The mortgage market in the UK is standing on the edge of a transformation. In the second quarter of 2021, gross mortgage advances were at a record high of £89 billion and are projected to increase to £238 Billion. Despite this, net lending is low.
This is due to a host of issues that the industry has faced for a long time. One of them is that mortgage loan origination is time and labor-intensive. IMLA reports that the pandemic has only accentuated these issues due to operational and consumer circumstances change.
In the dynamic climate that the world found itself in during the pandemic, the process used to determine whether a person could afford services or products, both at the time of application and through engagement, needed to be robust.
With stricter regulations from the FCA, affordability assessments have emerged as one of the topmost priorities for lenders. Not resolving these hurdles could deal a deafening blow to the affordability gap for cash-strapped homeowners who could be left without access to financing.
Enter Artificial Intelligence! It has been a buzzword in the mortgage industry, and for good reason. From enhancing the precision of risk assessments to optimizing customer service operations and reducing cycle times and costs, AI has revolutionized mortgage origination and improved loan efficiency.
This article highlights the challenges in affordability assessments and how AI-driven affordability services, such as RevEL, are changing the game.
Affordability is one of the key foundations of mortgage underwriting. It offers a 360-degree view of the financial health of the person seeking to borrow. If done correctly, it can provide the lending organization complete trust in a borrower's capacity to repay the mortgage loan.
Despite understanding the importance of these checks, many lending organizations are yet to make affordability assessments a standard practice.
Affordability assessment is one of the more nuanced, time-consuming, and rigorous aspects of the mortgage origination process, most often leading to loan rejections.
Over one-fourth of all applications were rejected in 2013, and the rejection rates had slightly reduced to 17% in 2018. But there is much room for improvement.
Lenders notice the following key challenges in performing an affordability assessment:
According to research, just under 19 percent of lenders regard themselves as being exceptionally effective at detecting warning indications that a customer is on the verge of financial trouble. This points to a need for change.
The need for increased AI intervention in mortgage loan origination has never been clearer, particularly for Affordability Assessments - to service the increasing volume of mortgages while ensuring due diligence.
This is where Intelligent Affordability Services change the game.
Intelligent Affordability Services categorize transactions and automate decisions by using predictive analysis. It delivers accurate, reliable, and scalable income and expense support.
Intelligent products like RevEL help with building scalable affordability models based on accurate data to make better decisions.
With the help of real-time and reliable data sources, Predictive analysis can bring new insights in affordability assessments with the use of multiple indicators.
The predictive analysis incorporates predictive modelling, AI, machine learning, and data mining to make predictions.
These new data sources can enhance the opportunity for businesses to gain an understanding of the applicant's financial situation and make intelligent decisions that are scalable, quick, and robust and helping them be prepared for whatever challenges the future economic environment will bring.
Lenders always look into alternate sources of information that can assist them to make better decisions. Such sources might include utility payment information and even industry-specific data.
However, mortgage loan origination systems that employ AI and Predictive Analysis can speed up these procedures thanks to large processing capacities.
Intelligent Affordability Assessment solutions can handle both organized and unstructured data, as well as pictures. Evidence shows that AI-based predictive models are far superior at predicting losses and creditworthiness utilizing non-traditional data sources.
Furthermore, property valuation and risk are of immense importance in the process of underwriting. Modern-day methods of valuation of property assess real-time third-party data alongside conventional metrics of property valuation to provide a complete view of the property’s value. This is done using technology such as automated valuation models (AVMs) and location intelligence.
Having a rich pool of data sources will aid in accurately analyzing I&E data and performing robust and accurate analytics. This might lead to more people being approved for credit and a lower bad-credit rate for the lender.
Predictive analytics can better understand which customers represent a default risk and which may be in the market for additional mortgage services.
AI in the mortgage industry can extract data from a range of sources by document recognition technology and classify them according to the type.
It can further compare the culled-out data against mortgage requirements and regulations to provide insights to the lender and cut down on additional time for contacting the customer.
Mortgage Loan Origination AI Software such as Digilytics RevEL seeks to address both parties' issues during the lending and borrowing process.
The collaboration between manual effort and AI helps improve the experience for brokers and clients. RevEL provides for lowered costs of origination and reduced time to fund.
1. One-shot Learning
The one-shot learning AI technology in RevEL uses a deep learning algorithm to extract data with minimal training sessions. The AI validates applications by ensuring accuracy, completeness, and consistency for first-time applicants. The AI is equipped to analyze over a hundred types of mortgage documents in the UK.
2. Data Extraction
The Digilytics Oculyse is an AI extension that can read and process the data from documents quickly and accurately. It is also capable of classifying the documents into different categories to help with organization. The AI then generates insights based on the E-documents.
3. Bolt-On Product
RevEL is a modular, easy-to-implement AI product that can be bolted onto the user’s existing Loan Origination System. The value of this addition can be realized within weeks as the microservice architecture enhances the borrowing experience.
The RevEL AI can be integrated for online and offline loan originations. It is also pre-integrated with a range of third-party Origination providers such as Open Banking (Accountscore). The scope of integration is set to include Rightmove, HooYu, HMRC, and Codat eventually.
The AI uses a hybrid model that combines deep neural networks with rule-based approaches to achieve accuracy rates of over 95%. The extracted data is compared with other documents to verify the information and validate it. This results in first time-right applications.
6. Income and Expense Verification
Lenders can use the predictive models offered by RevEL to predict what data will be required for income and expense verification at the time of application submission. The AI also automatically requests the relevant information to complete the verification process.
AI Mortgage origination channels the potential of technology to revolutionize the area of affordability and create better experiences for both lenders and customers.
By leveraging the power of AI, Data, and Predictive Analysis, Intelligent Affordability Services like RevEL by Digilytics allow Lending organizations to combine data sources, bring forth new ways of understanding, and use it to reduce financing risks substantially.
Engage Digilytics services in your lending organization to automate lending and deliver a seamless mortgage origination, increase productivity and reduce operations!
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