In the mortgage industry, the role of technology has expanded beyond simple digitization to sophisticated processing that can streamline operations, reduce human error, and elevate the customer experience. As your lending company's CEO or CTO, the decision to implement document processing software should not be taken lightly. This listicle will guide you through a meticulous process to ensure you choose the right automation tool that aligns with your company's scale, strategy, and compliance needs. Trust us, you'll want to be thorough in your evaluation, especially in a high-stakes field like mortgage. Let's dive into the essential steps to making your next technology move a game-changer for your mortgage operations.
When it comes to finding document processing software, there are a few key factors that truly matter: data extraction capabilities and the concept of straight through processing (STP). STP refers to the percentage of documents that can be processed and extracted without human intervention. The higher the STP, the more accurate the software is likely to be. So, it's crucial to choose a data processing solution that offers high accuracy for your specific use case. But before you rush into it, take a moment to define your use case and consider its scale. By keeping these factors in mind, you'll be well on your way to finding the perfect document processing solution for your business -
Step 1: Define the Scale of the Problem
To begin, you should first determine the extent of the problem. This involves considering the number and type of documents to be processed, the data that needs to be extracted, and the minimum required STP. It is crucial to have a clear understanding of the project's scope before moving on to the next step.
Figuring Out the Volumes
Get a grasp on your current document processing & loan volume. This might include the average number of loans your organization processes per month, the common document types you encounter, and any specific challenges or complexities in your process. Understanding these numbers will help you choose a solution that can handle your current workload and scale with you as your business grows.
Figure out the type of documents to process
Consider the type of documents you need to extract: structured, semi-structured, or unstructured.
For structured documents like W9 Forms, rule/template-based extraction is reliable. The fields to be extracted, such as name, address, and tax ID number, are always in the same location. Setting up a rule-based extraction can accurately and efficiently extract these fields.
However, rule-based extraction is not reliable for semi-structured and unstructured documents. Different document formats require different rules, which need constant updating even for minor changes. Since the documents may come from various sources, their formats can be diverse.
On the other hand, AI/ML-based extraction can handle the variety and complexity of documents from diverse sources. It can adapt to changing structures by fine-tuning or pretraining the model on updated data. This makes it a reliable solution for semi-structured and unstructured documents.
For example, in the case of bank statements, an AI/ML-based extraction can adapt to varying formats and structures. By training the system on a large number of bank statement data, it can accurately extract the necessary information, even if the statement format changes.
Understanding your specific document type will help determine if a custom solution is needed.
Your mortgage business likely deals with varied documentation including loan applications, proof of income, property assessment reports, and more. The right software should be adept at handling the plethora of documents involved in a typical mortgage transaction.
Make a list of data points to be extracted
Data extracted from documents can be divided into three main categories:
- Key-value pair: This type of data consists of two related elements. The key represents a constant attribute of the data set (e.g., account number, Customer's address, Total loan amount), while the value is a variable that belongs to that set (e.g., 180XXX4456, 8 The Green, Suite A, Dover, United States, $12,00,000). A key-value pair can be represented as follows:
- Invoice number = 180XXX4456
- Seller address = 8 The Green, Suite A, Dover, United States
- Total loan amount = $12,00,000
2. Checkbox
Checkbox extraction from documents involves identifying and extracting the status (checked or unchecked) of checkboxes in a document. This process is particularly useful when extracting data from forms that contain checkboxes, such as Tax forms like IRS Form 1065 and 1040 family.
3. Table
A table is a structural representation that organizes data into rows and columns, capturing relationships between elements and attributes. Another type of table is nested tables, commonly found in documents like rent rolls and can be challenging to extract. Additionally, tables can have different layouts depending on the document type. Financial statements, rent rolls, and invoices all have distinct layouts.
Step 2: Automatic Classification of Document Types
If you have various document types that are not organized by folder, the Document AI platform's ability to classify documents to their respective types is a crucial feature.
Step 3: Check for STP Metric of the Solution
Straight Through Processing (STP) should be a key criteria when considering automation tools. Vaultedge takes great pride in offering exceptionally high STP rates, which translates to minimal human intervention and maximum efficiency. Our solution’s accuracy is a critical differentiator, ensuring your STP stays high and your processing times stay low.
Step 4: Decide If You Need a Custom Extraction Solution
Document AI companies offer generic solutions for different document types. For structured documents like W2 forms, W9 forms, 1040, and others, they may have rule-based or AI/ML-based generic solutions. These document types do not require a custom solution.Step 5: Analyze the Cost and ROI of the Project
However, for semi-structured documents such as Bank Statements, Invoices, Financial Statements, Rent rolls, etc., they provide generic AI models. Each document type's model is trained on a large volume of data with varying content and structure. These models can be used directly as they offer high STP (Straight-Through Processing).
You may need a custom solution for the following reasons:
- If the document type is unique and the Document AI company does not have a generic model for it, they will train a model using the (50-100) documents provided by you. They will utilize techniques like Data augmentation to increase training data and transfer learning to leverage a similar generic model for another document type, ensuring STP that meets your requirements.
- If the generic model does not provide the desired STP, the Document AI company will fine-tune it using the (50-100) documents provided by you.
For the mortgage sector, customization of data extraction is often the difference between software that impedes or streamlines your operations. While Vaultedge's existing proprietary models cover a broad range of document types, we offer customized solutions for unique formats, ensuring your data capture aligns perfectly with your business needs.
Step 5 - Analyze the cost and ROI of the project
The cost of the project depends on factors like document volume, data extraction complexity, and automation level. It's important to consider the project's cost in relation to the return on investment (ROI). For instance, automating a time-consuming manual data entry process can save significant time and resources, resulting in a positive ROI. Additionally, automated document processing offers long-term benefits such as increased efficiency, accuracy, and faster processing times, leading to improved customer service, productivity, and decision-making.
When evaluating the project's cost and ROI, businesses should consider initial setup cost, ongoing cost, processing cost per document, and overall benefits. By carefully assessing cost and ROI, businesses can make informed decisions about implementing automated data extraction solutions.
Checklist: Choosing Your Mortgage Document Processing Software
Explore the following list of factors and functionalities to ensure that your document processing software aligns with your business needs
1. Categorical Identification
Your software must accurately identify and categorize all document types associated with mortgage processing, ranging from loan forms to underwriting documents, IRS verifications, Promissory notes, contracts, applications and beyond.
2. Flexibility in Formats
Choose a software that is format-agnostic, capable of processing a wide variety of document structures and types, including both digital and scanned paper documents. This is where Vaultedge's proficiency in handling structured, semi-structured, and unstructured documents can be a significant advantage for your organization.
3. Speed and Accuracy
Speed is of the essence in the mortgage business, but never at the expense of accuracy. Ensure that your chosen software can maintain the highest standards of precision even under stringent time constraints.
4. Adaptive
In a world of evolving regulatory requirements and document formats, select a solution that adapts with minimal AI model retraining. Our models at Vaultedge use a continual learning approach, keeping them abreast of changing patterns and structures.
5. No Need for Third-Party Applications
A robust document processing tool should offer a comprehensive suite of features without reliance on third-party software, ensuring a streamlined and secure data processing pipeline.
6. Security
Mortgage documents contain sensitive and personal information. Prioritize a software that offers best-in-class security features to protect this data at all times.
7. Integrations
Any new software should integrate smoothly with your current technology stack. Vaultedge's Document AI seamlessly integrates with your existing Loan origination system via api.
8. Capture Data Intelligently
Ensure that the software can not only extract data but also provide intelligent insights and analysis to support the decision-making process. Vaultedge's offering goes beyond simple data capture, providing you with actionable insights derived from the high-quality data you feed into it.
Conclusion
Mortgage document processing software offers significant benefits to businesses. It increases efficiency, improves accuracy, and reduces processing times. To implement an effective solution, businesses should define the problem's scale, consider customization needs, and evaluate project costs and ROI. By carefully considering these factors, businesses can choose the right data extraction technique that meets their specific needs and achieves maximum automation benefits.
Looking for new document processing software? Consider Vaultedge! Our future-proof, efficient, and secure system is more than just software - it's a strategic business enabler. Take a proactive step today and connect with us for a personalized consultation. Our Document AI solution can transform your mortgage processing to be robust, reliable, and responsive. Check out our case study on how we helped BSI Financial Services with their loan boarding. Partner with Vaultedge to stay ahead of the game and inspire confidence in your clients for a seamless lending experience.