A leading mortgage company faced persistent inefficiencies in processing inbound mail—each piece of correspondence requiring manual sorting, categorization, and routing to appropriate business units. This led to rising operational costs, frequent delays, and a high risk of human error. The company partnered with Codvo.ai to automate and modernize its mail handling process using NeIO, Codvo’s Gen-AI-powered automation platform.
Despite having a robust loan servicing infrastructure, the client was constrained by legacy processes for managing incoming mail. Specific hurdles included:
- Labor-intensive sorting of thousands of documents each day
- Dependency on manual data entry for classification and processing
- Delayed workflows for time-sensitive functions like loan modification and foreclosure prevention
- Limited scalability to support fluctuating mail volumes
These challenges not only hindered operational agility but also compromised customer service and compliance timelines.
Codvo.ai implemented NeIO’s Intelligent Mail Handling solution—an AI-first, end-to-end automation system designed specifically for high-volume, regulated industries like mortgage servicing.
Key Capabilities Included:
- Automated Ingestion: Centralized intake of scanned mail from various sources, removing the need for human triage.
- AI-Based Classification: Documents were instantly classified using advanced intent recognition—no barcodes or templates required.
- Key Fact Extraction: NeIO extracted crucial information with confidence scoring and source referencing, drastically reducing manual intervention.
- Seamless Workflow Triggering: The solution integrated directly with the client’s existing BPM system (e.g., Aspen Grove) to auto-initiate business processes in real time.
The tech stack includes:
- NeIO Gen-AI Platform
- Machine Learning Models for Document Classification and Fact Extraction
- Natural Language Processing (NLP) for Mail Intent Identification
- Optical Character Recognition (OCR) for Content Recognition
- Confidence Scoring & Metadata Extraction Engine
- Integrated Contextual Knowledge Search
- Workflow Automation via BPM Integration (e.g., Aspen Grove)
- Secure Cloud Deployment with API & Webhook Support
Within weeks of deployment, the mortgage company began seeing measurable outcomes across key performance indicators:
-70% Reduction in Manual Processing Time
-85% Accuracy in Document Classification & Extraction
-50% Cost Savings from Reduced Labor
-Improved SLA Adherence through faster turnaround of customer requests
-Future-Proof Scalability without proportional increases in headcount
