Making First Time Right Applications a Reality in Mortgage Lending

Loan Approved in Minutes!

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These are the typical ads that give loan borrowers the hope of getting loans in short periods, which eventually lead to utter disappointment due to the lengthy lending applications and underwriting process.

Standing by your word and sanctioning loans on time is the only way to increase business revenue & reputation and gain more market share. That means assisting customers to be First Time Right with the application submission, i.e., the presence of an intelligent loan application health report prior to submission.

Using AI won’t cut it.

Artificial intelligence is the cornerstone of increasing lending efficacy. Mortgage lending is a vast and diverse industry, requiring a variety of tools at various stages of the application. You need a platform that harnesses the power of top-notch AI technologies in the market and is easy to implement in your existing business infrastructure.

Digilytics RevEl: The perfect combination of AI tools for mortgage lending.

Our product harnesses proprietary techniques in various emerging sub-fields of AI, offering a high-value platform to transform your mortgage lending business.

Let’s take a look at various components and how they can help your business

Intelligent capture: Reads documents like a human, with a machine’s accuracy.

  • Computer Vision:

Gone are the days where just an OCR scanner would suffice to process mortgage loan documents. If images speak a thousand words, then mortgage loan-related images or scans can reveal every aspect of a customer’s financials if processed correctly. RevEl brings computer vision into the mix. It uses deep neural networks based on the highly successful convolutional neural network algorithms to understand all types of graphical representations specific to mortgage lending in one go.

  • Machine Learning + NLP:

RevEl also leverages machine learning to contextualise textual data captured by OCR and estimate different elements of affordability like estimating income to assist the underwriter with both structured and unstructured customer evidence (pay slips, bank statements, etc.). Furthermore, it uses Natural Language Processing (Based on Google’s BERT algorithm) to enrich data captured from OCR and make contextual sense of all the words and phrases, to quickly resolve pressing queries.

Now, First Time Right applications mean preparing machine learning models for independent data or untrained data sets. Enter one-shot learning!

One-Shot Learning: Get machine learning evaluation right the first time, every time!

Extensive training of machine learning models impedes adoption. One shot learning innovation will uniquely allow origination to become truly paperless and will drastically reduce transaction cost and time taken for providing credit. This would accelerate an urgent sustainable recovery from the Covid-19 crisis and significantly benefit a sustainable future by reducing waste, slowing climate change, and enhancing access to the essential need of shelter.

  • Cross Validation: Fool proofing First Time Right applications

This is a technique in which machine learning models are trained on sub-sets of available input data and are tested on the complementary subset of the input data. This allows machine learning models to improve accuracy when it comes to understanding independent data.

For e.g., Let’s say a borrower has given a free form letter as salary proof. Document-level cross-validation can compare this with the bank statement acquired and validate the proof given by the borrower.

This innovation will drastically improve on the current state-of-the-art algorithms by achieving 95%+ accuracy in data extraction and validation for mortgage documents.

Deep Learning: Going beyond FICO scores & ordinary parameters for credit risk evaluation.

The mortgage industry is a data-heavy industry, making it naturally suitable for deep learning that relies on layers of neural networks performing complex mathematical functions in various permutations and combinations, mimicking the human brain.

This means a person’s capability of payback can be evaluated based on a vast range of market dynamics, such as digital footprint, the value of loan tied to collaterals, future inflation, and economic growth. Unlike machine learning, deep learning deals with unstructured data and un-trained data-sets, making it perfect for affordability evaluation in today’s time.

This allows you to cater to borrowers with various financial circumstances e.g. Those who lack credit history but have excellent payback capacity, enabling faster business growth.

About Digilytics RevEl

Digilytics™ RevEl for Financial Services is an AI-enabled revenue elevation product built on the Digilytics™ platform. It is available as a SaaS-based solution and can be plugged into any loan origination system (LOS) without the need for replacing existing mortgage systems. For more information about Digilytics RevEl, visit our dedicated website here.

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