Financial Scoring

The SPENDiD Financial Scoring service uses demographic behavioral modeling and any customized known fixed expenses to create two predictive cash flow health index values, plus a numerical Predicted Saving Ability (monthly). Each index is built to represent a familiar 0-100 "grade" scale easy for the public to understand. A positive Predicted Saving Ability will result in a SPENDiD Score of 80 or higher (a "B" grade or better). These index values can be easily modified to a different preferred scoring metric for any given application's use case by adding to or "factoring" the index value to meet the application's preferred presentation scale.

We'll detail each score and use cases in the guide.

The first index is the SPENDiD Score which uses the calculated Predicted Saving Ability as the numerator for index calculation:

curl --request POST \
  --url \
  --header 'accept: application/json' \
  --header 'content-type: application/json' \
  --header 'x-api-key: your_api_key' \
  --data '
    "demographics": {
        "age": 40,
        "gross_annual_income": 131613,
        "household_members": 4,
        "is_homeowner": true,
        "net_annual_income": 102000,
        "zip": "77479"
    "budget": {
        "mortgage_and_rent": 19200,
        "vehicle_purchase_and_lease": 9600,
      "health_insurance": 0,
      "other_debt_payments": 3600

The second index is the SAVINGS Score which incorporates the impact of a specifically expressed periodic Savings amount:

  "demographics": {
    "age": 25,
    "gross_annual_income": 56376,
    "household_members": 1,
    "is_homeowner": false,
    "net_annual_income": 42000,
    "zip": "35210"
  "budget": {
    "mortgage_and_rent": 6000,
    "vehicle_purchase_and_lease": 3000,
    "savings": 2000,
    "health_insurance": 0,
    "other_debt_payments": 0

SPENDiD returns the user's Predicted Saving Abiity and Score indexes as shown below:

  "Predicted Saving Ability": "17431",
  "SPENDiD": "97.1",
  "SAViNGS": "90.6"

Predicted Saving Ability (PSA)

SPENDiD can determine a User’s Predicted Saving Ability (PSA) based on their simple Demographic and known Fixed Expense inputs. A higher SPENDiD Score will result in a larger PSA, while a lower SPENDiD Score might even result in a negative PSA amount. This Predicted Saving Ability can serve as motivation and a benchmark for greater savings achievement and/or expense reduction. The PSA amount may also be useful as a secondary lending qualification metric indicating an applicant's relative ability to pay based on their current cash flow health. This can be useful in situations of "thin credit file" applicants, or those with borderline traditional credit scores.


The User’s SPENDiD Score is a predictive metric indicating the User's ability to meet their Fixed Expense obligations, plus all other peer-modeled expenses based on their Demographic profile, and still "BREAKEVEN" on a cash flow basis during an average month. This is made possible by the User’s Demographic profile, Take-Home Income, and any known Fixed Expense inputs which commonly include categories such as Mortgage/Rent, Vehicle Payments, and Other Monthly Debt Payments, or other legally required payments such as alimony, child support, tax estimates, etc... SPENDiD achieves this scoring metric by comparing the User's provided demographic and major fixed expense information, plus any other personalization made to other spending categories, against proven spending and saving behavioral models of similar peers. SPENDiD converts this scale to a 0-100 range by adding a base fixed amount of 80 to the API-calculated SPENDiD Scores. Developers can use the Predicted Scoring Ability to present scores and metrics in any preferred structure.

SAViNGS Score is calculated in the same manner as the SPENDiD Score with one exception: The User's input amount for targeted periodic savings is included as a Fixed Expense to yield a predictive metric of that User's relative ability to achieve their targeted periodic savings amount.