The electronic prefix ‘e’ has seamlessly attached itself to the United Kingdom (UK) mortgage origination industry. E-mortgage makes processes like application, underwriting, and funding time-saving, accurate, and reliable than the traditional mortgage system.
Mortgage products like Digilytics RevEL use artificial intelligence to process and classify documents. It also helps underwriters in making effective decisions based on the borrower’s information.
While Optical Character Recognition (OCR) is widely used to scan documents, the One-Shot Learning (OSL) technique takes documentation to the next level.
Let’s find out how!
Before we get into OCR and OSL processing techniques, it is important to learn the necessity of using these scanning techniques in the first place.
In the traditional loan origination process, the borrower physically submits their application along with all the documents to the lender. The lender or the case handler then manually organises and checks if all the documents are complete with the necessary information.
This step alone can take a long time if the documents or the information is incomplete. Even if all the information is correctly provided by the buyer, manual data processing may lead to many errors.
This is where automated mortgage lending tools come in handy as they can accurately scan the data and check for completeness, correctness, and consistency.
An OCR reader is used to scan and read various numeric and alphanumeric characters from physical documents. This entire process occurs in three steps,
As OCR mainly works on pattern recognition, it faces two major drawbacks.
While the OCR technique is quite efficient with printed text, these two challenges can cause problems in the mortgage origination process, as every character of data is vital. As a result, case handlers resort to double-checks because of the non-reliability of the extracted information.
The OCR software can be trained to detect all the features and data in a document to make it more efficient and robust. However, training the software may be very time-consuming.
Digilytics one-shot learning methods aim at first-time-right applications for mortgage lenders. With OSL algorithms, lenders can accurately process documents and complete more loan contracts effectively in the mortgage lending UK industry.
Accurate Hybrid Model
The ground-breaking innovation by Digilytics combines the power of computer vision, machine learning models, and Natural Language Processing (NLP) algorithms.
Being a hybrid model, OSL makes use of computer vision along with deep neural networks to understand and analyse the document with complete precision. This way, it can read and extract information from text, layouts, and images with accuracy levels up to 95%.
Nowadays almost all the NLP models use general English models as bone's model. We are creating our model, with a special vocabulary and syntax understanding for mortgages.
The model is created and trained with mortgage-related terms and regulations.
Unlike the OCR method that banks on its dataset and excess training for better results, one-shot learning requires minimal training as it can extract information in “one-shot”. This avoids the need for large datasets and also saves time and resources in continuous training.
One-shot learning algorithms can also check for consistency in the documents by comparing data and signatures with ease.
At Digilytics, we have trained our models and fine-tuned them with over 7 billion mortgage-specific tokens and data from reliable customers.
Digilytics model incorporates a unique model called MortBERT in its training processes.
While most NLP algorithms focus on the text alone, at Digilytics we train OSL with State-Of-The-Art (SOTA) models that allows document pre-training and understanding in a single framework.
The model uses BERT (Bidirectional Encoder Representations from Transformers) as its base model. BERT is also a SOTA model that is known for its pre-training capabilities.
1. Pre-trained and Self Learning
The one-shot learning model has already been trained with over 100 documents related to the mortgage origination process. This includes payslips, bank statements, tax returns, and various other forms.
Machine learning mortgage tools and models enable RevEl’s OSL to continuously learn and improve itself while in use.
2. One-stop Destination
RevEl’s one-shot learning capabilities are not solely focused on one particular step of loan origination system. OSL contributes to every aspect of the United Kingdom’s mortgage origination by delivering accurate results at all times.
Through real-time health checks, OSL technology can also check for the completeness, correctness, and consistency of the documents.
3. An Overall Saver
Digilytics OSL model is a saver on all fronts as its abilities help in reducing operational costs and resources by streamlining the mortgage process for both the buyer as well as the lender. Through digitalisation, RevEl also provides quick mortgage loan clearance and funding
Based on the live runs with a few lenders in the United Kingdom, RevEl and its one-shot learning AI tech has proved itself to offer absolute value to your money.
These are the results that were immediately seen by the lenders who used this Digilytics product:
Digilytics RevEl offers an intuitive and user-friendly artificial intelligence dashboard to its users. With One-Shot Learning technology and real-time analytics, document processing and underwriting have never been any simpler.
The OSL model provides better and more accurate results to the lender when compared with its counterpart, the OCR reader. This is due to its mortgage-specific pre-training and self-learning abilities in reading text, layout, and images.
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