Investors today want investment products that are customised to fit (and flex to) their specific long-term strategies.
Increasingly, this means products that enable them to thematically invest – tapping into the opportunities afforded by long-term, global, market-reshaping trends like blockchain, cryptocurrency, Metaverse, 5G, an ageing population, automation and robotics.
These trends represent a huge opportunity for investors – particularly as, unlike other types of investment, thematic investments cut, unconstrained, across geography, sector, style, market cap size and asset class.
Thematic investing was once restricted to investors with the piles of capital necessary to fund teams of domain experts to research themes and assets.
But as exchange-traded products (ETPs), index funds and other related processes widen access to thematic investing, appetite is growing. Respondents to a FactSet and Forbes Insights survey of 103 investment executives reported holding, on average, 28% of their total portfolios in thematic instruments or strategies – and expected this percentage to grow to an average of 35% within 18 months, and 42% within 3 years.
To make most of this surging demand for thematic investment products, you need to offer investors the most opportunity-rich thematic products possible.
Your ability to do that depends to a large extent on your data. And, if you’re like most asset managers, it could mean addressing a yawning gap in your datasets.
Introducing the Thematic Insights Gap
The Thematic Insights Gap is the disconnect between quantitative, structured data insights and qualitative, unstructured data insights in an Asset Manager’s datasets.
It’s a gaping void through which lucrative opportunities (thematic and otherwise) are escaping – Every. Single. Day.
Believe us: if you have a Thematic Insights Gap, you’re being held back from identifying the full range of relevant insights needed to offer investors the most valuable thematic investment opportunities.
Many of the opportunities and insights that thematic investing depends upon simply don’t show up in structured data.
A whole host of vitally important critical thematic signals are hidden in the unstructured data found on the web, in the news, and on other first-party and public domain sources.
Therefore, you need to be able to feed these unstructured data signals into your structured data models in order to get the truly nuanced, comprehensive and accurate picture of thematic trends that a growing army of investors are demanding.
But the Thematic Insights Gap in your dataset is making that impossible.
This Gap is holding you back. This Gap is losing you money.
This Gap must be stopped.
But how? Simple (sort of) – by changing the way you handle qualitative data.
The unbearable state of unstructured data
At its essence, leveraging unstructured data can turbocharge the quality, efficiency and explainability of thematic investing strategies.
When you consistently integrate unstructured data into your thematic investments, you move closer to resolving the insights gap and unlocking the potential of more performance, explainability and customization.
Historically, unstructured data has never been easy to use or integrate.
Collecting it has been a manual process – a process that not only sucks up time and resources but also depletes the value of whatever insights are derived.
And, given the sheer volume of unstructured data that’s out there, is impossible to attain through purely manual means.
It’s also incredibly hard for a human to weigh the dizzying multitude of unstructured data sources on the web for credibility and importance (ranging from reputable news outlets to ‘some bloke on Twitter’). Add the inherent error-prone nature of people and things get unreliable, fast.
As for integration – on top of being difficult to collect, analyse and weigh for importance, unstructured data is also a complete (insert expletive of your choice here) to integrate into structured data models.
Altogether, these qualitative-related shortcomings add up to a distinctly fuzzy view of the complex themes your investors are counting on you to understand.
That’s the cause – and the cost – of the Thematic Insights Gap.
Now let’s talk solutions.
Imagine if unstructured data wasn’t hard to use.
Even better: imagine unstructured data was just as usable as structured data.
Unstructured data that was collected, distilled and analysed for insights at machine speed (leveraging Natural Language Processing and deep learning tech) – so that asset managers could track thematic trends more or less as they happen.
Unstructured data from which qualitative insights could be automatically drawn, weighted and scored – so asset managers were always armed with the most important insights.
Unstructured data that was easily integratable into core data and quantitative data sets – so asset managers knew they weren’t missing any key information when planning their next move.
With this kind of unstructured data to hand, the Thematic Insights Gap would snap shut.
Asset managers could finally match the pace of global change, spotting opportunities and managing risks in near real-time for their deliriously grateful clients.
They could create new, highly differentiated thematic investment strategies and products, energise their existing products with better asset allocation strategies, and rapidly scale the most impactful models and processes.
Now what a world that would be. Cue your wistful sigh.
Now cancel that sigh.
Because we have great news: you’re living in that world right now.
We’ve created that world – by launching our Affinity platform.
It’s the first product to let asset managers easily collect, analyse and score clean unstructured qualitative data – and combine it with both core fundamental data and structured quantitative data sets.
And it’s the platform you need to create the ultra-granular, ultra-accurate, customisable and thematic investment models and products investors are waiting for.
Head to the Affinity platform page now to see why you should be as excited about this as we are.