Why AI holds the key to faster and deeper financial research

If you’re a financial analyst or portfolio manager, you’ll be all too familiar with the trials and tribulations that come with manual research. Terminals like FactSet (whom we partner with), Bloomberg, and Refinitiv all provide huge and orderly fundamental and quantitative data sets.

But when it comes to capturing and integrating qualitative data, asset managers face a continual struggle to find consistently relevant and user-friendly information. Trawling for data sources across search engines, news and filings is slow, painstaking and inefficient – a clear blocker to driving down margin pressure or providing more customisation options for investors.

Not leveraging this data means you risk missing out on an abundance of relevant insights and timely market events.

For a long time now, people and businesses have employed AI to take over repetitive and manual-heavy processes. Applied correctly, AI can grease the proverbial wheels—and thematic investing is no different.

Here’s why.

It saves (so much) time

You already know that searching Google, news, and filings takes time – a lot of time. Time that could be used to develop and create more products, or provide more customisation. And even longer than the process of finding qualitative data is the process of aggregating it.

Finding, and bringing order and useability to unstructured data is hard. It’s time consuming – even more so when you have to repeat the act for every rebalancing to update the investment universe.

These are all reasons why the traditional research methods are losing you money. And it’s why portfolio managers are paying a premium whenever they invest thematically.

AI removes the dreaded and never-ending “scroll, scroll, click, scroll” and hoovers up the data points you tell it to—from sources across the web (Affinity’s AI web crawler ingests around 35m data points per annum, plus data about 30m private and public companies).

With Affinity’s UI, ThemeScape, research analysts and portfolio managers can model any theme fast – really fast:

• Up to 70% faster ad-hoc research (so you can build ingest and integrate more relevant data points and create more bespoke investment products).
• Up to 100% reduced efforts for updates (so you can react to market changes more often, and capture opportunities and pull back from potential liabilities).
• And up to 10x more relevant candidates for the investment universe (so you have a comprehensive, exhaustive library of investable companies at your fingertips).

It boosts quality, consistently

With manual research, you’re as likely to stumble onto a data dud as you are onto a jewel. Which means you run the risk of feeding less-than-premium data points into your investment models.

AI has the power to not only capture superficial information, but go down beyond the level of a news headline and discover which companies and people already map to your fundamental and quantitative criteria.

Affinity’s ThemeAI engine extracts, orders and filters companies that fit your investor specifications— constantly, and on repeat. It provides more companies, leveraging big data to bring in equity opportunities that are pre-filtered in line with your asset allocation strategies.

The result?

AI removes the heavy lifting and gives portfolio managers the power to build increasingly tailored and responsive investment products in a timely manner—again and again.

It enables better things, more often

To paraphrase the old psychology saying, AI is a great servant but a terrible master. Financial researchers who use AI as a tool to enrich—rather than overwhelm—their work, stand to benefit the most.

Whether that’s compounding process efficiency to roll out thematic investment products faster…

…or fuelling those products with more informed and more comprehensive thematic insights to create more bespoke offerings…

…or capturing timely market events to generate more alpha—applied intelligently, AI can unlock more and better outcomes, more often.

We’ve designed Affinity’s AI to help financial researchers and portfolio managers do all this and more—capturing, assessing, and integrating relevant fundamental and qualitative data.

See what AI can do for you here.