The session explores the role of AI and big data in improving risk management and building business resilience in Financial Services. You will get a broader perspective into emerging (also referred as non-financial or Environment, Social and Governance (ESG)) risks in Financial Services. Finally you will be walked through a case study with a leading bank on their use of AI to future-proof their organization.

1. The role of AI in identifying
emerging risks in financial services
Maeva J. Charles
Partnerships & Technical Director
Datamaran
maeva@datamaran.com
www.datamaran.com
Data Management and Analytics in Financial Services Summit
17th July 2019

2. Agenda
1. Emerging risks
What are they and why are they important?
2. Role of AI
How can it help, especially in Financial services?
3. Case study
The example of Dutch group ING

3. “Emerging risks may be issues that are
perceived as potentially significant, at least by
some stakeholders or decision-makers, but
their probabilities and consequences are not
widely understood or appreciated.”
“Likelihood of a new [event] causing harm in a manner that is not apparent,
assessable or manageable based on current approaches to risk
assessment and management” (Adapted from Ramachandran, 2011)
Definition
1. Emerging risks

4. A subcategory of emerging risks
1. Emerging risks
ESG (Environmental, Social, Governance) risks
Non-financial risks
Sustainability risks
Emerging risks
or
or

5. No economic risks
in the Top 5
over the last 3 years
Beyond economic risks
1. Emerging risks

6. “The International Organization of Securities Commissions (IOSCO)
encourages issuers to consider the materiality of ESG matters to their
business and to assess risks and opportunities in light of their
business strategy and risk assessment methodology. “
“As the global industry body for exchanges, the WFE’s new Principles for
Sustainable Exchanges make clear that sustainability is the new
‘business as usual’ for exchanges.
“As with any group of risks, integrating ESG-related risks into ERM
enables organizations to realize long-term value.”
What is driving this ESG shift?
1. Emerging risks

7. 1. Emerging risks
Recent binding ESG-related laws
Waste
manage
-ment
Climate
change
Human
rights
UK
Modern
Slavery
Act
EU Green
Taxonomy
Single
use
plastic
bans
?
US
Congress
hearing on
ESG
disclosure?

8. 1. Emerging risks
What’s next?
Download full report at:
https://www.datamaran.com/global-insights-report/

9. Compliance
Long-term value
Reputation
Talent attraction & retention
Investor attraction & retention
Operational efficiency & cost reduction
Innovation
What are the benefits of better ESG
risk management?
1. Emerging risks

10. Tangible vs Intangible assets
in market value:
1. Emerging risks
Why do ESG risks matter?

11. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?

12. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?
Examples of risks:
- Shortage of skilled workforce
- Longevity
- Succession

13. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?
Examples of risks:
- Theft or loss of intellectual property
- Critical infrastructure breakdown
- “Born digital” competition

14. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?
Examples of risks:
- Data fraud or theft
- Unethical use or misuse of data
- Third party incidents

15. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?
Examples of risks:
- Climate change liability
- Man-made environmental disaster
- Involvement in social crises/unrest
- Human rights issues in supply chain

16. Corporate
culture
Brand
value Workforce
Intangible
assets
Technological
know-how
Customer
data
Reputation
1. Emerging risks
What do we mean by “intangible assets”?
Examples of risks:
- Diversity & inclusion
- Generation gap
- Fair & equal remuneration
- Agility
- Out-sourcing

17. Compliance
• business liability
• regulatory actions
• liabilities arising from
past, ongoing, or
potentially future legal
obligations
• reporting challenges
• compliance challenges
• compliance audits
Operational
• business disruption
• business interruption
• data loss
• expertise gaps
• harm to employee's life and
health
• high attrition rates
• inability to meet time to market
expectations
• loss of a part(s) of the network
or its inaccessibility
• loss of license to operate in a
specific location
• harm to employee's health
• negative impact on operating
results
• operational and strategic lagging
• reduction of production
• decrease in productive efficiency
• ….
Strategic
• becoming obsolete
• boycott
• competitive disadvantages
• customer dissatisfaction and
churn
• disclosure of sensitive personal
information
• employee dissatisfaction
• failure to attract and retain talent
• impossibility to implement new
business projects
• lack of motivation
• lawsuits / claims
• loss of brand value
• loss of customer trust
• loss of key
executives/employees
• loss of market share
• loss of privacy
• loss of regional/international
collaborations
• loss of strategic resources
• …
Financial
• decrease in cash flow
• expenses on
litigation/arbitration
processes, settlements and
judgments
• financial losses
• fines/penalties
• great drop in profits
• higher HR costs
• higher production costs
• inability to generate the
expected returns from the
shareholders
• increased costs
• increased R&D costs
• large economic damage
• large property losses
• legal expenses
• loss of investment
• loss of revenues
• lower revenues
• …
What do these risks have in common?
They all have economic consequences
1. Emerging risks

18. Challenges of integrating emerging risks into
standard enterprise risk management
2. Role of AI
Recognize
same topic in
different terms
Provide
understanding
of context to
non-experts
Quantify
qualitative
information
Expand the
breadth of
analysis
Scope Data
LanguageKnowledge
Role of AI

19. 2. Role of AI
Recognize
same topic in
different terms
Provide
understanding
of context to
non-experts
Quantify
qualitative
information
Expand the
breadth of
analysis
Scope Data
LanguageKnowledge
Financial services
have a broad
operating ecosystem,
risks can come from:
- Your operations
- Your clients’
operations
> AI allows to automate
analysis to enable a
broad screening that is
manually time and
resource intensive to
perform
Challenges of integrating emerging risks into
standard enterprise risk management

20. 2. Role of AI
Recognize
same topic in
different terms
Provide
understanding
of context to
non-experts
Quantify
qualitative
information
Expand the
breadth of
analysis
Scope Data
LanguageKnowledge
Many ESG/emerging
risks are qualitative
> AI allows to assess all
types of risks with the
same methodology and
provides a quantitative
score enabling
comparison of risks of
different nature and
relying on different
types of data
Challenges of integrating emerging risks into
standard enterprise risk management

21. 2. Role of AI
Recognize
same topic in
different terms
Provide
understanding
of context to
non-experts
Quantify
qualitative
information
Expand the
breadth of
analysis
Scope Data
LanguageKnowledge
Within and across
companies, business
units approach and
talk about the same
topic in different ways
> AI allows to identify
terms pertaining to the
same topic and treat
them as one
Challenges of integrating emerging risks into
standard enterprise risk management

22. 2. Role of AI
Recognize
same topic in
different terms
Provide
understanding
of context to
non-experts
Quantify
qualitative
information
Expand the
breadth of
analysis
Scope Data
LanguageKnowledge
Emerging risks are
wide in scope and risk
professionals lack the
knowledge to address
all of them
> AI allows to provide
data-driven insights and
context that give risk
professionals
information for risk
assessment
Challenges of integrating emerging risks into
standard enterprise risk management

23. “Identify future trends, new business risks and
opportunities that could impact ING’s ability to create
medium and long-term value”
3. Case study
A single approach
“To summarize in one line: it’s the convergence of
materiality. As the line between financial and non-
financial disappears, so too does the need to look upon
the concept of materiality between financial and non-
financial disclosures differently.”
CONTEXT
OBJECTIVE

24. 3. Case study
An integrated process
Read full case study at:
https://www.datamaran.com/customer-stories/ing-materiality/

25. 3. Case study
A cross-team & data-driven strategy
Sustainability
Risk
Strategy

26. https://www.datamaran.com/customer-stories/stakeholder-
voice-zurich-insurance/
https://www.datamaran.com/customer-stories/ing-materiality/
• Materiality of ESG Issues Takes Center Stage At US Congress
https://www.datamaran.com/blog/materiality-esg-us-congress/
• EU Green Taxonomy and NFR Directive update: Key Takeaways
https://www.datamaran.com/blog/eu-taxonomy-nfr-directive-takeaways/
• The Non-Financial Reporting Directive: What You Need To Know
https://www.datamaran.com/non-financial-reporting-directive/
• Global Insights Report: The Rise of ESG Regulations
https://www.datamaran.com/global-insights-report/
References

27. Thank you!

28. Thank you!
Contact us:
info@datamaran.com
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