**Appendix**

*Artificial Intelligence and Bank Soundness: Between the Devil and the Deep Blue Sea - Part 2 DOI: http://dx.doi.org/10.5772/intechopen.95806*


#### **Table 1.**

*Operations Management - Emerging Trend in the Digital Era*

the devil and the deep blue sea.

**Government Support AI & Banks**

Capital • Uncover crisis Asset • Explainability

Management • Predictability

**Appendix**

economic stability, political stability, digital safety, and financial safety causing disastrous consequences from reputational damage, revenue losses, regulatory backlash to criminal investigation, ignores equality and fair treatment, difficult to evaluate decisions due to poor explainability, transparency, resulting in lack of trustworthiness, accountability and reliability [12, 20, 28, 108]. The chapter has successfully portrayed bank soundness in the face of AI through the lens of CAMELS. The taxonomy partitions challenges posed by AI into 1(C), 4(A), 17(M), 8 (E), 1(L), 2(S) distinct categories. Ironically, both AI and banks are opaque in nature and have diminished public trust in them. Governments will be held accountable once again by taxpayers if markets come to a standstill as a result of AI. As such, banks need to provide answers on how well they are protecting customer's privacy and security with a range of protocols, controls and measures. If a silver bullet is not found than either banks will have to disappear, or the world will witness yet another catastrophe created by banks but this time with the help of AI. As such, trapping banks further into the conundrum of being in between

> Competition and Survival Nature of Banking Industry Future customers Beyond human capacity

Challenges

• Transparency

• Corruptibility • Responsibility • Cybersecurity risk

• Concentration risk • Systemic risk • Operational risk • Staff expertise • Conflict of interest

• High cost • Decision making

• Flash crash • Reputational risk • Mistakes

• Non-traditional data evaluation

• Biasness from spurious relationship

• Robo-advisor incorrect risk evaluation

• Biasness from data input

• Training and learning

**296**

*Taxonomy of challenges posed by AI on bank soundness.*
