In the movie Margin Call, there's a pivotal moment when a quant discovers that the investment bank he works for is teetering on the edge of collapse.

Asset managers do everything to avoid such a scenario and try to understand the risk exposure of their investment strategy at all times.

But as John Lennon famously noted, 'Life is what happens when you're busy making other plans,' a sentiment all too familiar in the world of risk management.

The risk management scenarios in banks are based on outside variables that are in constant flux. That's why banks employ quants.

Quants, or quantitative analysts, specialize in analyzing large-scale financial data to identify patterns, assess risks, and create predictive models.

They aim to answer questions about what happens when parameters change, like the oil price going up, inflation going down, war breaking out, hurricanes forming, election results, or whatever makes the financial markets move.

But even with many analytical tools and datasets available, it can take a few hours to weeks to model specific scenarios.

Imagine the value for banks if they could access risk assessments within seconds.

Sebastian Janisch and Misha van Beek arrived in New York seven years ago and have worked on risk modeling and quant products for BlackRock (the world's largest asset manager) and Bloomberg (the dominant company in the financial information industry).

Both recognized the potential of AI in risk management tools but also understood that the legacy architecture of established providers would make it challenging to upgrade existing systems to what AI could enable.

So, they decided to take a greenfield approach and build their AI-assisted risk management tool, Bayesline, offering an add-on or alternative to these legacy solutions.

With the first iteration of their product, they were accepted by Y Combinator and found their investors. Having the YC badge of honor no doubt helped.

Sebastian and Misha have an unfair advantage. 

The industry experts we interviewed told us that there are probably only 20 people in the world with the combination of IT, risk management, and quant skills necessary to build an AI-assisted risk management tool for asset managers. 

Sebastian and Misha represent 10% of that population, and we wonder if many of the remaining 18 people all have the risk profile of giving up a very well-paid job for a risky startup.

Now, that's a moat that we like.

Currently, Bayesline is running prototype projects with four major clients, allowing asset managers to explore the capabilities of AI-enhanced risk management. 

Many asset managers use more than one risk modeling software, so without any risk, they can just try and experience how AI can improve their risk management business.

In an increasingly digital financial landscape, the importance of effective risk management will extend beyond traditional assets to include digital assets. 

As more institutions integrate digital assets into their portfolios, products like Bayesline will be a critical tool for identifying, measuring, and mitigating risks unique to those markets.

If you're in the risk modeling or portfolio analytics space, you may want to give Sebastian and Misha at Bayesline a call.

Or explore it yourself at app.bayesline.com/login

For those old enough to remember, it reminds us of the introduction of spreadsheets with Lotus 1-2-3 (for GenZ: Microsoft Excel) in the Eighties, which changed financial planning and modeling forever.

AI promises to be able to do almost everything. 

However, you still need experts who design a wrapper fine-tuned to an industry's specific requirements, intellectual property, and datasets.

Bayesline aims to be the one that will make it happen in the financial industry.

In a market valued at $15bn, that seems worthwhile.

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For further information, visit www.bayesline.com