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AI in Financial Services –
What are the Rules?
https://www.shieldfc.com/
Your AI can no
longer remain a
black box.
Implicit Bias in Machine Learning
A Call for Governance
Let’s step back a moment for a quick
primer into how implicit bias has
apparently crept into financial risk
assessment models. First, machine
learning (ML) is an applied form of AI.
The term originated to describe the
practice of how the machine learns to
associate X with Y.
The wild, wild West analogy
here refers to a lack of self-
agency and policing which
leads to an “anything goes”
type of environment. Even
in an industry as tightly
regulated as financial
services,
https://www.shieldfc.com/
What’s Next?
The RFI will likely not probe deeply enough on
how financial firms are flagging transactions to
alert compliance officers to potential fraud and
money-laundering schemes. Nor will they likely
be able to elucidate how firms are analyzing
unstructured data to obtain insights alerting them
to suspected instances of market abuse.
The goal is a better understanding of and rules
governing how AI and ML should be applied to alert
compliance officers to suspected market abuse.

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Rules For AI in Financial Services | Sheild FC

  • 1. AI in Financial Services – What are the Rules? https://www.shieldfc.com/ Your AI can no longer remain a black box.
  • 2. Implicit Bias in Machine Learning A Call for Governance Let’s step back a moment for a quick primer into how implicit bias has apparently crept into financial risk assessment models. First, machine learning (ML) is an applied form of AI. The term originated to describe the practice of how the machine learns to associate X with Y. The wild, wild West analogy here refers to a lack of self- agency and policing which leads to an “anything goes” type of environment. Even in an industry as tightly regulated as financial services,
  • 3. https://www.shieldfc.com/ What’s Next? The RFI will likely not probe deeply enough on how financial firms are flagging transactions to alert compliance officers to potential fraud and money-laundering schemes. Nor will they likely be able to elucidate how firms are analyzing unstructured data to obtain insights alerting them to suspected instances of market abuse. The goal is a better understanding of and rules governing how AI and ML should be applied to alert compliance officers to suspected market abuse.