.
FinText were fast and responsive, working with our team from survey design to final delivery. Their process driven approach helped ensure use and reuse of content for multiple channels.
Overall, we were very impressed with the quality of the work done by FinText and would highly recommend their services.”Geoff Horrell, Group Head of Innovation at London Stock Exchange Group