How will finance jobs change with AI and Machine Learning?

Each sector of finance will be affected differently

Artificial intelligence and machine learning have been affecting human intervention in finance for a very long time, we’ve only begun noticing because AI/ML are at the peak of the hype cycle.

Using a framework of how 1) data driven 2) predictable 3) expensive a financial services job is, we can see the future of the broad verticals in finance.

1. Trading (High automation potential) : Machines have been picking up a large amount of trading work because it is highly data driven and doesn’t require much human interaction. Although there is a fair amount of unpredictability involved with trading in markets, the high salaries of traders (upwards of $500K/year) makes it economically feasible to invest in algorithms and data science to do the work.
2. Corporate Finance (Medium automation potential) : As companies become more data driven, the key reports and insights that a corporate finance executive generates will be automated. Given that this is more predictable than markets (just one company) it becomes far easier to run basic analysis. The key component that will not be automated is the high level of human interaction needed to communicate and package these insights, which is why it will be hard to automate entirely.
3. Investment Banking (Medium automation potential) : Investment banking is driven intensively by human interaction (deal making) and the lack of data for all parties involved. The core reason investment bank is so intensive (and well paid) is that it involves gathering non public data, communicating deal information and convincing relevant stakeholders that is extremely unpredictable. As bankers are deal brokers, till deal information remains hard to get - it will be hard to automate.
4. Private Equity and Venture Capital (Low automation potential) : Venture capital involves deploying risk capital on business models that are usually unproven - there is usually no data, it is highly unpredictable and is driven a lot by by discussions. Similarly with private equity, where there is some more data but again involves a lot of human interactions. Both are extremely unpredictable and human intensive, it will be hard to build algorithms to deploy risk capital.

Overall, technology is becoming the overarching framework of virtually everything we do. Finance, retail, healthcare and the like are now not sectors - but products and use cases of technology. As Goldman Sachs describes itself “We are now a technology company” - there is a lot of meaning in this because GS has always been a trendsetter in financial services.

I blog about Venture Capital in India at Life of a Junior VC