Faster, Reliable Financial Due Diligence for Automotive Lenders
Get the story behind the numbers. Perform faster and more effective analysis of automobile dealership financial statements through automated review of details behind the data. The Crowe Collateral Analysis for Automotive Lenders solution helps commercial lending institutions streamline financial due diligence for more timely information and accurate identification of credit review adjustments, while uncovering meaningful insights for lenders and borrowers.
The Crowe Collateral Analysis for Automotive Lenders™ Solution
This video discusses how the Crowe Collateral Analysis for Automotive Lenders solution can transform your financial due diligence so you can spend less time accumulating data and more time uncovering valuable insight.
Automate Dealership Financial Due Diligence
The Crowe Collateral Analysis for Automotive Lenders solution automates the financial due diligence process for banks and captive lenders by:
Extracting the underlying accounting records of dealership financial statements
Processing the numbers through modeling functions
Creating reports that identify potential lender adjustments to working capital
With more than 50 years of financial services and retail dealership industry experience, Crowe Horwath LLP has created a solution designed specifically for automotive lenders – one that lets you spend less time accumulating data and more time strengthening your relationships with dealerships.
The Crowe Collateral Analysis for Automotive Lenders solution is one of several credit portfolio management and stress-testing tools offered by Crowe. Our credit analysis tools can integrate loan and credit data from various internal systems and third-party sources, helping you to automate and streamline your credit, capital planning, and stress-testing practices.
Automates the collection of commercial customer financial data, digitally maps the data via user-specified rules, and feeds the information into existing financial analysis, spreading, and risk-scoring systems.
Automates the credit review process, integrating data from multiple sources to provide a comprehensive view of customer information, while helping to improve productivity, compliance, risk management, and portfolio visibility.
An end-to-end stress-testing system that applies machine learning to offer lenders a better, faster way to aggregate data, develop and test models, and create DFAST submission reports.
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