The Future of Computer Vision, Machine Learning and Artificial Intelligence in Mortgage Industry

Human thinking about technology

Lenders tend to spend long hours filling out an application and gathering documents in their mortgage process. There’s a lack of transparency about the status of the process and uncertainty about, what outstanding documents could be requested later.

Most of the lenders still rely on traditional paper-based manual process. But, with the world evolving rapidly and massive digitization in the mortgage industry, most of the mortgages are missing out the opportunity to capitalize on this change and adapt accordingly.

Lenders are struggling to ingest and capture relevant data due to high complexity and lack of tools to automate the processes.

Here’s when cutting edge technologies like computer vision and trained proprietary machine learning models for mortgage specific documents come into the picture.

In this blog, we will discuss how computer vision, can be used in innovative and differentiated ways to meet industry needs and usage of machine learning models specific to the mortgage industry.

What is computer vision?

Computer vision is an interdisciplinary scientific field that deals with how computers can gain a high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.

How computer vision can help mortgages in innovative, differentiated ways and tuning it to meet the industry needs?

Computer vision uses intelligent data capture that involves a combination of multiple technologies, by creating a content flow and integrating it into the existing business workflow and internal systems.

Intelligent data capture provides document storage capabilities in a secured manner and helps in data ingestion/capturing from various sources, data extraction from multiple languages, and document classification using natural language processing and text analytics.

This intelligent infrastructure connects contents from all channels - using image repository, data capture, information management and AI technologies.

Intelligent data capture technology enables automation of multiple tasks that require human intervention, hence saving time.

Scanning devices and mobile capture technologies have extended the scope: Data can now be captured, streamlined, and managed by advance document handling capabilities from customer’s home or workplace to other remote locations. It has improved the speed of operations and decision-making capabilities of mortgages.

Important metrics to be kept in mind before setting up intelligent data capture:

  • Accuracy: Set up accuracy standards for different types of data and documents you plan to capture
  • Flexibility: Based on business requirements, select intelligent solutions that offer content management and automation
  • Reliability: Should be intelligent to mirror human comprehension and decision-making capabilities through context and error recognition
  • Self-learning Capability: How does the solution perform with new data types or formats
Computer vision in mortgages

Digilytics approach towards computer vision

DigilyticsTM Oculyse is a platform module for processing, managing and generating insights from e-documents; it’s an AI extension to Electronic Document Management Systems (EDMs) – that enhances the business process by adding intelligence and improves process efficiency by providing access to AI-enabled analytics and automation capabilities.

An integrated intelligent data capture tool that can handle different levels of integration, types of data and highly complex processes.

Steps involved for any type of mortgage document, as illustrated below:

  • Document upload
  • Reliability: Should be intelligent to mirror human comprehension and decision-making capabilities through context and error recognition
  • AI-Based Text Recognition
  • ML Based Auto Classification
  • Final Review

Advantages of using a product powered by computer vision

  • Intuitive and Efficient User Experience
  • Can facilitate concurrent document viewing across multiple documents. Eg: Signature comparisons, select & share options directly from cases, drag & drop feature to support page(s) movement across documents & ability to verify documents.

  • Data Validation
  • Checks if the information added is valid and consistent with host systems such as vendor/client names, product details, passport, bank statement & payslips.

  • Configurable Index Classification
  • Easily configurable file storage templates catering to applications across various industries like Banking, Mortgage, Insurance, Legal etc. .

  • Annotation
  • Enabling annotations, user can mark and highlight the pages of a document. Annotated data is further fed for contextual data extraction.

  • AI-based recognition & ML-based classification
  • Artificial Intelligence combined with computer vision technology is utilized to recognize text on individual pages, to identify the content. Machine Learning technology is used to auto classify pages into relevant documents as per a pre-defined file order.

  • Centralized Repository
  • Allows complete control, audit compliance & provides a single source of truth for all documents produced or received across the organisation. Document versioning & duplication can be managed easily across the module.

  • Smart Checklist
  • Automated checklists and workflows to assist users for mandatory checks.

  • Configurable Role-Based Access
  • Provides an additional layer of configurability in defining roles and access to documents with proper audit control mechanisms for shared and simultaneous access to sensitive data.

  • Data Extraction & Indexing
  • Seamless, quick data extraction and auto-population from documents, emails, and other sources. Eg: When an “Account Number” field is added, it, auto-fills other relevant fields – such as payment details, address etc.

  • Integration with transactional systems
  • Expands the possibilities & improves the customer experience by having the ability to seamlessly integrate with not only document mailing and archiving solutions but also with transactional systems.

  • Document Comparison
  • Simultaneous view and comparison of multiple documents and duplicate versions of the same document to look for any ambiguity or anomaly in the data.

Machine learning in mortgages

How Digilytics built and trained proprietary machine learning models for mortgage specific documents?

How DigilyticsTM RevEl for financial services dramatically reshapes the mortgage lending process, leveraging Documents such as mortgage illustration, application declaration, payslips, bank statements and affordability assessment form are a rich source of valuable information, that can be leveraged to gain meaningful insights.

AI for document processing is a powerful tool for streamlining workflows, minimising delays, and reducing errors caused by manual document classification.

AI in mortgages

Methodology

RevEl for financial services leverages DigilyticsTM Oculyse and recommendation engine modules to automatically classify documents based on structural features (layout-based document classification), textual features (content-based document classification), or both.  

It enables users to automatically classify various mortgage specific documents such as payslips, bank statements, legal documents, valuation documents, affordability assessments, correspondences, and others.  

It ensures information is available for intelligent decision-making, eliminating risk and cost associated in manual document management by improving the time to offer and time to fund significantly. 

Machine learning algorithms provide high levels of accuracy and reliability by handling messy inputs. Different types of algorithms are used to classify documents.  

TF-IDF, which stands for term frequency-inverse document frequency, a scoring measure is widely used in information retrieval (IR) or summarization. 

TF-IDF reflects the relevance of the term in each document. The logic behind this instant is, if a word occurs multiple times in a document, the model should boost its relevance than other words.

Features of built and trained proprietary machine learning models for mortgage specific documents

  • Model Deployment
  • GUI-based interface to deploy models using REST APIs and simultaneously maintain metadata on deployed models.

  • Model Management
  • Manage model versions across multiple deployments to ensure transparency and easy administration of multiple models.

  • Model Performance
  • Monitor model performance of deployed models & get automated notifications for recalibration of models when model performance goes below a defined threshold.

  • Xplainability
  • Ability for users to monitor explainability of decisions taken by the model to understand the rationale behind why the model is taking a specific decision.

  • Embedded into Workspaces
  • Easily integrated with transactional systems & commonly used systems (CRM and Payment systems).

  • Role-based Access
  • Advanced role-based access for model management.

Concluding with food for thought

Automating all aspects of the mortgage lifecycle is still a challenge. Most lenders will be hopping on the train and integrating AI and machine learning into their systems at some point.

We’ve built DigilyticsTM RevEl with the latest AI technology which will help you save time and money by revolutionizing your origination process.

“NOT I – NOT ANYONE else, can travel that road for you, You must travel it for yourself.” – Walt Whitman 

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Author: Nalin Suri, Product Manager at Digilytics AI | Ishanee Bajpai, Marketing at Digilytics AI

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Posted Under: Artificial Intelligence, Machine Learning, Computer Vision

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