Child Support Lien Network – Financial Institution Data Match (FIDM) Services

Background: Financial Institute Data Match (FIDM)

The law required States to enter into agreements with financial institutions conducting business within the State for the purpose of conducting a quarterly data match. The data match is intended to identify financial accounts held in banks, credit unions, money market mutual funds, etc., belonging to parents who are delinquent in the payment of their child support obligation. When a match is identified, State CSE programs may issue liens or levies (referred to in the statute as “freeze and seize” procedures) on the accounts of that delinquent obligor to collect the past-due child support.

Multistate Financial Institute Data Match (FIDM)

In the Child Support Performance and Incentive Act of 1998, (P.L. 105-200), Congress made it easier for multistate financial institutions (MSFIs) to match records by allowing OCSE, through the Federal Parent Locator Service, to assist States in conducting data matches with MSFIs. When matches are made, the information is sent to the States within 48 hours for placement of a lien on and seizure of all or part of the accounts identified. States are using their expedited procedures to seize the accounts and thereby force debtor noncustodial parents to meet their child support obligations.

Instate: Financial Institute Data Match (FIDM)

With the introduction of FIDM, CSE agencies must conduct quarterly matches with hundreds of single-State FIs operating within their State. State agencies also must participate in matching at the Federal level with thousands of MSFIs and process tens of thousands of matches resulting in collections through account seizures. State agencies also engage in interstate processing to identify and seize accounts located in another State. In addition, they engage in outreach activities to solicit the cooperation of FIs, perform customer service to address the concerns of delinquent obligors whose access to financial assets have been disrupted, and develop automated systems to routinely process and manage large numbers of cases.

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