Artificial intelligence is showing promise in a wide range of fields, but it also somewhat inaptly named. Unfortunately, many of the ideals around AI have been formed by the fantastic imaginations of science fiction writers. While AI certainly has a wide range of applications, it is a far cry from the capacity of human brains or any type of sentient beings, including animals. Risk management is one area that is a perfect fit for the available uses of AI, but even there, it has drawbacks and limitations. Here are three ways that AI is assisting in risk management and some drawbacks of each.
1. Credit card monitoring and fraud protection
Perhaps one of the most invaluable uses of AI is in protecting financial data and transactions. AI can scan billions of daily transactions to spot irregularities in spending patterns, money transfers or other types of financial movement. One drawback to this, however, is that many of these irregularities are legitimate but it would take too long to go through each irregularity. So, while AI can spot irregularities that might point to something amiss, determining the appropriate response to the data is still a work in progress.
2. Extending credit
Credit scores are invaluable in assessing risk, and yet they don’t always paint a fully accurate picture in some cases. Most credit scores are determined by a complicated AI-powered algorithm, but even formulas and algorithms have potential issues. Ultimately, formulas and algorithms are still created by humans, which means there is always the potential for algorithmic bias. When creating algorithms that weigh certain factors and criteria as being more favorable than others, personal biases will almost invariably creep into the formula. These small biases can even end up magnified over time to even further reinforce existing patterns of discrimination.
3. Protection from cyber attacks
The same way that AI can detect anomalies in spending habits, it can also detect the telltale signs of a cybercriminal attempting to penetrate layers of security. The issue, however, is that AI-powered security systems can themselves become the object of attack and can potentially be subverted into doing the cybercriminals bidding. Think of a bank guarded by a robot that can instead be reprogrammed remotely to steal the very thing it is supposed to be protecting.