This document discusses artificial intelligence (AI) and its applications in financial services and real estate investing. It begins with definitions of AI, machine learning, and deep learning. It then provides examples of how AI is used in areas like fraud prevention, predictive analytics, trading, and customer service. The document also discusses contract models for data sharing agreements and AI-as-a-service. It explores challenges around intellectual property and data governance when using pooled data between companies for AI applications. The document concludes with contact information for Giuseppina D'Auria to ask further questions.

1. May 9, 2019
AI’s applications in financial services and
real estate investing:
BEST-PRACTICES EXAMPLES AND MODEL CONTRACTS
GIUSEPPINA D’AURIA

2. AI, Machine Learning, Deep Learning
AI’s applications in financial services and real estate investing
Contract models
A paradigm shift
Q&A
Contents

3. Definition of AI
3May 9, 2019
Artificial intelligence (AI) systems are software (and
possibly also hardware) systems designed by humans
that, given a complex goal, act in the physical or
digital dimension by perceiving their environment
through data acquisition, interpreting the collected
structured or unstructured data, reasoning on the
knowledge, or processing the information, derived
from this data and deciding the best action(s) to
take to achieve the given goal.
“
”
Source: Eu’s Ethics Guidelines for Trustworthy AI

4. Machine learning and
deep learning
Machine learning is the branch of AI that
involves creating algorithms
that can learn from data.
Deep learning is a type of machine learning that
uses deep (or many layered) artificial neural networks,
i.e. software that roughly emulates the way neurons
operate in the brain.
4May 9, 2019

5. ARTIFICIAL INTELLIGENCE
MACHINE LEARNING
DEEP LEARNING
May 9, 2019
Layers of AI
5

6. How deep learning works
May 9, 2019
Source: ARK Invest
6

7. What is AI?
AI’s applications in financial services and real estate investing
Contract models
A paradigm shift
Q&A
Contents

8. Source: CBInsights
8May 9, 2019

9. AI’s application in financial services
Fraud
prevention
Predictive
Analytics
Trading
Customer
Services
Regulatory
Compliance
Capital
Markets
9May 9, 2019

10. New and
unique
correlations
between
datasets
Highly
personalized
insights
Investment Management
May 9, 2019 10

11. May 9, 2019
> Equip advisers with highly
personalized insights
AI can automate the generation of
very detailed, specific insights (e.g.
persona wealth report generation) to
support advisers’ interactions with
their clients
> Find new and unique
correlations between datasets
Identify unexplored patterns to
outperform markets where
traditional active-investing
strategies are less attractive for
investors
Identify high-potential investment opportunities
11
Source: WEF Report, 2018.

12. Caveat
Free flow of non-
personal data (Reg.
UE 2018/1807)
Open Banking
(PSD2)
Personal Data
Portability
(GDPR)
May 9, 2019 12

13. What is AI?
AI’s applications in financial services and real estate investing
Contract models
A paradigm shift
Q&A
Contents

14. Synallagmatic
contracts
Data Pool
Data Lake
Adversarial
approach
Collaborative
approach
Agreement between
different firms to
licence specific data
sets to a central
administration in
order to fully exploit
its whole value by
means of big data
analytics.
Incomplete Contracts
Adverse Selection
Transaction Costs
Contract models
A contract in which
both parties
provide
consideration: the
data processor gets
a licence from a data
holder in exchange
for a sum.
May 9, 2019 14

15. Different viewpoints
The incumbent intends
to discover and develop
ideas for strategic
growth and market
gaps.
The AI company designs
and trains an ensemble
of machine learning
models in order to form
outcomes to be used in
advanced analysis.
Developing AI Implementing AI
innovation
15May 9, 2019

16. How the AI company works
DATA
TRANSFER
DATA MINING ML MODELS
MACHINE-
GENERATED
DATA
The larger the quantity of data pooled together, the more insights, findings
and accuracy of the outcomes
The very
essence of big
data consists of
drawing valuable
and original
insights from
data having
different
sources.
May 9, 2019 16

17. Data Supply Agreement
The agreement should be
necessarily integrated with IP
provisions.
Datasets
May 9, 2019
Most of the time, the supply
agreement implies license of
IPR:
Database
Trade SecretIoT Data
Stream
17

18. What the incumbent needs
The incumbent needs the necessary
infrastructure to collect data, store it, sort it
and extract by algorithms specific
knowledge, which can then be returned as
information or, more typically, goods and
services.
Options
1) DIY
2) outsourcing (i.e. AI-as-a-Service)
May 9, 2019 18

19. Contract for data processing
May 9, 2019
1) Duty to store data and keep them and AI outcomes confidential;
2) IPR to the owner;
3) Duty to return all copies of the data to the proprietor, and all
physical supports that contain or reflect the data and the AI
outcomes;
Provisions
4) The services are works made for hire. The contractor
transfers any rights and interest in any intellectual property
developed by him during contractual performance.
19

20. Bankruptcy – pending contracts
Data supply agreement
May 9, 2019 20
Contract for data
processing
Official receiver’s choice
Art. 179 CCI (former Art. 74 L.F.)
Termination
Art. 186 CCI (former Art. 81 L.F.)

21. Some small print
May 9, 2019
“By submitting, posting or displaying the content you give [X] a perpetual, irrevocable, worldwide, royalty-free,
and non-exclusive license to reproduce, adapt, modify, translate, publish, publicly perform, publicly display and
distribute any Content which you submit, post or display on or through, the Services”
“You grant us a non-exclusive, transferable, sub-licensable, royalty-free, worldwide license to use any IP
content that you post on or in connection with [Y] (IP License). This IP License ends when you delete your IP
content or your account unless your content has been shared with others, and they have not deleted it”
“The Aggregation Services are protected by copyright, trade secret, and other intellectual property laws. [Z]
hereby grants Licensee a personal, limited, non-exclusive, revocable, non-sublicensable, non-transferable
right and license to use the Aggregation Services during the term of this EULA in accordance with the terms
and provisions of this EULA. Except for rights expressly granted to Licensee in this EULA, [Z] reserves all
other rights, title and interest in and to the Aggregation Services and the underlying technology used to provide
the Aggregation Services, including without limitation all software and any copies, corrections, bug fixes,
enhancements, modifications or new versions thereof and all research and development and experimental
development in respect thereto […]. Licensee acknowledges that only [Z] shall have the right to maintain,
enhance or otherwise modify the Aggregation Services”
21

22. What is AI?
AI’s applications in financial services and real estate investing
Contract models
A paradigm shift
Q&A
Contents

23. Data Pools
May 9, 2019
Sharing pooled
data between two
or more
companies
Members offer
relevant data gathered
from different sources
in a jointly accessible
data store
In exchange for its
data, a member gains
valuable and original
insights that he may
not have had otherwise
23
A third party would get
a license from a single
administrator instead of
each relevant data
holder

24. Data Pools
May 9, 2019
IPRs
Antitrust tool
24
Favourable treatment in line with the one already provided to patent
pools.
Foreground IPRs on derived data will be equally shared by the
members.
Issues with managing IPRs.
Issues with meeting the Guidelines requirements.

25. What is AI?
AI’s applications in financial services and real estate investing
Contract models
A paradigm shift
Q&A
Contents

26. Giuseppina D’Auria
Avvocato, Di Gravio Avvocati
www.linkedin.com/in/giuseppinadauria
giuseppina.dauria@studiodigravio.com