# Introduction to Metrics

# Overview

Intelligent Risk Platform™ leverages exposure data and peril models to calculate that risk of financial loss posed by a particular exposure. The result of this analysis job is a record called an *analysis result*. The analysis result contains metrics that estimate of the financial risk posed by an exposure.

The Risk Modeler API MetricsV1 and MetricsV2 collections expose operations that enable you to view analysis results, retrieve metrics from those results, or generate new results based on existing results by means of a post-analysis action.

# Understand metrics

Analysis results include various metrics that enable you to measure the projected risk to an exposure. Metrics include EP metrics, ELTs, PLTs, and statistics.

## EP metrics

The Exceedance Probability (EP) or stochastic analysis option runs a full probabilistic analysis on the exposure at risk, producing curves that are cumulative distributions showing the probability that losses will exceed a certain amount, from either single or multiple occurrences. These losses are expressed in the occurrence exceedance probability (OEP) and the aggregate exceedance probability (AEP) curves. AEP and OEP curves are two different curves that have two distinct uses and offer different information. Both curves show the probability that losses will exceed a given threshold.

The Get EP Mertrics operation returns the following metrics for each analysis result.

```
[
{
"id": 8,
"workflowId": 9064540,
"position": "GU",
"portfolioId": 8,
"variationId": 0,
"dimensions": [
""
],
"metricName": "AEP",
"metricValue": [
{
"id": 0,
"value": {
"returnPeriods": [
1.0,
2.0,
3.0,
4.0,
5.0,
...
50000.0
],
"positionValues": [
0.0,
0.0,
0.0,
0.0,
1.4336826286215238,
...
2898128.185059362,
2923391.5767636155
]
}
}
]
}
]
```

## Event loss tables

The event loss table (ELT) is an output table that contains information about the loss-causing events in an analysis, including the mean loss standard deviation (split into an independent and a correlated piece), exposure value, and event rate.

The ELT is the basis of losses for all financial perspectives at all exposure levels and is used in computing output statistics.

The Get ELT Metrics operation returns the following metrics for each analysis result.

```
[
{
"anlsid": 83343,
"id": 8,
"sourceid": 22267,
"eventid": 2865697,
"perspvalue": 3473657.880534969,
"perspcode": "GU",
"stddevi": 1066771.2741421806,
"stddevc": 400576.7724183246,
"expvalue": 4343900.0,
"rate": 1.2056769946866552E-6,
"status": 0,
"peril": "Windstorm",
"region": "North America",
"oepWUC": 1.205676267823641E-6
}
]
```

## Period loss tables

The period loss table (PLT) is an output table that simulates event losses over the course of a time period, providing greater flexibility to evaluate loss metrics than the analytical calculations based on event loss tables (ELTs).

By simulating events through time, a model computes total loss as well as maximum event occurrence loss for each simulation period in the table, and generates loss statistics based on the distribution of losses across the large number of simulated periods. This methodology can calculate the impact of all contract terms, including terms with time-based features, such as contracts that are shorter (or longer) than a single year.

The Get PLT Metrics by Result operation returns an array of PLT metrics for a specific analysis result.

```
[
{
"periodid": 503,
"weight": 2.0E-5,
"eventid": 3508644,
"eventdate": "2020-08-07T00:00:00.000Z",
"lossdate": "2020-08-13T00:00:00.000Z",
"perspvalue": 111642.35349968076,
"peril": {
"id": 0,
"code": "FL",
"name": ""
},
"region": {
"id": 0,
"code": "EU",
"name": ""
},
"exposureNumber": ""
},
...
{
...
}
]
```

## Statistics

Statistics include the average annual loss, standard deviation, and coefficient of variation.

The Get ELT Tables operation returns the following metrics for each analysis result.

```
{
"anlsid": 83343,
"id": 8,
"sourceid": 22267,
"eventid": 2865697,
"perspvalue": 3473657.880534969,
"perspcode": "GU",
"stddevi": 1066771.2741421806,
"stddevc": 400576.7724183246,
"expvalue": 4343900.0,
"rate": 1.2056769946866552E-6,
"status": 0,
"peril": "Windstorm",
"region": "North America",
"oepWUC": 1.205676267823641E-6
}
```

# Post-analysis actions

A post-analysis action is a process that generates a new analysis result based on an existing analysis result, a result called a *base analysis*.

Analysis workflow jobs generally require substantial time and resources to complete. Post-analysis actions enable you to expedite the generation of results by making adjustments to the parameters used to generate an existing result, and thereby avoid re-running expensive or time-consuming analysis jobs from scratch. The post-analysis action leverages an existing analysis result, as a "base analysis".

The action recalculates projected losses by substituting operation parameters for the parameters that were specified in the reference analysis.

The following Risk Modeler operations generate analysis results as post-analysis actions:

- Convert Result Currency generates a new analysis result by substituting a different currency for the currency used in the base analysis.
- Convert Event Rates and Losses generates a new analysis result based on an existing portfolio-level EP result by applying event rate or event loss adjustments to the original result.
- Simulate PLT Analysis generates a new PLT-based analysis result based an existing ELT-based analysis result.
- Convert Financial Perspectives generates a new analysis result by substituting a new financial perspective for the specified in the base analysis.
- Recalculate result EP and statistics generates a new analysis result based on the base analysis. The process recalculates EP losses and statistics using the specified analysis result as a base analysis.
- Recalculate result with PATE recalculates losses by substituting new treaty terms for the terms specified in the bases analysis. Post-analysis treaty editing (PATE) enables reinsurers (primary insurers and underwriters to create new treaties or make adjustments to existing treaties based on the losses projected in analysis results.
- Calculate Marginal Impact Report generates a report that measures the effect of adding accounts to an existing portfolio as differential losses.
- Calculate Climate Change generates an analysis result that measures the effects of climate change by leveraging an existing analysis result as a base analysis.

Updated 3 months ago