Driving GOOD In 2023: LOOP's Annual Impact Report

Published on
January 10, 2024

January 10th, 2023

Dear All,

We are pleased to present our 2023 Annual ‘DRIVE GOOD’ report to uphold our value of transparency as we further our mission.

LOOP was founded in 2020 as a B-Corporation with the stated mission of using technology to create more equitable insurance.

We’ve come a long way since our start: introducing  several industry-changing innovations into the world of auto insurance, standing up a vertically-integrated insurance operation, and serving over 10,000 members across the State of Texas.

Perhaps our most meaningful innovation to date has been the elimination of the use of FICO Credit Score in pricing — which disproportionately impacts low-to-moderate income communities across America — and replacing FICO with risk design rooted in more equitable, accurate, and dynamic data sources.

We measure the progress of our intended mission’s impact in  the following measures:

  • Gross Written Premium
  • Members Served
  • Cumulative Premium Saved by Eliminating Credit Scores
  • Number of Members Living in Overpriced Zip Codes

Member Growth

In 2023, LOOP wrote a cumulative total of $26.3M in Direct Written Premium and served over 12,000 members. Collectively in 2023, LOOP members logged over 10 million miles of driving.

Annual Savings from Predatory Practices

It is the auto-insurance industry standard to use credit score to incentivize higher credit drivers and those with more insurable assets with greater discounts.

By removing credit, LOOP has saved members $30,865,926, or $1,360 on average each year, since LOOP began selling auto insurance. Although credit does not predict crash risk as readily as a DUI conviction might, the cost of having low credit is so costly that it outweighs surcharges for a DUI conviction by 1.8x.

In addition to removing credit-based rating, LOOP has developed novel and unique insights that allows LOOP to identify areas where potential members are paying more than they should. Using machine learning-based methodologies, LOOP more accurately approximates the risk of a car crash in these neighborhoods and rates based on factors including population-level crash data from over 4M crashes in Texas, traffic volume, roadway infrastructure, and weather conditions.

According to LOOP’s analysis, 8,450 Members lived in over-priced zip codes, and benefited from LOOP’s more equitable, accurate, and dynamic methodology since LOOP began selling auto insurance.

Conclusions

In summary, LOOP is generating meaningful savings for LOOP members, by shielding them from predatory practices including redlining and the use of credit-score in auto insurance. LOOP is growing in membership and written premium, and so the impact in terms of volume of the financial benefit to LOOP members is also increasing overall. Based on this prepared analysis, the Board of Directors has concluded that LOOP is achieving its stated mission as a Public-Benefit Corporation to improve equity and fairness in insurance with the use of technologies.

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