Bahnemann Flashcards

1
Q

Panjer’s Recursive Algorithm

A
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2
Q

Size view of losses

A
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3
Q

Layer view of losses

A
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4
Q

Expected losses in a layer

A

E[X; a; l] = E[X; a + l] - E[X; a]

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5
Q

Excess loss conditional on a claim exceeding retention

A

Mean residual life at a

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6
Q

Graphs of excess severity

A
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7
Q

Mean and variance of excess claim counts

A

p = probability that a loss exceeds a

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8
Q

Impact of inflation in fixed excess layer

A
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9
Q

Impact of severity inflation on excess counts

A
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10
Q

Impact of severity inflation on aggregate losses

A
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11
Q

Mean and variance of aggregate losses in a layer

A

Claim contagion parameter (accounts for claims not being independent of each other)

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12
Q

What the risk charge covers

A

Contingencies such as process and parameter risk

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13
Q

ILF assumptions

A
  1. All UW expenses and profit are variable and do not vary by limit
  2. Frequency and severity are independent
  3. Frequency is the same for all limits (may not be true due to adverse/favorable selections)
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14
Q

Price of a layer of coverage using ILFs

A
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15
Q

Consistency in ILFs

A

Increasing and doing so at a decreasing rate.

Premium for successive layers of coverage of constant width will be decreasing

Violation: adverse selection, lawsuits influencing size of limits (frequency would not be the same)

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16
Q

Risk loaded ILFs

17
Q

Risk load: Miccolis approach

18
Q

Risk load: ISO approach

19
Q

Premium for policy with limit l and deductible d

20
Q

Pure premium after inflation

21
Q

LER relationship for the three different deductible types

A

Straight

Diminishing

Franchise

22
Q

Franchise deductible

A

Loss is truncated but not shifted

23
Q

Diminishing deductible

24
Q

Advantage/disadvantage of Panjer’s

A

Good for small frequency of claims

Only a single severity distribution can be used

25
Issues with using lognormal distribution
No ability for loss-free scenario (ln 0 is undefined) No easy way to reflect impact of changing per occurrence limits on aggregate limit
26
Theoretical curve fit for excess severity if curve is flat
Exponential
27
Theoretical curve fit for excess severity if curve is linear
Pareto
28
Theoretical curve fit for excess severity if curve is decreasing exponentially
Gamma
29
Theoretical curve fit for excess severity if curve curves up
Lognormal
30
Theoretical curve fit for excess severity if curve is concave down
Weibull
31
Issue with fitting excess severity curves
Data usually thin and volatile at the higher amounts -- difficult to see a pattern
32
Pricing a layer of coverage and applying a risk load
Can't simply subtract risk loaded ILFs (incorrect resulting risk load)
33
ILFs that account for both claim and aggregate limits
E[Sl;L] / (E[N] x E[X;b])
34
Impact of inflation on deductibles
35
ILF after inflation
ILF of the deflated limit DIVIDED by the ILF of the deflated basic limit
36
Basic pure premium after inflation
Freq x Sev x (1 + t) x deflated basic limit