actuaries’ club of theacsw.us/spring17/noronha.pdf · insurers are using a broad range of...
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Actuaries’ Club of the Southwest Creating and Communicating to Management through Use of Dashboards – Primer on visualization
June 15, 2017
PwC
The insurance market is undergoing major disruption –Finance/Actuarial needs to navigate “from the Cockpit”
Failure to modernize finance will likely result in finance and the overall enterprise falling behind traditional competitors and new entrants, missing out on new opportunities and profitability enhancements, higher operating costs, and other groups becoming the strategic advisor to the business.
“The new hypothesis involves the CFO and finance leaders:• playing a much more dynamic and
facilitative role;• moving from static and rigid processes
and controls to adaptive, agile and resilient models which;
• require orchestration rather than execution and control …
In the future, finance will have sharper analytical capabilities in the use of Big Data query analysis, social media monitoring, and real time dashboard creation”1
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ACSW – Primer on visualization
PwC
Finance/Actuarial in the cockpit is an aspiration to most as they strive to put the pieces in place
• Implemented data virtualization capabilities (e.g. Cisco, Informatica, DOMO) to access heterogeneous data without moving it or conforming it to a single model
• Implemented Hadoop technologies to allow for the distributed processing of data from mobile and sensor technologies then making the data available for analytics.
Data Integration
Leveraging the Cloud
Data Visualization / Advanced
Simulation
• Used cloud-based modeling capabilities to manage capacity needs and drastically reduce cycle times by 90 -95 percent.
• Moved finance applications (e.g. Oracle, Workday, SAP, Google) to the cloud to facilitate multi-user accessibility, improve model/application controls and reduce operating costs.
• Used visualization “cockpits” (e.g. Tableau, Qlik) to evaluate market entry strategies and growth-profitability tradeoffs in markets/product lines.
• Used a packaged simulation solution (e.g. AnyLogic) to create discrete and agent-based models to evaluate potential events.
Sample action taken by insurance market leaders…..
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Several tools available for business intelligence and analytics
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June 15, 2017ACSW – Primer on visualization
Source: Gartner report (2007)
PwC
The insurance sector is moving from backward-looking analytics to forward-looking analytics
Descriptive Analytics
What happened?
Diagnostic Analytics
Why did it happen?
Predictive Analytics
What will happen?
Prescriptive Analytics
How to make it happen?
Incr
easi
ng
Bu
sin
ess
Va
lue
Increasing Sophistication of Data & Analytics
DatabaseWebsites
Audio
Video
Sensors
Social Media
Structured Data andOperational Decisions
Unstructured Data andStrategic Decisions
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Insurers are using a broad range of advanced modeling techniques to generate insights
Tra
dit
ion
al
Em
erg
ing
Structured Unstructured
A/B/N Testing
Experiment to find the most effective
variation of a website, product, etc
Sentiment Analysis
Extract consumer reactions based on
social media behavior
Complex Event Processing
Combine data sources to recognize events
Predictive Modeling
Use data to forecast or infer behavior
Regression
Discover relationships between
variables
Time Series Analysis
Discover relationships over
time
Classification
Organize data points into known categories
Simulation Modeling
Experiment with a system virtually
Spatial Analysis
Extract geographic or topological information
Cluster Analysis
Discover meaningful groupings of data
points
Signal Analysis
Distinguish between noise and meaningful
information
Visualization
Use visual representations of
data to find and communicate info
Network Analysis
Discover meaningful nodes and
relationships on networks
Optimization
Improve a process or function based on
criteria
Deep QA
Find answers to human questions
using artificial intelligence
Natural Language Processing
Extract meaning from human speech
or writing
Data
Te
ch
niq
ue
s
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June 15, 2017ACSW – Primer on visualization
PwC
The Finance challenge today:
What is at the top of your challenge list?
95%*
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June 15, 2017ACSW – Primer on visualization
PwC
Finance function of the future
Manage the performance of the enterprise
Drive business insights
Advise and support business
development
Model scenarios/risks
Perpetual close
Real-time forecast
Data ubiquity & availability
Process automation
Robust reporting
The disruptions will not be reserved only for the front office.
CFO’s and finance leaders are becoming key partners in the navigation of growth.
Finance can play a much more dynamic and facilitative role – data driven, forward looking, risk aware, collaborative. Finance shifts from providing static dashboards to sitting in the cockpit –able to pull levers and actively guide the business.
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Finance creating value as a business partner
Finance and actuarial organizations can look forward and use disruption to find opportunities to use predictive models and scenario analysis to gain greater confidence around future decisions.
Finance must evolve from…..
Data & transaction processing
•Minimal involvement
•Problem finding
•Post-hoc critique
•Confrontational
•Technical compliance with external rules
•Data collection
•Organizational hierarchy driven
•Technology constrained
•Manually intensive & cumbersome
•Policy view
•Redundant
•Risk and scenario based analysis
•Strategic/market issues
•Problem solving
•Embedded
•Accountability
•Cost/benefit sensitive
•Relevant to business
•Information rich
•Integrated
•Automated & streamlined
•Customer view
•Predictive
Decision support….Requires role transformation
Business controlRequires new processes
ReportingRequires new process & thinking
Data & transaction processingRequires better and faster integration
…..To
Leading organizations have 40% more FTEs in business insight roles than median performers
88% of organizations are working to enforce or execute their corporate level data strategy across finance
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PwC
Finance & Actuarial must lead and partner with businesses to make the right “bets” on innovation; it’s about looking forward
• Finance functions have the opportunity to define innovation and assert its role.
• The challenge is to steward, rather than stifle, innovation.
• Additionally, finance can provide structure and control around innovation enabling data.
• Align your organization with new innovation models and forge partnerships with strategic business units where innovations typically begin.
• Innovation resides in collaboration and cross fertilization between finance and other parts of the company. Finance and Actuarial functions have the analytical skills to advance the big data and predictive analytics.
• Assign finance/actuarial staff to proposed innovations on one of three “Horizons” with suitable expectations:
- Horizon One features products and services that increase revenues from known sectors in familiar markets.
- Horizon Two initiatives seek growth from products or services adjacent to existing sources of revenue.
- Horizon Three represents the game-changer—the brand-new idea that vaults beyond the competition.
• Consider internal big data and predictive analytics projects as an investment portfolio.
• Invest in “sensing and scanning” the external environment for potential opportunities and disruptors.
Steward for company-wide innovation and data
Align finance for innovation mindset and pathway creation
Manage internal and external portfolios
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Integrating data analysis across finance & actuarial
Along with a unique opportunity to drive innovation with the business, finance and actuarial must also maintain their steward roles across a set of new expectations and value propositions.
Taking new sources of data… …finding new ways of looking at the business
Socialmedia
Competitor data
Benchmarkdata
Marketdata
Employee data
Customer data
Customer data
Historicaldata
Opportun-itiesdataTrans-
actional data
Internal data
External data
Customer firstbig dataanalytics
Growth/Investment decisions: Where to invest
• Identify new markets, channels, and partnerships
• Rationalize investment for innovation/R&D
• Validate customer behaviors and economic outcomes
• Challenge and refine business cases
Performance and profitability management
• Analyze profitability levers
• Assess effectivity of business strategies
• Analyze customer acquisition and distribution costs
• Deliver customer and segment lifetime value analysis
• Drive planning processes with integrated analytics
Managing risk
• Consistent performance measures
• Integrated stress testing capabilities
• Collaboration and stewardship with data governance and model risk management
Risk data
Riskdata
42%spend significant time gathering and verifying data vs. reporting, analyzing and forecasting, etc.
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Deterministic & Predictive modeling Behavioral and simulation modeling
Simulation modeling strives to re-create real-world environments, employing scenario analysis to explore the full range of potential outcomes for a given strategy
Traditional approach Simulation approach
“Cockpit view”
Traditional approaches rely on statistical and AI algorithms to prescribe and predict actions based on historical data. Predictive modeling can be useful for forecasting aggregate outcomes, but it is not able to understand true drivers of the outcomes, such as how individuals make their decisions.
Simulate real-world relationships between consumers, providers, distributors, employers, and other system players. This approach is able to show how and to what extent internal (e.g., consumer attitudes) and external (e.g., rising inflation) dynamics can alter outcomes.
“Dashboard view”
-Starts with data-Data warehouses and marts-Requires translation-“Dashboard” (historical) view-“Siloed” thinking-Driven by large multi-year projects
-Static reports and graphs-Technology-led
-Starts with decisions-Data-driven mash-ups-Information in context-“Cockpit” (forward) view-“Systems” thinking-Driven by iterative and agile projects
-Dynamic visualizations-Business-led
Behavioral simulations provides insurers with richer and more long-lasting insights
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PwC
Actuarial Cockpit Prototype – Case study results
Even with “drill down” capabilities, true insight requires significant time and effort
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PwC
Finance innovators will need to develop tools and methodologies to support customer lifecycle analytics
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Actuarial Cockpit Prototype – Customer Behavior
We enhance the experience studies by enriching them with external data
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PwC
Actuarial Cockpit Prototype – Customer Behavior
Then, we take a look at what’s driving customer behavior and how to predict customer behavior over time
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Illustrative path of three low wealth households retiring in 2030
Fu
nd
ed
ne
ss L
ev
el
Ex
pec
ted
Ret
irem
ent
Sa
vin
gs
as
% o
fE
xp
ecte
d R
etir
emen
t E
xp
ense
s
Overfunded/
Secure
Underfunded/
Fragile
Constrained/
Stressed
137%
95%
25%
HH1
HH2
HH3
PwC
Actuarial Cockpit Prototype – Customer Behavior
What we get is a visual cockpit with scenario analysis and drill down provides self-service analysis capabilities
June 15, 2017ACSW – Primer on visualization
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PwC
Illustrative finance cockpit (P&C)
ExecutivePeriod LoB Filters
Scenario Generator
Cockpit (all products)
Inorganic model +Net Profit (US $m)Policy
Claim
Billing
Operations Combined Ratio Expense Ratio Loss Ratio
Quote & Hit Ratio Retention & Cust…. GWP & NEP (US $b)
370.00
400.00
425.00
300.00
350.00
450.00
800.00
820.00
900.00
320.00
425.00
440.00
310.00
2020
2019
2018
2017
2016
2015
2014
2013
2012
PlanActual
Acquisition
85%
90%
95%
100%
Actual vs Plan
W/transw/o trans
0%
10%
20%
30%
Actual vs Plan
W/transw/o trans
50%
52%
54%
56%
58%
Actual vs Plan
W/transw/o trans
20%
40%
60%
80%
QuoteHit 50%
70%
90%
Customer Sat.Retention
GrossNet
12 13 14 15 16 17 18 19 20
15
10
5
0
Notes:
Summary and detail views of the key performance metrics
Key performance metrics that are
interactive
Event/scenario timing
Period and line of business filtering
Scenario generator to model different events
or stresses
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Illustrative finance cockpit (Life)
ExecutivePeriod LoB Filters
Scenario Generator
Cockpit (all products)
Inorganic model +Net Profit (US $m)Sales
Performance
Profitability
Capital Mgmt Sales VNB IRR
RBC ratio ROE Duration
370.00
400.00
425.00
300.00
350.00
450.00
800.00
820.00
900.00
320.00
425.00
440.00
310.00
2020
2019
2018
2017
2016
2015
2014
2013
2012
PlanActual
Acquisition
0
1,000
2,000
3,000
Actual vs Plan
W/transw/o trans
0
100
200
300
Actual vs Plan
W/transw/o trans
8.0%
9.0%
10.0%
Actual vs Plan
W/transw/o trans
-100.0%
100.0%
300.0%
500.0%
Actual vs PlanW/transw/o trans
7.0%
8.0%
9.0%
10.0%
W/transw/o trans
AssetsLiabilities
12 13 14 15 16 17 18 19 20
15
10
5
0
Notes:
Actual vs Plan
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PwC
Illustrative finance cockpit (PwC Prototype)
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June 15, 2017ACSW – Primer on visualization
PwC
Illustrative finance cockpit (PwC Prototype)
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June 15, 2017ACSW – Primer on visualization
PwC
Illustrative finance cockpit (PwC Prototype)
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June 15, 2017ACSW – Primer on visualization
PwC
Illustrative finance cockpit (PwC Prototype)
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June 15, 2017ACSW – Primer on visualization
PwC
Visualization “cockpits” can be created to evaluate market entry strategies and growth-profitability tradeoffs in markets/product lines.
Illustrative example – Market entry strategies
Emerging markets insurance flight simulator
A “cockpit” has been created to simulate client’s share of insurance markets – complete with
competitor and market dynamics
Tradeoff between growth and profitability in commercial sector
Case study client
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June 15, 2017ACSW – Primer on visualization
PwC
PwC perspective on key architecture elements to enable cockpits, analytics
• Actuarial, finance and IT must be equal partners in building and maintaining quality metrics
• Delivering quality and consistent data to models is the linchpin to enabling management cockpits
• The discipline of system design lifecycle should be applied with vigor to both data infrastructure and the development and maintenance of actuarial models
• Valuation and projection model development should be integrated and efficient, as well as capable of all needed metrics
• Visualization tools provided to management need to be well controlled to ensure the integrity of metrics
• Decisions around data warehouse components can be distracting and meaningless if the ultimate design lacks strong controls
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PwC
Modernized data, model and visualization infrastructure will be crucial to power insights
Internal Extracts Data Warehouse
Destination Systems
ValuationSystems
Models
Valuation & Modeling Processes
ET
L P
ro
ce
ss
Analytical & Reporting Processes
Data Aggregations Analytical Tools
• Standard reports
• Queries
• Report writers
• Dashboards
• Cockpits
• Analytics
Governance and Controls
Controls
Policy Data
Transactions
Model Results
Operational Data Store
General Ledger
Me
tad
ata
La
ye
r
. . .
External ExtractsSource Systems
External Sources
Bloomberg
Federal Reserve
Ex
tra
ct,
Tr
an
sla
te a
nd
Lo
ad
Pr
oc
es
s (
ET
L)
Internal Sources
Policy Administration
Claims Systems
Bond Prices
Option Prices
Interest Rates
Policy Data
Financial Transactions
Client Data
Ex
tra
ct
Pr
oc
es
se
sEnvironments
• Laboratory
• Development
• Production
. . .. . .
1 2 3 4
5 6
7
. . .. . .
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June 15, 2017ACSW – Primer on visualization
www.pwc.com/us/insurance
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PwC
Micro-site and Recent Publications
Insurance Modernization Stakeholder Analysis:Who does it impact?
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June 15, 2017ACSW – Primer on visualization
Insurance modernization:The role of advanced analytics
Stepping into the Cockpit:
Redefining finance’s role in the digital age
Insurance modernization:
Developments in insurance contracts accounting and reserving
Insurance modernization:
New metrics: Increased efficiency, lower costs and better analysis
http://www.pwc.com/us/en/insurance/insurance-modernization.html