Solvency II Strategic
Implications on Financial
Modelling
Martin Sher
MG-ALFA European Product Manager
November 2010
Solvency II is Driving Shift From Desktop to
Enterprise Risk Analytics
Policy-by-policy EV Liability
Focused
Centralised code and assumption
management.
Deterministic or limited
number of scenarios
Data warehouses, usage rights,
transaction logs, roll-back, regression
testing, web-based access etc
Decentralised desktop Excellike usage paradigm
Stretch modelling
capabilities.
Replace or supplement
internal fixed capacity.
Daily solvency monitoring. active
hedge programs, risk dashboards.
Stochastic (and stochasticon-stochastic) modelling.
Consistent with and complement
the production cycle actuarial
reporting analytics
Separate product and model
development environments.
More frequent and shorter reporting
timeframes.
Standard production schedules.
Impact on operational and
processing demands on actuarial
resources.
Increased Asset Types
Automated data feeds.
Advanced investment and
disinvestment strategies
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Number and size of runs.
Results aggregation and version
control
Increased pressure to reduce costs.
Mainstream corporate
systems.
Same executive
attention and IT
disciplines as other core
corporate technologies
eg accounting systems
Resulting in an Expanded Actuarial IT
Landscape
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IT Characteristics
ƒ Includes all Pillar I analytics including internal tools (often Excel
based)
ƒ Typically web-based interface to facilitate widespread access
ƒ Fundamentally different and orders of magnitude more
sophisticated technologies than currently adopted by actuarial
departments
ƒ Centralised internal or hosted data centre
ƒ Requires active involvement and management by corporate IT
department
ƒ Internal and external resources
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Web User
External
Data &
Results
Warehouse
5
Check In/Out Model
Import, Export,
View, Edit
FTP Upload, Download
Model
Storage
Data Storage
Results
Storage
Job
Repository
Audit &
Control
Repository
Job Execution, Monitoring
Desktop User
Model & Data Version Control, Data Access,
Reporting, Job Scheduling, User Administration
Future Solution
Processing
Processing Capacity
Capacity
Production Processing
Objectives
–
–
–
–
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Automated
Controlled
Auditable
Reliable
Solution
– Client-server system
– Version control with
disaggregated data
model
– Access control
– Scripted job streams
– Dynamic provisioning of
resources
Web User Interface Functionality
SAS Data
Warehouse
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Model Management Review
Development Model
Production Models
8
Hosting Options
ƒ Cloud computing resources from, for example, Microsoft Azure
ƒ Dynamic capacity charged on CPU per hour usage basis
ƒ Extensive scalable storage
ƒ Multiple data centres with “live” mirroring of data
ƒ Backup, redundancy, high bandwidth etc
ƒ Global access
ƒ Combine internal and cloud resources
ƒ Outsourced model maintenance and management
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Reporting Cycle and Daily Solvency
Monitoring Integration
Actuarial Projection
Calibrate Using Closed
Form, Replicating Portfolio,
Curve Fitting, Hedge
Sensitivity and other
techniques
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True Up and Recalibrate
Milliman is Implementing such a Solution at
Phoenix UK
“Having acquired many companies with a variety of actuarial projection
systems and models, we sought a provider who can work closely with us to
simplify, rationalise, and streamline our processes. We must be able to gain
Solvency II internal model approval, monitor and manage our risks on a daily
basis and drive internal operational efficiency savings across our full
business. We believe that the combination of Milliman’s consulting expertise,
the MG-ALFA® actuarial projection system and the Daily Solvency Monitoring
System (DSMS) offers us such a solution.”
Andy Moss
Phoenix Life Finance Director
September 2010
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Conclusions
ƒ Requirements and implementation solution largely independent
of:
– Size of organisation
– Internal or standard SII model
ƒ Difference is:
– Scale and capacity of organisation to implement internally or
through external support
– Whether to use existing actuarial system/models or implement new
solution
– Whether to host internally or seek to outsource infrastructure and/or
model operation
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