Amplification of fluctuations in the market
The benefits of AI in the banking sector are evident, but every time we take a step forward we find more uncertainty and doubts. For example, one of the main risks is the possibility of amplifying fluctuations in the market . This is because AI algorithms , being based on historical data, could enhance market movements. Simply put, the threat of Artificial Intelligence exacerbating Banking Crises is very real.
For example, if an algorithm identifies an upward trend in a financial asset, it could generate a wave of buying that artificially boosts its price. Subsequently, it would only cause a sharp drop in price when investors realize that the real value of the asset is lower. Likewise, AI with machine learning could have biases when learning from incomplete data or databases. These errors could be amplified due to interconnected networks of financial institutions.
On the other hand, the integration of AI in the financial sector has made these systems attractive to cybercriminals. Thus, a breach could not only disrupt critical services and lead to fraud, but may even lead to manipulation of financial markets.
Another danger is that the irresponsible adoption of AI worsens financial inequality and encourages exclusion . Algorithms could favor larger, more sophisticated institutions, taking into account that they have access to better technologies and data. Small businesses and technologies could be disadvantaged, increasing the risk of financial instability.
Challenges in supervision and regulation
AI financial regulation within the banking system should be approached in the same way as it was during the Covid-19 pandemic. That is, there must be close international cooperation . Unfortunately, it does not seem that this will be the case, since it is increasingly difficult to reach agreements. According to multiple experts, the prominence that AI is gaining in the banking field will have severe implications on financial stability .
There are several challenges for effective regulation and supervision of Artificial Intelligence and preventing Banking Crises from amplifying . One of them is the rapid evolution of AI, which makes it difficult to create strong regulatory frameworks. Likewise, the complexity of algorithms makes their complete understanding and evaluation by regulatory bodies more difficult.
On the other hand, the lack of accessible and high-quality data on the use of AI within the banking sector hinders or blocks risk assessment. There is also little transparency about the algorithms, making it increasingly difficult to find biases and errors. In addition to this, authorities face problems in establishing responsibilities in case of failures and errors when an AI system is involved in the processes.
The challenge is to establish regulatory frameworks that allow finding a balance that protects financial stability and, at the same time, guarantees the security of information without stifling innovation within the sector. An overly restrictive regulatory approach will prevent the exploitation of technological advances. This alone will result in AI not being used to better shield banking systems . Therefore, it will be more vulnerable to attacks that do use new technological tools .