  Artificial intelligence (AI) continues to find more numerous and more
critical applications in the financial services industry, giving rise to fair
and ethical AI as an industry-wide objective. While many ethical principles and
guidelines have been published in recent years, they fall short of addressing
the serious challenges that model developers face when building ethical AI
solutions. We survey the practical and overarching issues surrounding model
development, from design and implementation complexities, to the shortage of
tools, and the lack of organizational constructs. We show how practical
considerations reveal the gaps between high-level principles and concrete,
deployed AI applications, with the aim of starting industry-wide conversations
toward solution approaches.
