Measuring how Simple, Personal, Fair Santander is toward
their customers
Willis/IRM Seminar, London, July 2015
Dr. Peter Mitic
Head of Operational Risk Quantitative, and Advanced Analytics
Santander UK
Disclaimer: The opinions, ideas and approaches expressed or presented are those of the author and do not necessarily reflect Santander’s position. As a result, Santander cannot be held responsible for them. The values presented are just illustrations and do not represent Santander losses.
Copyright: ALL RIGHTS RESERVED. This presentation contains material protected under International Copyright Laws and Treaties. Any unauthorized reprint or use of this material is prohibited. No part of this presentation may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system without express written permission from the author.
In 2004 Coca-Cola marketed its
Dasani
mineral water
brand in the UK. The discovery that the ‘mineral’ water
was actually tap water from Sidcup resulted in headlines
such as
"Coke sells tap water for 95p"
The product was immediately withdrawn and has not been
seen in the UK since.
The immediate financial loss to the
company is estimated at £40 million
(Willis UK Bulletin, Spring/Summer 2004: willis.com)
What is Reputation Risk?
Reputation A perception of anorganisation on the part of stakeholders that can
affect, positively or
negatively, the business relationship between the stakeholder and the
organisation (*)
Reputational Event
An occurrence or action that affects Reputation
Reputational Risk
The potential to influence Reputation. (positive as well as negative)
Management actions – Deloitte’s view
(*)Step 1: Examine strategies, risks and vulnerabilities
Step 2: Set up a baseline view of reputation drivers
Step 3: Proactively manage reputation:
•
Anticipate threats
•
Analyse trends
•
Action on behaviours
But there may be problems…
Does Reputation Risk
matter?
(*) Deloitte (2013) Three Steps Toward Managing Reputational Risk. Risk and Compliance Journal http://deloitte.wsj.com/riskandcompliance/2013/04/25/three-steps-toward-managing-reputational-risk/
Does Reputation Risk
matter?
You cannot think of
everything.
When it hits you there is
probably nothing you can
do about it.
Does Reputation Risk
matter?
Imagine a world where we can completely ignore our reputation
with respect to our customers, and there are NO consequences.
Does that world exist?
We make a great deal of fuss about reputation (we are doing so
by attending this seminar!), so we probably think that reputation
risk
does
matter.
Why? Because it tells us what our customers and potential
customers think of us. Furthermore:
1. We can measure it
2. Customer satisfied = better reputation = larger
income
Our Reputation: Usage
We have a growing understanding of the ways in which external reputation can affect the value creation within our business.
Santander UK has strengthened considerably through the Risk Framework and decision making process, where consideration of reputation risk – within risk appetites; product development; policies; process and compliance – are now embedded.
Alongside this, we have looked at how we can further develop the way in which we monitor, track and assess our reputation relative to our peers and in respect of specific issues as they arise
Our Reputation: Usage
We measure reputation by the Alva Reputation Index (
www.alva-group.com)
We receive a daily and a monthly reputation report
Its uses:
• Track Santander’s sentiment trend against our UK peer group, and
investigate areas that matter to us
• Reveal and highlight emerging reputational issues. We can look at the strengths of our competitors and see opportunities there
• Identify the drivers of reputation
• Classify the negative and positive issues that affect sentiment
Can Reputation Risk be measured?
Outline of the
alva
reputation measurement process
Content Harvesting
Content Analytics
Sentiment (reputation) score
… and then we take over…
Correlation model: Sentiment/Sales
Can Reputation Risk be measured?
“Content Harvesting”
.
(alva)
Receive feeds from financial press, news reports, TV/radio, social media etc., Search for keywords such as Santander, @santanderuk
Content Analytics
(alva)
1. Reject irrelevant content (“I had a nice holiday near Santander”) 2. Separate positive/negative sentiment – keywords not, -dis, poor 3. Weight content with respect to factors
1. Influential sources: have a higher weight (e.g. national press, tweets with many followers)
2. Prominence: headline exposure is worth more than a passing mention
3. Relevance: incidental mention is down-weighted
Reputation Index (alva)
1. Score and weight each content to produce a daily score in the range 1-10, reset daily to base
5.5
Sample daily report
On Twitter yesterday, user @Blonde_M (2,149 followers) noted: “Exemplary call centre customer service from @bankA - @bankB could learn an awful lot.”
The Independent i and Reuters report that two Canadian pension funds and BankC have established a £1.3bn London-based entity to manage and invest in renewable energy sources.
Mathematical Model
1. Find correlation:
ΔSentiment with ΔSales (lag 0-6 weeks)
2. Separate Up and Down sentiments
3. Find conversion factors
c
: (one for Positive and one for Negative
sentiment)
Δsales ~ c Δsentiment
4. Fit Up and Down distributions separately to Sentiment differences
5. Simulate loss distribution and extract 99.9% VaR
Super-stressed VaR: Scenarios
Summary:
The biggest hit comes from Extreme negative
sentiment.
It pays to preferentially mitigate negative
reputational events
Stress the ‘base’ results using
scenarios. Add high value sentiment
scenarios to the sentiment data to
simulate exceptionally good
reputation.
Similarly, simulate exceptionally poor
reputation by adding low value
sentiment scenarios.
Note that we add positive as well as
negative scenarios.
Annual Sales
expected values
Sentiment movement Sales (volume) Up 1.6% Down 1.9%Annual Sales
stressed values
Sentiment movement
Sales (volume)
Up 4.0%
-150 -100 -50 0 50 100 150 200 250 0 50 100 150 200 250 300 350 400 450 500 C um ul at iv e s ent im ent Day Cumulative Sentiment 1/1/2014 to 1/5/2015 J F M A M J J A S O N D J F M A
Cumulative sentiment comparison
Quartile 2 Quartile 3 Quartile 1 Quartile 4
