the role of data in esg & impact investing integrating esg ...€¦ · 8 confidential |...

The role of data in ESG &

impact investing

Integrating ESG Data

Dario Popadic, Quantitative Analyst 4F Equities

13. June 2019, Amsterdam

2 Confidential | Investec Asset Management

Agenda

1. Responsible Investing at IAM

2. Use of RepRisk in the Firm

3. Early Findings of Empirical Research

4. Working towards a tailored ESG Quant solution


Responsible Investing at IAMWe monitor, evaluate and actively engage or withdraw investments with the aim of

preserving or adding value to our clients’ portfolios.

Develops

ESG

approach

Therese

Niklasson,

Global Head of

ESG, joins

Joins Principles

for Responsible

Investment

(PRI)

Establishes:

• Investment

Governance

Committee

• Stewardship

policy

• Ownership and

proxy voting

guidelines

Signs UK

Stewardship

Code

Evolves

integration

programme

Signs SA

CRISA

Code

Formally sets

up ESG team

Sets up

Investment

Sustainability

Forum

Expands

exclusion

policy

Establishes

exclusion

principles on

cluster

munitions

Expands

ESG team

Develops

ESG tools for

investment

teams

Integrates climate

change statement

within stewardship

policy

Expands

private markets

expertise

Appoints

Head of

Engagement Publishes first

integration

progress

report

Publishes second

integration

progress report

Enhances

transparency

and disclosure

with Annual

Stewardship

reportOnboards

external

data

provider

Sets up

ESG

integration

framework

Launches first

Sustainability

fund

Creating sustainable

investment solutions

Ensuring ESG is integrated across all

of IAM’s investment strategies

Ensuring we are active

stewards of capital

2016 2017 20182014 20152009 2010 2011 20122008 2013 2019

Launches

second

Sustainability

fund


Use of RepRisk in the FirmRepRisk’s proposition

• We use a number of external ESG data and research sources that are intended to

complement fundamental research

• In a world where externalities are being internalized, the quality of data becomes

increasingly important

• We have built internal tools and scoring systems that are powered by independent

research and data

RepRisk’s focus on capturing adverse information, the differentiated approach

and its fast moving and event-driven data makes it a core component of our ESG

analysis. The increased granularity through assigning risk incidents to categories

allows us to perform a deeper analysis and hence get more out of the data than

simply ESG scores.

RepRisk helps us: 1. Analyse ESG issues

2. Build proprietary models

3. Monitor portfolio’s ESG profile and discuss external risk


Early Findings of Empirical ResearchRepRisk Methodology

Source: RepRisk

RepRisk focuses on assessing companies' reputational risk and monitoring ESG

issues based on sources external to a company. It is differentiated and

complementary to the more traditional, research driven ESG ratings such as MSCI.

• RepRisk attaches each risk incident to the issuer

according to 28 ESG issues, which map onto the

Ten Principles of the UN Global Impact

• Relevant data from over 80,000 public media and

stakeholder sources every day are screened

A risk metric called RRI (RepRisk Index) is attributed to each company, ranging

from 0 (lowest) to 100 (highest). The RRI is calculated regarding the number of

issues, severity and novelty of risk incidents on a daily basis.


Early Findings of Empirical ResearchRepRisk Example Flag

Thai authorities to pursue

investigation into Rolls-Royce

Assigned:

- Medium level of reach (Level 2)

- Medium level of severity (Level 2)

1. Screening of news

2. Identification of E S or G issues

3. Assigned levels of:

▪ 80 000 news sources in 20 languages

▪ Keywords scanned related to ESG issues (UNPRI)

▪ Reach: How influential the source is and how widely read

▪ Severity: Scale of the issue and level of criticism

Keywords linked to issues:

- Violation of national legislation (G issue)

- Corruption (G issue)

Methodology: Example: Rolls Royce


Early Findings of Empirical ResearchA look into the data

Source: IAM 4Factor, Date: 01-Jan 2007 – 31-Dec 2017

How well would a portfolio have done by avoiding the companies with high

number of issues?

number of issues / month

Highlights increased likelihood

Likelihood of negative outcome vs number of issues over various holding

periodsdifference between

the two groups

• The higher the number of issues, the more likely that there is a negative outcome

• The likelihood increases with time

Holding period


Early Findings of Empirical ResearchInitial backtests

Source: IAM 4Factor, Date: 01-Jan 2010 – 31-Jul 2018

Focusing on high number of issues can help to mitigate ESG risks.

Cumulative return profiles for the low / high number of issues and comparison

across multiple holding periods

▪ Low # of Issues

▪ High # of issues

- - - Universe

* The distribution of the total number of issues that are recorded each month is

skewed. For example, it is most common to have two issues recorded in a

month. Therefore, we combine the bottom two tertiles of constituents to form the

low number of issues with the remainder being the high number of issues.


Early Findings of Empirical ResearchRepRisk Index

Source: IAM 4Factor, Date: 01-Jan 2007 – 31-Dec 2017

RepRisk RRI metrics share a similar level of importance.

Detailed analysis of RepRisk RRI-scoreNumber of issues

*Average annualised return is calculated as the average across all holding periods (1,3,6,12,18,24 months)

** Scoring: 1 (low), 2 (medium), 3 (high)

Ave

rag

e a

nn

ua

lise

d r

etu

rn %

High Low


Working towards a tailored ESG Quant solutionESG Data Challenges

*Source: The Global Initiative for Sustainability Ratings

The lack of transparency and a common standard reporting format for companies

presents a major challenge, in particular for a more data driven ESG approach. Third-

party ESG data providers have different scoring approaches which can provide varying

views.

• 125 ESG data providers*

• Providers create their own scoring methodologies and sourcing

• Risk of incorporating judgement calls of providers into the investment process

Key differences among providers: Aggregation and weighting of factors

Data acquisition and estimation

Materiality of factors

IAM has built a scoring system based on data from various best-in-class providers and

utilises the Sustainability Accounting Standards Board’s (SASB) materiality framework.

Requirement for tailored ESG scoring.


Working towards a tailored ESG Quant solutionESG Scoring Approaches

Source: IAM 4Factor

The Do Good Score translates information related to a company’s Environmental,

Social and Governance performance into a signal that is ready for practical

application in investments. It links ESG information and investment performance by

identifying the financially material issues.

How it works

The assessment of financial materiality is carried out in two ways, both of which

combine to create the ultimate Do Good Score. Good performance on both inputs

mean a company is Doing Good.

(1) Pre-defined mapping of the SASB to identify the material issues

(2) Historical performance of ESG issues per region, sector and size of company


Working towards a tailored ESG Quant solutionESG Data integration and visualisation

Source: IAM 4Factor

ESG forms a core part in investment decisions and data from various providers is

being integrated into our platforms for:

• Proprietary ESG scoring

• Holistic security level ESG analysis

• Portfolio level scores

the role of data in esg & impact investing integrating esg ...€¦ · 8 confidential |...

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