Lots of algorithms go bad unintentionally. Some of them, however, are made to be criminal. Algorithms are formal rules, usually written in computer code, that make predictions on future events based on historical patterns. To train an algorithm you need to provide historical data as well as a definition of success.
We’ve seen finance get taken over by algorithms in the past few decades. Trading algorithms use historical data to predict movements in the market. Success for that algorithm is a predictable market move, and the algorithm is vigilant for patterns that have historically happened just before that move. Financial risk models also use historical market changes to predict cataclysmic events in a more global sense, so not for an individual stock but rather for an entire market. The risk model for mortgage-backed securities was famously bad – intentionally so – and the trust in those models can be blamed for much of the scale and subsequent damage wrought by the 2008 financial crisis. Read more
We’ve seen finance get taken over by algorithms in the past few decades. Trading algorithms use historical data to predict movements in the market. Success for that algorithm is a predictable market move, and the algorithm is vigilant for patterns that have historically happened just before that move. Financial risk models also use historical market changes to predict cataclysmic events in a more global sense, so not for an individual stock but rather for an entire market. The risk model for mortgage-backed securities was famously bad – intentionally so – and the trust in those models can be blamed for much of the scale and subsequent damage wrought by the 2008 financial crisis. Read more