LERETA, a provider of tax data to mortgage servicers, has launched advanced Tax Status Reports (TSR) – reports that standardize the delinquent tax research format regardless of the variations between agencies.
Using these reports, mortgage servicers can accelerate the determination of whether real estate tax payments have been made or are owed.
This is the company’s second product launch in the last two months. In February, LERETA rolled out its Total Tax Solutions web-based platform, which is designed to seamlessly integrate loan servicing and tax service data.
As per a company press release, the new TSR reports supply the delinquent status of loans that are not in cycle and may have not been monitored for property taxes. Typically, an employee will conduct time-consuming research to identify a specific tax agency and parcel numbers for accurate tracking in order to eliminate costly delinquency and penalty fees. Now, the company’s reports standardize the format regardless of the agency.
“Existing delinquent tax research methods are limited and overly complicated, creating an environment where mistakes can easily occur and speed to payment is restricted,” says John Walsh, CEO of LERETA, in the release. “Our Tax Status Reports streamline processes and make it easier for lenders and investors to reach secure, qualified decisions. We are breaking new ground and advancing the industry to a new level of excellence with this new method of reporting. These reports allow LERETA to set a higher standard for delinquent tax research.”
Reporting, labeling and collecting delinquent taxes is a complicated process. Having a standard format automatically eliminates manual errors and allows for more accurate tracking of payments and fees. This new approach expands current tax status report combinations from four to 13 possible variations, creating a robust reporting system that is customizable to each customer’s needs and allows for a more thorough risk assessment. Lenders and investors can now better analyze risk and tax payment data while reducing the time needed to make payment decisions.
