Automation Insights for a European Asset Manager
FinText provided training on practical coding tools that can help boost investment marketing work
Should everyone learn how to code?
Please don’t answer; this is a trick question.
To think of coding as something one either “knows” or “doesn’t know” is a false dichotomy. Much better is to consider that some coding can provide an exceptional productivity boost for handling everyday tasks.
But companies often struggle to train their employees on coding skills that make a job easier. And it’s because the typical training programme will teach the coding basics, without ever touching on any specifics relevant to day-to-day operations.
Ideally, a company would state the typical challenges it faces, and then receive training on tools and techniques that will likely provide material benefits.
The Client
A global investment manager with a large European presence commissioned FinText to provide a ‘state of the nation’ report for its content marketing team, which introduces practical tools that can support investment marketing work.
Specifically, the company sought out insights on the following issues:
1. Working assumptions on the expected tech available within the next twelve months
2. Web scraping fundamentals – for competitor analysis and PR/media purposes
3. Tool categories for translations and transcriptions
4. Prompting best practices for working with an in-house LLM instance.
5. Solutions to flag keyword and phrases for compliance reviews
6. Getting started on automation of repetitive tasks
In preliminary conversations, the client requested the review to assume an initial limited knowledge of coding, but make no explicit judgement on the “buy or build” decision:
It wished to see pointers to off-the-shelf services, but also to solutions that, in exchange for a low degree of coding knowledge, can offer greater adaptation to the problem at hand.
The Project
The review was presented in four parts:
Part 1 presented the working assumptions as applicable to the asset manager.
One such assumption is that, over the next twelve months, we don’t expect the Large Language Model (LLM) technology itself to get materially better than its current state. Further, evidence suggests that, while the initial hype surrounding AI has (for now) subsided, the long stretch of capturing value is still in its infancy.
Further, with many use cases still awaiting validation, we’re at a sweet spot for companies to experiment in-house with the tools, applying it to their data and requirements.
Part 2 introduced the basic concepts of web scraping.
Part 3 explored using LLMs directly for text-based use cases (with a section on translations and transcriptions).
Part 4 introduced other ways of thinking about task automation, with a special focus on three different approaches to handling keyword/phrase-based tasks.
On top, great effort has been made to provide resources to help the client take their first steps in coding. These included:
- A list of carefully selected sources to guide the learning to the point team members can implement the suggested ideas.
- A step-by-step example for using ChatGPT to support code-writing.
- A Jupyter notebook (along with guidance on what it is and how to use it) is included with the report, providing live code examples for immediate testing and experimentation.
To learn more about getting started with coding in your everyday marketing work – please contact us here.
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