Orgs using NPSP Enhanced Recurring Donations (RD2) run a nightly batch job (npsp__RD2_OpportunityEvaluation_BATCH) that evaluates Lapsed Recurring Donations for Status Automation. When any Lapsed Recurring Donation has a Schedule End Date earlier than its Effective Date, the batch job's date math fails and throws:
"Batch Apex error — First error: List index out of bounds: 0" Context: npsp__RD2_OpportunityEvaluation_BATCH
This error is generated by bad data — specifically, Recurring Donation records where:
npsp__EndDate__c (Schedule End Date) < npsp__StartDate__c (Effective Date)This pattern is commonly introduced by third-party fundraising integrations (such as Fundraise Up) that create Recurring Donations without validating the date order. Each new record with inverted dates will trigger the error on the following nightly run.
NPSP is working as designed — it is correctly raising on malformed input data.
Immediate fix (stop the nightly error emails):
Long-term fix (prevent recurrence):
If the records were created by a third-party integration, escalate to the integration vendor to add date validation — specifically, the integration should never set npsp__EndDate__c to a date earlier than npsp__StartDate__c when creating Recurring Donation records.
005387169

We use three kinds of cookies on our websites: required, functional, and advertising. You can choose whether functional and advertising cookies apply. Click on the different cookie categories to find out more about each category and to change the default settings.
Privacy Statement
Required cookies are necessary for basic website functionality. Some examples include: session cookies needed to transmit the website, authentication cookies, and security cookies.
Functional cookies enhance functions, performance, and services on the website. Some examples include: cookies used to analyze site traffic, cookies used for market research, and cookies used to display advertising that is not directed to a particular individual.
Advertising cookies track activity across websites in order to understand a viewer’s interests, and direct them specific marketing. Some examples include: cookies used for remarketing, or interest-based advertising.