Know the role of artificial intelligence in financial services that are flagging transactions to alert compliance officers to potential fraud and money-laundering schemes. Also RFI will not deeply probe on financial institutions who will not likely be able to elucidate how firms are analyzing unstructured data to obtain insights alerting. To know more visit: https://bit.ly/3xPbaiN

1. AI in Financial Services –
What are the Rules?
AI in Financial Services –
What are the Rules?

2. Introduction
Iftach Drori
Head of Marketing
Let’s keep it short, Iftach has over 10 years
of Sales and Marketing experience. He
holds a B.A in Economics and
Management from the Tel Aviv Academic
College.
He joined Shield in 2018 and since then
has managed to say the term “provide
value” 545,892 times.
Introduction

3. Financial services
and market fraud
Financial services and market fraud; two
phrases that you’d never expect to hear
uttered in the context of a technology wild,
wild West. Yet that’s the picture painted
behind the recent RFI (Request for
Information) posted by five of the world’s
largest financial regulators. These include the
Federal Reserve, Consumer Financial
Protection Bureau, Federal Deposit Insurance
Corp., National Credit Union Administration,
and Office of the Comptroller of the Currency.
Financial services
and market fraud

4. is there any unconscious bias that
has inadvertently been built into
the models?
This potentially exposes a murkier side of
financial transactions, one that we haven’t
seen in nearly 20 years since Enron’s
headquarters was raided by the FBI. “Do
they, or don’t they?” has once again
become the burning question. This time,
however, it’s being posed to the whole
financial industry as a collective. And it’s
not only the financial regulators asking the
question.

5. Implicit Bias in
Machine Learning
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 (in this case, the
mathematical algorithm versus a physical
machine entity like a robot) learns to associate
X with Y after it has been exposed thousands
or millions of times to data that explicitly
“states” X = Y.

6. Think about it this way, when you do a Google
images search, you’re actually on the receiving
end of an application of AI and ML. The software
engineers behind that technology chose which
data sets would be initially presented to the
search algorithm.
This first step is known as “training
the algorithm.” As is the case for
training of any sort, you learn
whatever you’re trained to learn.
Once the algorithm has been trained,
it is then tested on randomized data.

7. A Call for
Governance
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, there is no existing set of
standards or rules governing how
AI and ML (and the underlying
training data) can be used in the
assessment of financial risk.

8. Contact us at
11 Menachem Begin Rd. Ramat Gan, Israel
97235685587
https://www.shieldfc.com
info@shieldfc.com