OPTIMISING INSURANCE POLICY
DECISIONS FOR THE POWER
INDUSTRY USING PALISADE
SOFTWARE
May 2012.
Who are we
EPM is the second largest business group in Colombia, consisting of 42 enterprises (18 in Colombia,
and 24 overseas) that acts in the sectors of Electric Energy, Natural Gas, Waters and
Telecommunications, with investments in most of Colombia, Panama, Guatemala and El Salvador.
Maxseguros is EPM’s captive reinsurer, founded in Bermuda in 2008, , with the purpose of reinsuring
the risks of its parent company and its subsidiaries.
Under Bermuda Insurance Act, Maxseguros is a Class 2 captive reinsurer, and is authorized to
negotiate policies for Property, Terrorism, All-Risk Construction, Directors and Officers, Infidelity and
Financial Risk.
WhoWe
We Are
Who
Are
JLT Re COLOMBIA is the first reinsurance brokerage company in Colombia with over 30 years of
experience in the reinsurance brokerage. JLT Re Colombia is the leader in the Colombian
reinsurance consultancy market for many industries including Oil & Gas, Energy Construction,
Aviation, Financial Lines, among others.
JLT RE Colombia is a subsidiary of Jardine Lloyd Thompson Group PLC (JLT Group PLC). JLT
Group PLC, based in London and founded in 1832, is a leader in risk management, insurance
and reinsurance brokerage and benefits. Through affiliated companies and subsidiaries, JLT has
over 100 offices world-wide in 36 countries and employs over 6,000 people.
Introduction
Transformers Model is:
An in house development
A real time decision tool
An on going tool
An idea that works With one policy: Keep it simple
What is the issue?
Insurance policies are important mechanisms for transferring risk and are essential for
businesses needing to protect themselves from unforeseen events.
The insurance world contains an infinite amount of different policies based on changing
parameters such as deductible, depreciation which affect compensations.
How then can you choose the optimal policy which suits the randomness (risk) of your
assets?
How do you solve it?
Our model calculates an optimal policy (a policy which reduces Cost of Risk) given the
following:
A set of stochastic conditions (probability of failure).
A set of insurance policies (premiums, deductibles and depreciation)
Although you could apply this to many different forms of assets – for the purpose of this
presentation we have used Power Transformers.
What is a Power Transformer?
Power transformers are one of the most valuable
assets in sub-stations and power plants. They are
high-voltage
equipment
used
for
power
generation, transmission and distribution systems.
Our model considers a fleet of generation and
transmission transformers, utilizing their age as
the key input for evaluating probability of failure
and we utilize voltage capacity and price as key
inputs for evaluating potential loss during an
event.
Probability of failure
Application 1
Policy Negotiation Support:
Considering the randomness of the insured risk.
Policies conditions.
Transformers conditions.
The Cost of the Risk.
Application 1: Policy Conditions
Deductible: amount of loss that insured pays in a claim; includes the following types:
•
Absolute dollar amount
•
Time period amount (Business interruption)
Depreciation: Actual or accounting recognition of the decrease in the value if hand
asset (property) over a period of time, according to a predetermined schedule such as
straight line depreciation.
Premium: rate that an insured is charged, reflecting his or her expectation of loss or
risk. The insurance company will assume the risk of the insured in exchange of a
premium payment .
Application 1: Cases
DEDUCTIBLE
DEPRECIATION
ALTERNATIVES MATRIX
1
2
1
Case 1,1
Case 1,2
2
Case 2,1
Case 2,2
Application 1: Potential Total Loss Sensitivities (%)
Transferring/Retention Graphs
X: Transformers; Y: Percent of the Loss
Depreciation, Deductible, Compensation
Application 1: Potential Total Loss Sensitivities ($USD)
Transferring/Retention Graphs
X: Transformers; Y: Percent of the Loss
Depreciation, Deductible, Compensation
Application 1: Potential Partial Loss Sensitivities(%)
Transferring/Retention Graphs
X: Transformers; Y: Percent of the Loss
Depreciation, Deductible, Compensation
Application 1: Potential Partial Loss Sensitivities ($USD)
Transferring/Retention Graphs
X: Transformers; Y: Percent of the Loss
Depreciation, Deductible, Compensation
Application 1: Monte Carlo Simulation
The model is based on a Monte Carlo Simulation for the creation of possible failure
scenarios for a population of power transformers using:
INPUTS (211)
Total probability of failure (includes partial and total failure); and
Probability of total failure (includes only total failure)
OUTPUTS (55)
Number of Failures, Depreciation, Deductible and Compensation.
Bernoulli
Distribution
Application 1: Monte Carlo Simulation
ILUSTRATION OF THE SIMULATION.
Application 1: Risk Results (Number of Failures
and Total Loss)
Mean:4.27
Mean: 2,367,648
Application 1: Risk Results (Depreciation)
Application 1: Risk Results (Deductible)
Application 1: Risk Results (Compensation)
Application 1: Risk Results
Application 1: Cost of Risk
To fully assess and choose the optimal policy we now have to consider what are
the potential costs to be paid for different levels of coverage (Cost of Risk).
Cost of Risk = Depreciation + Deductible + Premium
Self-Retention
Cost of Risk
Application 2
As the power transformers get older their risk profile changes and thus the
chosen policy is no longer optimized.
This application shows the changing condition of the policy over time and
indicates when to commit a major overhaul and whether to improve the
maintenance program over a period of 10 years.
Application 2:
Application 2:
Study Case
This model was utilized by Maxseguros, the Reinsurance company of he EPM
GROUP, to assess the material damage coverage for a subsidiary and to assist in
policy negotiation.
The conclusion of the policy negotiation was:
A simplified policy structure
Elimination of USD 500,000 per year of premium which only provided an
average coverage of USD 130,000 and up to USD 350,000
(90th
percentile)
Reduction in the deductibles implying a premium increase of USD 50.000
and a risk transferring on average USD 120,000 and up to USD 270,000
(90th percentile).
Conclusions
More effective policy negotiation:
Retention/Transferring analysis
Analysis of offered policies from Insurance and Reinsurance agencies
Conditions negotiation (Deductible and Depreciation)
Improved risk management:
Cost of Risk calculation based in a stochastic vision
Evaluation of maintenance programs and overhauls
Probable maximum loss (PML) calculation
This decision-making model is a powerful tool for supporting the decisions in the policy
negotiations, based on risk quantification by using random variables.
SUMMING UP
Transformers conditions
Depreciation
Total Prob of Failure
MODEL
Deductible
Compensation
Number of Failure
Policy Conditions
Premium
Total Loss
Cost of Risk
The Decision
What is next?
Consider more variables that can affect the Probability of failure of
Transformers, such as weather and operating conditions.
Designing and optimizing of maintenance programs and overhauls.
Adapt the model to be utilized by other asset classes (generators, vehicles)
Adapt the model for the interests of Insurance or Reinsurance agencies.
¡Thanks!