Laura Myers, senior technology lead at Halifax Intermediaries, discusses the biggest buzzword in tech and how it impacts the mortgage industry

Are you worried about the impact of artificial intelligence (AI) on your business?

It’s not just the mortgage market talking about AI. Many industries are grappling with the obvious desire for increased productivity amid predictions of the rise of the machines and widespread job losses.

But is that really on the cards?

AI doesn’t necessarily mean inevitable mass job losses. In fact, for those who embrace AI and take the time to learn more about it, there are as many opportunities as threats.

That’s not to say that AI won’t be truly revolutionary. It will.

What is AI?

Artificial intelligence refers to human-like intelligence from machines, usually computer systems.

It describes the new ways that machines ‘understand’ their own and our environment, learn from it, reason and make plans, and execute them to achieve goals.

AI comprises different types of intelligence, including machine learning, deep learning, data analysis and generative AI, from creating images and content to programming.

Many of us already use it in everyday life, sometimes consciously and sometimes without knowing.

Amazon uses AI to show you products you’re more likely to buy, for example, Netflix to recommend programmes you like and Alexa to interact with you.

Pace of change

AI is developing at astonishing speed, which means some changes to the way we live and work in the very near future.

During the Industrial Revolution, machines scaled hard human labour, mimicking our arms and legs. Now AI mimics human cognitive abilities and it scales human thought.

But it does so at such a fast pace that, instead of 60 years of industrial change, we’re looking at a tech revolution before 2030.

Which means it’s time to get our heads around AI.

How AI works

AI incorporates different technologies, but the ability to quickly process huge amounts of data sits at its core. This includes:

Machine learning: Code and algorithms train the computer to learn from the data sets it is given. The models are very good at classifying information, predicting outcomes and spotting patterns. The more data ingested, the better the computer learns and improves the outcomes.

Deep learning: This is a type of machine learning which uses ‘neural networks’ to mimic the brain, teaching itself how to better detect patterns and improve its performance with multiple layers of algorithms working together. It is able to make sense of complex information, such as speech recognition.

Generative AI: This is used to create original content. Using machine learning and deep learning, generative AI analyses patterns and information from a wide range of sources, for example text, images, music, video and more, to generate new content.

Each of these features are effectively powered by big data, which comprises:

• Structured data in a fixed format, such as an Excel spreadsheet and information stored in a preset format, such as an SQL database
• Unstructured data (which accounts for 80% of all data everywhere), includes everything else, such as videos, music and images.

Although AI has been around since the mid-fifties, until recently, unstructured data couldn’t be easily analysed. That was until new tools like open source code, cloud computing and machine learning frameworks gave us the ability to analyse, store and process all of the unstructured data we didn’t have access to before.

And that put a rocket under AI development.

What does AI mean for mortgages?

AI is already being used in the mortgage market, but there is more to come.

Examples of technology that currently incorporates AI include:

• Anti-fraud software
• Chatbots to answer customer queries
• Staff training
• Risk assessment profiles of clients
• Digital ID verification
• Automation of admin tasks
• Processing large amounts of documents quickly.

The benefits of AI in the mortgage market are clear. It can:

• Boost efficiency by automating tasks, meaning that work that previously took hours can be completed in seconds. This includes spotting fraud by using intelligent data capture to look for inconsistencies and other markers.
• Help lenders and intermediaries analyse market trends, by looking at large sets of data and providing useful insights and predictions.
• Assess risk by analysing the risk profiles of existing borrowers and using algorithms to look at an applicant’s finances, credit score and submission to make a lending decision.
• Improve service. Chatbots use conversational AI to support customers and brokers with straightforward queries, 24/7.
• Act as a virtual assistant, listening to calls and conversations and summarising the meeting in notes. Some tools can even provide a list of compliance points after listening to a client call.
• Detect client vulnerabilities by recognising language and tone of voice, sending a prompt to an adviser to notify them.
• Increase accuracy when scanning documents, for example, using facial recognition or reading applications and payslips to identify specific pieces of data or to spot trends. It eliminates human error.

Of course, all of these things ultimately boost productivity, efficiency and accuracy.

The biggest potential benefit for intermediaries is that AI speeds up and reduces lengthy repetitive and mundane tasks, allowing you to focus on the human element of advising clients.

There’s an inevitable nervousness around using AI when many of us don’t fully understand it and want to avoid unintended harmful outcomes. But that risk won’t be mitigated by sticking our heads in the sand, so learning more is essential.

At Halifax, we’re already embarking on new ways of working with AI and are focused on doing it safely and ensuring that customer and broker data is always secure.

AI is powerful, complicated and changing very quickly. There is trepidation of course, but excitement too, because we recognise the endless possibilities it offers to improve the broker and customer journey.

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