Automated document processing (STP)
Our clients make their business processes more efficient via straight through processing (STP). Automated document processing enables STP and leads to strongly improved business processes in terms of speed and accuracy. This is even more true for the loan and mortgage market.
In today’s market, loan and mortgage providers need to maximize first-time-right ratios to remain competitive. Origination is however a vastly paper-dependent process and it can take more than 20 days to process a mortgage loan. The delays are mainly caused by manual analysis of mortgage loan supporting documents.
DocStreet is a secure cloud-based SaaS product that enables organizations to process documents automatically via a set of web services and a web application. DocStreet analyses the document type, extracts the required data and allows for its use in further processes. With DocStreet, the time required for mortgage loan processing is cut from a couple of weeks to several minutes increasing the conversion ratio and cutting down labour expenses. The DocStreet service can be easily utilized to automate document processing also outside the loan and mortgage market.
READ MORE Loan Origination, Servicing and Recovery.
The following groups of processing functions are available in the current version of DocStreet:
- Document Assembly
- Document Analysis
- Collection Maintenance
- Document Editing
- Notification Mechanism
Why docstreet?
- Automated document analysis enables straight through processing and improves first-time-right rates in loan origination
- DocStreet extracts data automatically from unstructured, semi- structured and structured documents (salary slips, IDs, contracts, etc.)
- Document data can be viewed, edited and verified via a web application
- Consistency and validity checks are available via built-in business rules for fraud prevention
- SaaS delivery provides cost, flexibility and scalability benefits
Main features
Straight through processing in loan origination process
An important part of straight through processing in loan and mortgage origination is the use of automated document processing. This requires data to be collected digitally. However, in most cases, data is unstructured coming from images (pdf, tiff, jpg, etc. of scanned documents) and searchable pdfs. DocStreet converts unstructured document data automatically into structured data, and allows for its usage in further business processes.
Delivery & Security
DocStreet is available as a SaaS/cloud solution implemented in AWS (Amazon Web Services). The SaaS/cloud has a security level that is compliant with the security policies of Dutch financial institutions and the legislation. For this, special contracts with AWS have been implemented for data protection. Due to the confidential nature of documents handled by this service, DocStreet offers the highest security levels such as full encryption of documents/data within DocStreet and in storage, whitelisting (IP-address restriction), and secure communication via https.
Easy integration
All functionality of DocStreet is available via well-documented web services and widgets. The web services and widgets can be easily embedded into any web (mid-office) applications.
Risk reduction & fraud detection
DocStreet has integrated intelligence to reduce risk by detecting possible fraud indicators on documents, a hot topic in financial organizations. The built-in document business rules check the consistency and validity of data within a document.
Checks and statuses
The client can indicate in DocStreet which documents are required for any individual dossier. Once that is done, DocStreet keeps track of these documents and sends a notification to the user once the dossier is complete. Besides that, DocStreet can apply business rules to documents, for example to check its validity. DocStreet has a user interface in which processed data of documents can be adjusted and repaired.
Schedule a one-on-one demo
Speak to our consultants about how we can help you reach your goals and schedule a free demo.