Risk Management
Task Force

Risk Management Metrics (RMM) Subgroup Minutes


Risk Management Metrics
January 21, 2005
9:00 a.m. Central Time

Participants: Fred Tavan, Julie Perks, Bernie Rabinowitz, Michele Goldberg

Development of Fuzzy Logic Model for Competitive Risk

We first defined Competitive Risk as the risk that competition in the market may lead to loss of future business resulting in reduced profits.

Then we tried to follow the following steps:

  1. Identify possible Key Risk Indicators (KRI's)
  2. Select linguistic variables/descriptors for each KRI (e.g. High, Medium, Low, or Poor, Average, High
  3. Develop a reasonable numerical scale for each linguistic variable


We identified and discussed several different types of KRI set alternatives:

Set 1 was made up of :

1. "Irrational Competitors"

  • price cutting to obtain market share
  • unsound business practices that invoke more regulation
  • Target of unfavorable publicity that hurts the industry

2. New Competitors

  • Market saturation
  • Increased competition for distribution channels and agents
  • Increased competition for management and staff

3. Current (and new ) competitors

  • New ways to compete (e.g. new value proposition or new paradigm)
  • New products
  • New technologies
  • New distribution channels
  • More capital rich
  • Hiring away qualified personnel
  • Increased competitive advantage

Set 2 was made up of:

  1. Number of competitors
  2. Market Share
  3. Trend
  4. Position in cycle (ie.Early/Innovation to mature)
  5. Number of applications received per year
  6. Marketing strategy (lowest cost, high value, highest quality)
  7. Competitive advantage ( patent, copyright, barriers of entry, technology, size)
  8. number of mergers occurring
  9. losing employees to competitors
  10. types of competitors
  11. competitors unit costs or profitability

While the brainstorming that led to step 2 was useful, it generated too many different types of potential KRI’s. It was important to reduce the list to a manageable set of 4-5 KRI’s. Using set 2, we then brainstormed a reduced set as follows:

Set 3:

  1. Pricing (in relation to competition)
  2. Innovation (generic products vs. specialized boutique type)
  3. Distribution Channel (limited to brokers vs. multi-channel)
  4. Customer Service (relative to competition)
  5. Losing Key Employees to Competitors (quit rate going to competition)

We all agreed that we would move forward with Set 3 as our KRI’s for competitive risk.


We tried to identify linguistic variables/descriptors for each of the 5 KRI’s identified in step 1.


High risk: prices are higher than most/all competitors
Medium risk: prices are in the middle of the pack relative to competitors
Low risk: prices are lower than most/all competitors


High risk: portfolio of products that are generic and can be easily duplicated
Medium risk: portfolio has mix of high and low risk
Low risk: portfolio consists of specialized products that are difficult and time-consuming to develop.

Distribution Channel

High risk: A single distribution channel that is small in size and made up of brokers. Customers have lots of accessibility to shop around
Medium risk: Medium size distribution channel with access to both brokers and agents
Low risk: Company has multiple distribution channels including agency force which operates in regions where customers do not have accessibility to shop around

Customer Service

High risk: Offer less customer service than competition (e.g. no call center, long response times, no CRM systems)
Medium risk: Service is good but not necessarily better or worse than competition.
Low risk: Offer more customer service than competition (e.g. 1-800 numbers to call with immediate response times, state of the art CRM systems in place)

Losing Key Employees to Competition

High risk: High percentage of those quitting are going to competition
Medium risk: A small percentage of knowledgeable staff are going to competition
Low risk: No one or low percentage of those quitting are going to competition

We will continue with step 3 (develop numerical scales for each set of descriptive variables) at the next meeting. Bernie will also start the development of a model company and the associated competitive landscape in order to facilitate the continued development of this Fuzzy Logic model example.

Next Meeting
The next meeting will be held on February 14, 2005 at 9AM central.

Fred Tavan, FSA, FCIA
Leader, Risk Metrics Working Group

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