Today's deduction claims process is labor-intensive, time-consuming, and prone to human error. It requires large staff to deal with extensive inbound claims from customers, contributing more than several days in days sales outstanding (DSO). Not only does it result in cash flow being tied up with customers, but also opens up cash being 'leaked' from invalid claims. Industry research suggests 'cash leakage' could be as high as 5% of total deduction claims.
Problems with today's deduction claims process
How it works
Accurate Predictive Models
Model is trained with historical transaction data, resulting in high accuracy and low false positives.
Real-time Predictions
Model is promoted for real-time prediction.
Seamless Workflow Integration
Each dispute is scored to determine validity with confidence levels.
Scores are easily integrated with dispute workflow via API.
Actionable Insights
Advanced analytics is provided to support model perfomance and root cause analysis results.
Improves effeciency by 2x, accurately auto-clearing at least 50% of all claims. Prioritize investigation of invalid claims
Eliminates a rule-based approach prone to cash leakage. Accurately detects invalid deduction claims
Accelerates dispute resolution of open invoices and claims. Automates the categorization of reason codes
Smartclaims utilizes machine learning algorithms to automate the deduction claims process. The algorithm finds patterns in customer behaviors from years & months of transaction records that can result in accurately predicting the outcome of any given dispute claim.
Smartclaims is ERP agnostic. Customers can invoke an API call in real-time to get predictive results integrated into existing ERP rules engines and workflow tools.