Sandler & Travis Trade Advisory Services, Inc. (STTAS) and Data Mining International, Inc. (DMI) announced that they have entered into a strategic partnership to help governments and other relevant customs and transportation-related entities detect risks to international trade. The partnership unites a seasoned team of customs and information technology experts with proven business procedures and proprietary technology to collaborate on developing risk-management software for customs and excise agencies world-wide. STTAS is a global provider of customs compliance, tariff and trade consulting services. DMI is a privately held software company which designs data mining software applications specialized for trade security, risk management and trade logistics applications.
By combining their respective expertise in designing cutting-edge tools, STTAS and DMI will offer products and services which provide solutions to global risks associated with the cross-border transport of goods, including import and export valuation, money laundering, smuggling, and terrorist-related activities. These solutions will help national governments and related entities better secure their borders, enhance their revenue collection, and manage their national security.
“Customs and excise agencies play an integral role in governments’ efforts to gather and analyze intelligence on illicit transactions and potential terrorist activities,” said Robert Schaffer, President of STTAS. “The partnership between DMI and STTAS demonstrates the commitment of both companies to devise innovative solutions that meet the financial and security needs and challenges facing these agencies across the globe.”
“DMI is excited about leveraging our technologies-which have successfully targeted billions of dollars in trade fraud and money laundering worldwide-through STTAS’ broad international reach and deep knowledge of customs services,” said Marc Epstein, CEO of Data Mining International, Inc.
For more information about ST&R or STTAS, please visit:www.strtrade.com