I this article I argue that anyone who prides themselves on being process-driven and is performing repetitive work will soon face stiff competition from automation and machine learning, as they are being introduced in the financial services space.

Imagine algorithms establishing specific client preferences from past investment patterns that autonomously trigger financial portfolio modelling and testing against various past and potential market scenarios.

Next, a new financial product is being legally structured, tax opinions and rulings are electronically requested and the respective documentation is automatically created. All filings are completed without the input of a single lawyer.

Then, based on the legal documentation, and combining previously obtained market evaluation and coded corporate positioning of all the involved firms, the required marketing collateral and associated promotional materials are being assembled. From term-sheets for pre-marketing, pitch decks, to a fully interactive reporting suite that seamlessly integrates into the client’s preferred reporting system.

A fully automated lauch campaign plan is being drawn up, which assigns contextually powerful messaging and briefings to spokespeople, after having blocked the respective time slots in their calendars. Content assets (pulled from research, white-papers, videos etc) are being added, and missing content is being ordered for production. Conference slots are being pre-booked, and slots in the calendars of investment and sales staff is reserved for road-shows.

Teaser emails, letters and phone scripts are being created for the prospect list that was initially created.

Whether you consider this the perfect world or a doomsday scenario: A lot of this is already possible today, and numerous FinTech startups have been working for years in order to stake their claim.

At the time of writing the discussion about the fate of humans in this context has only begun, and is still too sensationalistic for a meaningful discussion.

Two key human skills should remain valuable for some time: Complex problem solving and empathy.

Decades of research in artificial intelligence and machine learning have resulted in several disciplines in the field, with each one being good at resolving a specific type of challenge. There is, however, no master algorithm yet. Should you find one, please approach Pedro Domingos (for a video about his quest for it please click/touch here). Until the master algorithm is discovered, we humans should hone our skill in finding solutions to complex problems.

Empathy, the other skill, has to do with being able to read and adapt to the needs of other human beings. More technically, it is about the interface between the human and the machine. There are many situations where we probably will prefer a fallible human to the most elaborate app.