The #1 resource for M&A tools
Leverest is a digital platform for private market debt financing, specifically designed to enhance deal + lender matching using an innovative Relevance Score algorithm and proprietary Marketplace, streamline end-to-end process workflows, and empower users with intelligent software tools & features.
The company maintains an extensive network of >400 lenders spanning all relevant segments – ranging from local banks to LBO banks, credit funds and alternative debt providers – to provide corporates, private equity investors, family offices and advisors with solutions addressing a wide spectrum of scenarios. In addition, the platform facilitates collaboration across all participants in the value chain through integrating 3rd party advisors.
Deal Set-up, Matching & Selection: Leverest assists in data preparation and employs tech-driven data cleansing. Long List creation per one-click lender invitation and usage of data-driven methods and proprietary algorithms to match borrower and lender based on financing criteria, ensuring relevant lending options for companies and investors.
Full Control of Information: Enhanced data management through Leverests Deal Cockpit reduces the need for numerous emails and excel sheets to track your processes, streamlining information sharing.
Information Provision and Q&A: An in-house developed data room provides real-time access to updated data for all parties, while an efficient Q&A tool prevents duplication and ensures prompt responses.
Termgrids and Negotiations: Leverest simplifies negotiations with instant termgrid comparison and promotes transparency through the feedback option.
Integration of 3rd Parties: The 3rd Party Directory creates the opportunity to obtain customised offers from third parties such as lawyers, loan agencies or speciality advisors in the shortest possible time and to give them flawless access to the necessary data and documents via the platform.
Pricing is individually tailored to the product needs of the customer and the collaboration model chosen.