AI in Finance 2022: Applications & Benefits in Financial Services
AI in Finance and its Impact on Businesses
On a retail level, advanced random forests accurately detect credit card fraud based on customer financial behaviour and spending pattern, and then flag it for investigation (Kumar et al. 2019). Similarly, Coats and Fant (1993) build a NN alert model for distressed firms that outperforms linear techniques. Machine learning and ANNs significantly outperform statistical approaches, although they lack transparency (Le and Viviani 2018). To overcome this limitation, Durango‐Gutiérrez et al. (2021) combine traditional methods (i.e. logistic regression) with AI (i.e. Multiple layer perceptron -MLP), thus gaining valuable insights on explanatory variables.
They can now field 10 calls an hour instead of eight — an additional 16 calls in an eight-hour day.