WealthEngine

The Wealth Score provides a new dimension in wealth analytics and targeted fundraising. It is available on individual profiles and can be used to filter your results in the My Profiles area of the WE Platform. 

This article will provide a comprehensive overview on how to read this score, as well as how it is calculated – and why that makes it so special. 

This article will cover:

• Definition and Use Case
• Calculating the Score
  • Why start with the P2G?
  • Why add modeling?

Definition and Use Case

The Wealth Score is arguably the most robust of Wealth Engine’s ratings and scores. It is a numeric score that rates a person’s overall financial health, considering all forms of modeled assets (financial wealth, property value, physical assets, etc.) and liabilities (mortgages, auto loans, revolving credit, etc.) It provides an easy 360-degree view to accelerate the most effective prioritization and targeting of prospects.

The Wealth Score is assigned to each profile in the range 1-100 and takes into account multiple wealth signals for modeling.

• Note: Records such as net worth and some types of debt are private information. For this reason, we calculate those attributes using complex models that our data scientists have built using a truth file.

Calculating the Score

The Wealth Score, as it is being generated for each profile, has two key steps in its calculations that highlight its purpose and value:

• The P2G offers a starting foundation by initially dividing people into categories.
• Complex models utilize the Wealth Ratings and other key attributes to segment people even further from there.

In other words, the Wealth Score builds upon Wealth Engine’s existing Propensity to Give score and Wealth Ratings. The P2G score incorporates all the data in the profile, whereas the Wealth Ratings only apply to the more traditional wealth and assets information.

It provides an easy-to-read, comprehensive measurement that takes full advantage of our existing scores and combines their strengths. Using the Wealth Score, you can now differentiate and prioritize profiles with a greater level of detail than ever before.

Let’s dig a little deeper:

Why start with the P2G?

The Propensity to Give has historically been Wealth Engine’s flagship score, presenting the most complete picture of a person.

The P2G is unique in that it incorporates all the data in the profile. It will consider the strength and predictive value of specific data source matches (e.g. a tie to a family foundation) as a way of identifying top prospects. In this way, the P2G is not limited to traditional wealth and assets information. This is important because some wealthy people may have managed their finances and estates so as to make it look like they don’t own anything. The P2G is specifically designed to catch those individuals. 

Why then add modeling?

The P2G score, while incredibly valuable, is a relatively straightforward rules-based classification system. It does not utilize the more sophisticated machine learning techniques of the Wealth Ratings.

After all, if you have screened a large file, or pulled a large group from the Prospecting area of the platform, then you may have found that you had a large number of people who all had the same P2G score. Not all of those individuals are equally promising as prospective major customers or clients. However, you still want to make sure that you are allocating your resources correctly and prioritizing the best of your best! To account for this, our data scientists have built five complex new models that utilize key attributes such as: Age; Total # of Real Estate Properties; State Political Donations; Total Net Worth; Total Income; Total Debt; and Total Real Estate Value.

Those Machine Learning techniques will further slice and dice your list so that you can truly focus in and maximize your fundraising:

• Note: for more information on how the P2G itself is calculated, check out our detailed P2G Guide.

To illustrate this, let’s say that you have a Jane Smith and a John Doe.

• Jane Smith has a P2G of 1/4. That means Model 2 will be used to calculate her Wealth Score. 
• John Doe, on the other hand, has a P2G of 3/1. As a result, Model 4 will be selected. 

Once the correct model has been applied to the profile, the Wealth Score is generated based on those additional calculations - this is the number between 1 and 100. Remember, the higher the number the better! 

Keep in mind that some of these attributes (such as Net Worth, Total Debt, etc) are statistically derived, as we cannot see into anyone’s bank accounts or tax filings. Instead they are based on insights we have gleaned using a truth file. Jane Smith doesn't necessarily have $5,000 in debt - but based on our complex and extensively-researched algorithms, her profile closely resembles people who do.

At the end of the day, the Wealth Score takes predictive analytics to the next level by combining the best parts of both the P2G and modeled scores like the Wealth Ratings. It applies state-of-the-art machine learning techniques across all the features associated with a profile, taking visible wealth and assets into consideration, but without being limited by them.