When one considers the top view of the mortgage industry, it is difficult to comprehend its associated carbon footprint. After all, it primarily involves a few transactions and some amount of paperwork, right?
Dig deeper into the ecosystem, and you will discover the impact of offices, computers, data centres, paper mails, and travel - each of these elements contributing to the overall carbon footprint in one way or another.
While some of these are invariable and bear some amount of environmental costs, others can be curbed in measurable ways. And in light of point #10 in our, Green 2030 resolution, it is imperative that financial institutions take actionable measures towards decarbonisation of the economy.
Against this backdrop, it makes one wonder: could AI prove to be a sustainable alternative to shrink the carbon footprint of the mortgage industry?
Let’s take an in-depth look.
As stated previously, every activity, from advertising to loan repayment, adds to the avalanche of environmental costs in the mortgage industry.
So how does one go about quantifying it?
A report by The Guardian chalked up a carbon footprint of nearly 160g CO2e for every pound spent on financial services (including mortgage lending) in the UK.
At this rate, believe it or not, the mortgage industry generates an average of 800kg of CO2e per year for a principal of £100,000, loaned at 5% interest!
To put this figure in perspective, it is equivalent to a household’s annual electricity consumption!
Furthermore, a study by FREEandCLEAR discovered that documentation, primarily in the mortgage origination process, is the primary culprit behind the ecological tax posed by the industry.
Here is a quick snapshot of the key highlights of the study:
Furthermore, the fact remains that paper costs money to buy, store, print on, and circulate. And if such documents are lost, it costs money to replace them.
The problem gets compounded when the documents have to be returned, because the applications may be inconsistent or incomplete. As a result, the cumulative costs are to be borne by the lender, borrower, and, most importantly, the environment.
Clearly, to adopt an environment-first mindset, the first line of action would be to manage the paperwork menace.
Keeping the above observations in mind, the emergence of digital technologies like Artificial Intelligence in the Mortgage Industry could come as a blessing to address such concerns. AI paves the way for making the loan origination process smarter, error-free, and paperless.
The most obvious application of AI in mortgage origination revolves around submitting the application to the lender. Smart forms can easily and seamlessly replace legacy documents and extract data to eliminate the redundancy of refilling the same information over and over again. As a result, mortgage processing will no longer depend on the fifty or so paper documents and reduce it significantly.
Here are some other notable ways through which Artificial Intelligence and Machine Learning can make mortgage companies more eco-friendly:
As a mortgage expert, you may possess all the know-how of the steps and documentation that goes into seeking loan approval. However, for a layman, the experience can be rather overwhelming.
And for this reason, offering them AI-driven chatbots and a searchable knowledge base powered by an artificial intelligence dashboard can forgo the need for outdated brochures in print. Plus, once you empower your customers, you will notice a significant drop in the “back and forth” of applications.
Document verification and validation requires the inspector to travel to the borrower’s location and physically conduct the verification. Thereafter, the details of the customer are entered into the lending forms.
However, AI systems make use of intelligent document processing (IDP) to parse information from existing digital copies and auto-populate this data.
The information is then mapped against the relevant fields for quicker application submission. Furthermore, it works in tandem with automated systems that validate the documents with almost zero latency.
Service personalisation has become a key differentiator in the financial sector as the “one-size-fits-all” approach no longer appeals to the customers. However, to personalise services, mortgage institutions will have to invest in information retrieval systems that are present online and offline.
In this aspect, cloud-based loan origination systems can leverage online data sourced through multiple channels to grant personalisation. The role of AI here will prove to be critical as it can help acquire and store valuable data against the specifics without adding weight to the database.
At Digilytics, we attempt to nip the problem right in the bud through the implementation of AI in mortgage origination.
Our solution reduces carbon footprint of lenders.
Digilytics offers RevEl, a bolt-on loan origination system that streamlines all stages of the mortgage origination process through the power of AI and ML.
RevEl grants the following tangible results:
And while delivering your sustainability goals, Digilytics can also help you improve the AI-powered Mortgage Lending experience for customers!
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