"To see real improvement, we need a commitment to a leap in data management as a whole, and to deliver this in real time then AI is essential."
In the 21st century we expect to be able to transact digitally with ease. Customers increasingly want to move faster and have control over their processes, with little patience for cumbersome tasks. However, as we’re all too aware that it can take weeks to receive a legally binding mortgage offer.
While innovation has been selectively done on parts of the customer journey, the mortgage industry as a whole has not been able to innovate. This is partly due to the complexity of the mortgage customer journey and the huge undertaking required to change the process from the ground up. As a result, huge inefficiencies remain. To see real improvement, we need a commitment to a leap in data management as a whole, and to deliver this in real time then AI is essential.
AI Lab success story
Over the last decade, artificial intelligence (AI) research and development has surged. This has been driven by the wider adoption of machine learning techniques in business and a greater willingness to invest. R&D and investment in AI plays a critical role in the innovation process. It’s essentially an investment in technology and future capabilities to transform into new products, processes, and services.
Take for example the recent success of DeepMind, a London-based technology lab who have used AI for protein structure prediction. Through the AI lab, scientists have been able to predict how a protein folds into a unique three-dimensional shape, a problem that has puzzled scientists for half a century.
MQube’s AI Innovation Lab in partnership with MAB aims to explore the practical applications of machine learning technology in the mortgage industry, to remove the pain points that exist in the traditional lending experience. Our mission is to explore the frontiers of technology to help drive industry wide change.
Outdated processes
The mortgage industry is stuck in a time warp, drawn out by paper-based processes in pursuit of a non-definitive decision-in-principle. Decades-old technologies are used with hours wasted on mundane tasks - typing in customer information or repeatedly scanning and uploading documents.
There has never been a more pressing need for streamlined mortgage processes within the covid-era. The headline delays experienced by brokers, customers and lenders in the pandemic has highlighted just how desperately the mortgage system needs to change.
There are dramatic improvements to be made in data management. To have a less duplicated process we have to look at the way data is put into the system. We aim to look at how we can take data at the very earliest stage of the customer cycle and get them to the end of the process as fast and robustly as possible.
The aim of the game
For customers to have better access to mortgages and a better service, brokers need a better system. A system that focuses on their professional advice and that takes away the laborious donkey work that they find themselves doing all too often. This is what artificial intelligence is for.
The Adam Smith Institute recently published a paper that effectively debunks the luddite fallacy. That is, for too long we have been scare mongered into the view that robots are going to steal all of our jobs and that AI will bring the collapse of the economic order. It feels intuitive: if work that used to be completed manually is now automated, there is less need to employ a person. But this analysis is fatally flawed.
It is important to distinguish what humans are good at and what robots are good at. Sorting through large volumes of data, clarifying it and categorising it at speed – robots are good at this. Giving good advice based on complex financial situations and understanding human needs – a job for humans.
Successful adoption of AI means that we stand to gain as a society. As mundane jobs are automated, people can be paid better to do more interesting work. We can use labour resources more efficiently and generate greater economic value.
In the mortgage space, not only does the broker stand to benefit from this, but by removing unnecessary time-consuming processes through AI, lenders have a quicker and more cost-effective route to market.
Automation not digitisation
Understanding the difference between automation and digitisation helps to demonstrate the significant difference between the application of AI at MQube in comparison to the changes implemented by digitised technologies elsewhere in the mortgage space.
Digitisation is simply the process of converting non-digital information into digital data, such as, turning printed communications into email. Digitisation alone is not enough to transform the mortgage industry. The process of applying for a mortgage online and uploading documents to be checked by a broker is an example of how the process is digitized. While this may make it easier for businesses to collect and manage information it still involves manual processes on behalf of the broker that take up a lot of valuable time.
Automation on the other hand, means using machines to take on repetitive processes. Instead of the broker having to take the data off the page, and check it manually, AI can do this process. MQube has developed AI that can read and understand the data on a document, check it, verify it and categorise it. Brokers and underwriters will no longer have to manually check the data on an element-by-element basis, freeing up hundreds of man hours in the process and providing better customer outcomes. This is automation in action.
The future
The ship is sailing on the mortgage industry and those not on it are going to find the future tough. Those who do not invest time and money in automating are going to run the risk of being left behind and finding the world has moved on without them.
We are yet to see the real impact of Artificial intelligence on the mortgage industry but by focusing efforts with MAB within an exploratory lab, we are able to foster real innovation and produce tangible solutions. Full automation via artificial intelligence, rather than just digitisation, is the potential transformational difference between MQube’s platform and the incremental changes that other fintech in the sector have made.
Success in this initiative is a scenario whereby AI creates a mortgage industry that results in a better allocation of everybody’s scarce time and resources, and a more certain mortgage process for customers. Watch this space, with the successful application of AI, we could well be on the verge of a quantum leap in the mortgage industry.
