ldimovski

Taking Control of Risk Research Data

Blog Post created by ldimovski on Apr 27, 2016

Risk rating systems have been prevalent within our risk insurance market for over 20 years and would be one of the leading factors that contributed to the marked improvement in the quality of policy terms and conditions. Despite their widespread use, many in the industry have yet to fully appreciate how risk research systems are developed and how they can be best used within an adviser’s product recommendation process.

 

Risk Researcher allows the adviser to take control of the qualitative risk research comparison data and shape it in a way that will assist with meeting the ‘know your product’ obligations under best interest duty when placing life insurance products for clients.

 

Tailoring Product Scores to Your Client

Many risk research system adopt some sort of scoring system. Using default product scores as anything else other than a quick snapshot guide or a starting point to obtain an opinion around the feature richness of a product may be detrimental to the recommendation process. The obligations that come with best interest duty cannot be met with a reliance on a 4 to 5 point differentiation in product scores to recommend one product over another without further qualifying how the extra coverage will cater to meet the client’s protection needs.

 

The main limitation with default product scores is that some risk research systems may automatically incorporate optional benefits into the score, which on most occasions will not reflect the cover that is actually recommended to the client and hence the so called ‘quality’ of the product is overstated.

 

The IRESS risk research system overcomes this limitation by adopting a sophisticated and dynamic scoring methodology that will take note of what optional benefits are or are not added to the client’s recommendation modelling scenario and adjust the provision ratings accordingly to provide a ‘Scenario Score’ which closely reflects the cover that the client ends up receiving at the price they are actually paying.

 

A good example to illustrate Scenario Scoring would be the Claims Indexation Benefit which is a common feature amongst all retail income protection products but not always as an in-built benefit. Under the ‘Scenario Score’ approach, if this option is not selected as part of the premium model then the rating for Indexation on Claim reverts to a ‘No’ rating for all products that do not have this feature as an in-built benefit, and accordingly the score gets adjusted down to reflect that the client will not have access to such a feature.

 

Replace Numeric Scores with Star Ratings

Advisers who like to be able to produce comparisons with some sort of overall product quality indicator may want to explore the option of using the star rating system in place of the numeric product score.

 

The star rating system provides a couple of advantages in that it is customisable by allowing the adviser to specify the numeric score range to apply to each star rating level; and (ii) avoids the need to justify a difference of only a couple points between Product A and Product B where both products meet the client’s protection requirements.

 

Research Software Tools to Fit Your Approach

A quality risk research system will provide additional capabilities for an adviser to apply their own overlay to the core research comparative data, allowing it to be tailored to suit the adviser’s style or approach to recommending insurance products for their clients.

 

Risk Researcher provides advisers with a number tools that advisers could consider using to assist with their recommendations. These include:

 

Function

Description

Feature Finder /

Compare Features

 

The ‘Feature’ level of the IRESS Rating Methodology breaks down each of the evaluated provisions into smaller components allowing advisers to differentiate between products at a more intricate level that is represented in an easy to understand format.

Rather than trying to determine what an A, B, or C rating means, advisers can select simple descriptors such as ‘Heart Attack - 100% for clinical diagnosis’ or ‘Wait Period – No Total Disability Requirement’ as requirements and generate a short list of products that meet the client’s needs without ever having to refer to a product score.

Compare Differences /

Replacement Advice

This tool leverages of the ‘Features’ level research data in order to provide a quick and efficient summary of differences in cover between selected products without referring to product scores.

Integrated into Scenario Modelling, this powerful function makes the process of producing replacement of advice records seamless and highly efficient while providing the flexibility to determine the benefits gained and lost items that you want to include in your SoA.

Weighting Profiles

Not happy with the impact that a particular provision has on product scores? Do you think provision X should have a higher weighting?

No problem, the Weighting Profile module allows the adviser to build a scoring profile by weighting the importance of each and every evaluated provision.

The weighting profiles also allow you to determine minimum rating requirements for any evaluated provision, automatically removing any products that do not these requirements within your comparisons, ensuring that all products listed are appropriate to the client irrespective of product score.

Outcomes