Daniel Knüsli
Solutions to power your businessData Analytics: Was ist heute schon möglich? Potenziale. Grenzen. Relevanz
Road safetyThere are 1.2 million road casualties a year. Driver
and vehicle scoring, as well as technologies like driver
assistance (ADAS), can help us dramatically reduce road
casualties and develop a safer mobility future.
Cyber riskThe annual cost of cyber
crime to the global economy exceeds USD 400 billion.
Cyber solutions help us better manage and mitigate risks.
Natural catastrophesThe natural catastrophe
protection gap totalled USD 193 billion in 2017.
Parametric solutions can make insurance more accessible,
affordable and provide immediate pay out for
individuals and businesses to bounce back quickly.
Facing global risksTwo-thirds of global losses are uninsured
P&C Analytics • Tailored P&C Analytics consultancy
services to solve your every need • Portfolio Insights interactive risk
visualisation for steering and growth
Cyber • Cyber Product Suite for cyber
insurance product development• Cyber Analytics Platform for risk
scoring, portfolio, and accumulation management
Liability • Analyse and model liability portfolios
with Forward-Looking Modelling (FLM) to grow into new markets and segments
• Manage casualty accumulation risks
Property & Specialty• CatNet® natural hazard risk analyser• Sophisticated engineering
underwriting with PUMA• Agro Suite modular, end-to-end
agriculture solutions
Parametric• End-to-end pricing, risk monitoring,
policy administration, automated claims pay out and real-time reporting for flight delay, earthquake, tropical cyclone
SwiftRe® • Online risk placement, claims and
accounting platform • Cost-effective risk management• Full transparency into entire portfolio
Smart Homes • Develop next generation solutions
with advanced risk scoring• Preventive risk services • Fast time-to-market via Swiss Re’s
curated partners ecosystem
Automotive• Insurance-relevant driver scoring with
end-to-end telematics solution• Grow strategically and steer portfolios
with Motor Market Analyser
Ready to deploy
Increase efficiency, steer portfolios and grow into new markets and segments
P&C Solutions for your every need
Partnering with P&C Analytics…
Premium growthUnlocked premium growth potential of: >3%
UW profitability Improved portfolio loss ratio by: 6%
Pricing accuracy More accurate pricing leads to increased underwriting profit of: 5%
UW efficiency Reduced time to underwrite commercial risks by: 95%
Volatility reductionLong-term result volatility reduced by: 10 %
what we’ve already achieved with our clients
Powerful performance evaluation Outside-in smart visualisation of portfolio performance: INSTANT
We collaborate with our clients to
grow their business, increase their profitabilityand enhance their
efficiency
We provide tangible, data-
driven business insights that help our clients achieve
their ambitions
Broad set of analytic capabilities to generate powerful insights
Principles
Growth Profitability Efficiency
Go-to-Market
Portfolio and Loss driver analytics
Claims triaging and automation
Lapse, retention & propensity to bound analytics
Liability pricing analytics
Motor market analytics
Behavioural economics
Customer journey & platform consultancy
Portfolio Insights
Supply chain analytics
Property Risk and Cat analytics
Digital contract insights (Blockfinder)
Liability Cat modelling & analytics
Life Science Insights
Cross- and upselling analytics
Product Recall Insights
Value Chain
DistributionProduct
.DevelopmentUW &Pricing
OperationsClaims &
Portf. Mgmnt
Be
spo
keTo
ols
Our actionable business recommendations can help you reach your strategic objectives
A client story: Improved performance with insightsHow we use analytics to impact our clients’ underwriting strategy and improve profitability
6% decrease in portfolio loss ratio with further improvements expected
Developed new underwriting strategy and fine-tuned risk appetite based on analytics findings
6 months from kick-off to market roll-out
Enhancement of client portfolio data with external data sources
Detailed portfolio modelling and loss driver analysis by leveraging Swiss Re’s analytics tools and capabilities
Development of tactical risk map for future underwriting selection process and development of tailor made underwriting tool.
Our client had not achieved any significant performance improvement despite various internal portfolio “deep-dives” over past years.
On an industrial level, challenges included loss severity and frequency changes, impact of technology and cost pressures
Very large, global insurer.
Struggling with the rapidly changing industry, volatile and large losses and looking for solutions to better understand the changing risk landscape
6
The ResultsOur supportThe challengeThe client
Public recall data is not clean. Analytics and a combination of data sources are required to derive tangible business insights
17
130
7
15
1211
12
4
16
20
0
10
20
30
40
50
60
70
80
90
100
110
120
130
# r
eca
lls
1
name from DB
4
1 44
31
21
1 3
name from pdfs
TAKATA SOGYO
K.K. parent
17
113 130
TAKATA CORPORATION
TK Holdings, Inc.
Takata
T K Holdings
T.K. Holdings, Inc.
T.K. Holdings
TK Holdings (Takata)
Takata (Shanghai) Automotive Comp. Co.
TK Holding
Takata / T K Holding INC.
Takata/TK Holdings INC.
TK Holdings Inc.
TK Holdings
Takata AG
TK HOLDINGS INC
Takata Petri AG
Takata / T K Holding INC..
TK Holdings Inc. (Takata)
Takata/TK Holdings
TK Holdings Incorporated (Takata)
Example: NHTSA data on Takata recalls …
The NHTSA database lists the OEM that issued the recall, but not typically the supplier name. We can use text-mining techniques to extract the supplier name from “defect notices” in pdf form accompanying each NHTSA recall.
… combined with supply-chain data
Fiat Chrysler Automobiles N.V.
Takata costumers1, by market value
Honda Motor Co., Ltd.
Toyota Motor Corp.
Bayerische Motoren Werke AG
Volkswagen AG Pref
General Motors Company
Nissan Motor Co., Ltd.
Ford Motor Company
Renault SA
Ferrari NV
Tata Motors Limited
Leveraging third party supply-chain data, we gain insights into Takata’s customers, allowing to better understand supply chain risk and anticipate (accumulation) losses
no suit
lawsuit filed against Takata
1 Third party industry sources.
Data-driven insights into recall severity and frequency by component for better risk selection
… allow to identify car parts with increasing exposure to recalls
We use the compound annual growth rate (CAGR) of the last 5 years to identify problematic car parts with increasing exposure to recalls
Car-component level insights …
150’00050’000 450’000100’000
0
200’000
100
200
300
400
500
600
1’200
0
Body
# r
eca
lls
Wheel / Tires
Exterior Lighting
Powertrain
Interior System
Engine/Exhaust
Electrical System
Steering
Latches/Locks/Linkages
Engine Cooling
Fuel System
Heating / Ventilation
Brakes
Seat BeltsSeats
avg # units
Speed control (non-auto)
ChassisAir Bag
Other
Looking at the last 10 years, air-bags are leading in terms of units affected. Interior System recalls are frequent, but have a lower severity.
bubble scales by total number of units affected
7%
Engine/Exhaust
CAGR (5y)
Air Bag
Fuel System
4%
Seat Belts
-5%
Steering
PowertrainOther
SeatsChassis
Electrical SystemLatches/Locks/Linkages
Body
Engine Cooling
Wheel / TiresExterior Lighting 0%
Interior SystemSpeed control (non-auto)
BrakesHeating / Ventilation
6%
35%32%
2%
31%21%
18%18%
14%14%
-1%-2%
-5%
-15%
12%
A client story: Identify new markets and improve pricing accuracyHow we use analytics to identify growth opportunities and develop accurate pricing models
Improved pricing accuracy in various markets by 5%
Developed deep dive analyses and formulated holistic strategies for over 25 markets
2 months from kick-off to strategic insights of market opportunities
Combine our deep industry experience with expanded data pools and advanced analytics to develop an in-depth analysis to identify growth opportunities
Leverage Swiss Re’s forward-looking model and pricing expertise to enhance the pricing robustness and accuracy
Strategically and profitably grow into new risk pools and markets
Lack of information to identify and quantify the growth potential within specific markets and segments
Missing in-house resources to develop a holistic growth strategy leveraging market insights
Very large, global insurer.
Lack of clear strategy to identify and prioritize growth opportunities among various markets and segments
9
The ResultsOur supportThe challengeThe client
Marktgrösse: Buttom-up-Marktschätzung durch Kombination interner und externer Daten in erprobter Swiss Re-Schätzungsmethodik
Swiss Re interne und externe Datenquellen …
30 Umsatz
10
50
70
# F
irm
en
90
15
0
11
0
13
0
16
0
Externe Daten• Bureau van Dijk (Orbis)• SME Finance Forum• World Banketc
Swiss Re interne Daten• SwissRe Institut (Makroökonomisches
Expertenteam)• LRD• CatNet®• Underwriter und Marktspezialisten
(qualitativer Input)
… verbunden mit einer robusten Schätzungsmethode
13090
Umsatz
10 7030 50 110 150
Schätzung
Werte
Segmentierung der Firmen in (Sub-) Industrien
Industrie 1
Industrie 2
Parametrische Schätzmethode zur Approximation fehlender Umsatzkennzahlen und Subindustrien mit wenigen Datenpunkten
def mittelstand
Änderung des Mittelstandes im verarbeitenden Gewerbefür Baden-Württemberg
positiverUmsatzzuwachs
Legende
200y100y 50y
Swiss ReFlut-Zonen
Wiederkehrperiode
Die Karte zeigt den Umsatzzuwachs von mittelständischen Betrieben im verarbeitenden Gewerbe pro Postleitzahl, zusammen mit den Flutzonen des Swiss Re Flut-Risikomodells
negativer Umsatzzuwachs
Mittelstand: Betriebe mit einem Umsatz zwischen 10 und 250m Euro
Freiburg
Stuttgart
Konstanz
Tübingen
Marktgrösse: Das Segment mit >250m EUR Umsatz hat ~10 mal weniger Firmen, aber erzeugt vier mal mehr Umsatz als der Mittelstand
Anzahl Firmen und Umsatz pro Branche
• Der Mittelstand (10 bis 250 mEUR) generiert einen Umsatz von 1300 Milliarden Euro,
• das Segment mit Umsatz > 250m, generiert 5800 Milliarden Euro
• Das Segment mit >250 mEUR Umsatz hat ca. 10 mal weniger Firmen als der Mittelstand
• Im verarbeitenden Gewerbe sind es mit 763 vs. 5998 Firmen 8 mal mehr im Mittelstand
• Die Mehrheit der Firmen mit Umsatz über 250 mEUR sind in West Deutschland gelegen, spezifisch Baden-Württemberg, Bayern und Nordrhein-Westfallen
Beobachtungen
Umsatz
Geographische Verteilung
Anzahl Firmen
37,2
272,7
355,6
3,8
3,2
74,6
256,0
133,6
220,7
4,6
50,8
28,3
4,1
388,7
356,9
911,8
524,4
2′000 bn Euro
Retail Trade
Agriculture, Forestry, Fishing
Public Administration
Construction
Manufacturing
Finance, Insurance, Real Estate
Mining
Services
Transportation and Public Utilities
Wholesale Trade
2.7
1′727.8
1′377.1
10 to 250 mEUR
> 250 mEUR
79
75
55
37
763
20
170
398
340
403
2′0004′0006′000
3′985
1′0084′078
1′029
6
# Companies
5′998
4
1′548
4′966
2′572
Marktstrukturen und -trends: Swiss Re’s makroökonomisches Vorhersagemodell prognostiziert ein solides jährliches Wachstum von ca. 3.3%
Rezession
GDP Growth
Finance, Insurance,Real Estate
Agriculture, Forestry,Fishing
Manufacturing
Services
Wholesale Trade
Mining
Construction
Public Administration
Retail Trade
5.2%
Inflation (CPI)
Transportation andPublic Utilities
2.0%
3.4%
2.3%
4.3%
6.0%
3.1%
0.6%
6.8%
2.2%
2.6%
1.3%
-16%
-14%
-12%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
2008 2009 2010 2011 2012 2013 2014 2015 2016
jäh
rlic
he
Wa
chst
um
sra
te
Wholesale Trade
Finance, Insurance,Real Estate
Manufacturing
Services
Modell für die Prognose der jährlichen Wachstumsrate: • Basierend auf Swiss Re internen, makroökonomischen Vorhersagemodellen • Training 2008-2016• Vorhersageperiode 2018-2023
Historisches Industrie-Wachstum der Umsätze in Euro Durchschnittliche jährliche Wachstumsrate 2018 - 2023
Risikobewertung: Granulare Einblicke in die Exponierung gegenüber Naturgefahren
8,7%
100,0%
3,1%
50,3%
15,5%
43,4%
27,3%
12,4%
50,4%
11,5%
6,4%
2,3%
62,6%
Erdbeben
Waldbrand
6.2%
Flut
Hagel
Hagel-Karte
65,7%
100,0%
3,1%
28,3%
13,7%
86,3%
7,8%
11,5%
67,3%8.1%
Waldbrand
2.2%
6.0%Erdbeben
Flut
Hagel
Ba
de
n-W
ürt
tem
be
rgN
ord
rhe
in-W
est
fale
nH
ess
en
Erdbeben-Karte
46,5%
100,0%
53,5%
20,1% 11,1%
100,0%
3,8%
58,5%Flut
0.0%Erdbeben
0.0%
Waldbrand
0.0%
6.4%
Hagel
Flut-Karte
• Wir analysieren die Exponierung des Mittelstandes pro Bundesland bezüglich verschiedener Naturgefahren und aggregieren die Information auf Bundesland-Ebene
Statistische Analyse
• Die Exponierung ist zum Teil stark Bundesland-abhängig. So ist Erdbeben vor allem im Westen ein Thema, Hagel im Süden und Waldbrand nur im Nordosten (in geringem Ausmass).
• Flut ist ein lokales Thema und von Relevanz für ganz Deutschland
Einblicke
Legende
Erdbeben
Waldbrand
Hagel
Flut
Risikobewertung der Sachversicherung: Risikoexponierung nach Branche
Risiko-Exponierung für Sachschäden nach Branche Zoom-in für das verarbeitende Gewerbe
Swiss Re‘s Tarifierungsmodell für Sachschäden ermöglicht eine Einschätzung der Risiko-Exponierung nach Brache, für Betriebsunterbrechung (BI) und Materialschaden (MD)
niedrige Exponierung
hoheExponierung
• Der Finanzdienstleistung-Sektor und der Dienstleistungssektor haben ein geringeres Schadenpotential.
• Das verarbeitende Gewerbe und die Landwirtschaft sind wesentlich stärker exponiert
Bottom-up risk scoring for risk selection and prospecting
0,0 0,5 1,0 1,5 2,0
1,75
Albertsons
Disney
CVS
0,68Eldorado
Extended Stay 0,75
Hyatt Hotels
Kyo-Ya
Sears Holding
Sears Hometown
Wal-Mart
Wyndham
0,83
0,86
1,06
0,88
0,72
0,84
0,73
0,81
26
468
504
337
425
10,000 05,000
6
2,785
2,858
6,931
4
4,878
Total Risk(1) Normalized Risk(2)
Disney displays the highest relative risk due to its buildings being in locations that pose severe seismic and tropical cyclone risk.
Sears Hometown
Disney
Sears displays one of the lowest relative risks due to its buildings being well spread out across the USA with a proportion being outside of high Nat cat risk zones.
(1) The Total Risk is a proxy for the expected Nat cat loss for the corporate across all locations.(2) The Normalized Risk = Total Risk/#locations; therefore this measure serves as a relative risk across corporates.
xxx agency channel – demographics strongly skewed with respect to age and gender
Locations Sales force demographics
xxx
Competitors
Relative sales forcestrength1
23%47%
71%
254
67%
53%33%
29%
77%
15%
85%8%48
92%
87 187 362 267
95% 687%
< 25
8%
93%3%
97%
25 -30
926%
92%
5%
30 - 40
94%
40 - 50 50-60
1%99%
60 <
30 195 179 199
Clie
nt
ad
viso
ryA
ll a
ge
ncy
em
plo
yee
s
xxx’s sales force has a higher age – also compared to the market – and has an even stronger gender bias than the market – especially at lower ages
Market
Median age 42
% female 7.6
xxx
44
5.4
Market
49
5.6
xxx
56
4.6
All agents FKB
Female Male
High
Low
A client story: Improved transparency with insightsDeploying a highly tailored made visualization suite to enhance management focus and improve data quality
Instant drill-in capability to identify both positively and negatively performing areas
Deployment enabled swift identification of systematic data weaknesses and transition to a culture of excellence
Swiss Re provided a client-customised tool with relevant KPIs demonstrating data quality, performance and volume
This provided management with powerful levers to quickly identify areas requiring attention and growth opportunities
Client invested in cutting edge IT systems but lacked the ability to monitor and assess business performance across the company due to lacking data quality & complex organizational structure
Large Global player
Client required easy to understand analytics to improve focus & steer business towards improved performance across portfolio
The resultsOur supportThe challengeThe client
2 months
Snap-shots from the Portfolio Insights toolHarnessing the full potential of your data
Snap-shots from the Portfolio Insights toolHarnessing the full potential of your data