AI in the broker space

Artificial intelligence has been rapidly embraced by businesses, with major broking groups such as Lendi Group already testing new AI-powered tools and tech for its brokers. We catch up with co-founders David Hyman and Sebastian Watkins to find out why and how Lendi Group is harnessing AI to make broking more efficient.

Q. AI seems ubiquitous nowadays, with tools like ChatGPT and Microsoft Copilot becoming mainstream. But what are we seeing when it comes to AI in mortgages?

David Hyman: Robotic process automation, or RPA, has been around for some time, but when we’re talking about AI now, we’re really talking about generative AI, or large language models, which are fundamentally much more powerful.

When it comes to mortgages, AI is in its very early days. But there’s a huge opportunity for it in this space. In the mortgage broking process, AI fits in as a copilot framework that helps brokers be better at what they do; fundamentally helping customers achieve their dreams and goals.

As an example, you can take a technology like optical character recognition (OCR), which has been around for some time to read data from payslips, for example, and use AI to accelerate its use. It can see the variability around the name field, for example, and bring a level of consolidation and consistency to that. In mortgages, that’s where we’re seeing a lot of the acceleration, but we’re just at the beginning of the journey.

Q. What other opportunities can AI bring to the mortgage market?

Sebastian Watkins: This technology should serve three masters: the broker, the customer, and the lender. But across all three, the impact will be around efficiency and an improvement in data quality.

For brokers, AI can give them the ability to process all of the inputs of the client fact-find and the customers’ wants and needs, in real time, and produce a recommendation that has ingested hundreds of thousands of inputs. AI could run this data across all of the credit policies of our lenders and assist the broker in making recommendations to their clients. That is one area where we would see a greater increase in broker efficiency, as it would reduce the manual time required to go and do that work. The increase in application quality would also boost the probability of achieving unconditional approval at lodgement.

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It can also increase our awareness and visibility on potentially fraudulent activity or things that we want to take a closer look at. In doing so, it’s not only increasing efficiencies, it’s also protecting brokers from fraud.

Q. There are some concerns AI may make brokers redundant. Do you think that is the case?

Sebastian Watkins: I think people have been scared that the technology may replace what we do, but I think it will just replace parts of what we do; it will replace the administrative components of what we’re doing. For example, AI can replace the need to do multiple servicing calculator checks, or the job of extracting information from a payslip to fill out forms or rekey information into broker software, or putting together the summary proposal for a customer.

But what it won’t replace is the relationship that we have with the customers. That’s how we see the technology being used in the broker space; it’s not about replacing the human experience, it’s about turbocharging the experience.

Q. Have any other countries adopted AI successfully in the mortgage broking process already?

Sebastian Watkins: We’ve seen that in other countries, particularly the US, companies are using AI technology to increase their efficiency through the automation of administrative work. But even when you look at companies that are doing this particularly well, you still see the majority of their home loan applications and settlements coming through their human channels. They’re just using the technology to make that experience for their customers a better experience and to create more efficiencies for their brokers and bankers.

We’re also seeing a really interesting application of the technology where client conversations are being recorded and the data from that conversation – for example, the assets and liabilities, the income, and the expenses – is being extracted in real time and being populated into a lender’s CRM or platform. So rather than needing to fill out forms, the information is appearing in real time in the CRM as the customer speaks. Then it matches those inputs against things like credit policy and verifies it against the customer documents, surfacing any mismatches that need human intervention.

This is just the beginning of thinking about how generative AI can not only make the data extraction process faster but also become that copilot for the broker, which helps them actually be a better broker.

Q. Do you think AI will help or hinder broker market share?

David Hyman: We’re clearly biased on this one! But we’ve already seen broker market share rapidly accelerate ahead of 70 per cent. If that’s because consumers want choice, then AI is only going to make the broker experience better than it was yesterday … and the broker experience of yesterday was already driving massive growth!

So, whether it’s 75 or 80 per cent or more, broker market share will continue to increase as the relevance of a broker only continues to become more important. And AI is going to be a big driver behind that.

Q. How is Lendi Group using AI?

David Hyman: Our Platform already does a lot of the heavy lifting around policy, serviceability, and questions and documents, but we’re currently piloting an additional experience that uses AI for credit policy. It is almost like a ChatGPT-style interface for credit policy. We call it Leeni.

Leeni can help the broker make smarter suggestions. For example, if the broker is wondering which lender is going to lend to a 37-square-metre apartment in a Category 3 postcode, Leeni can identify that and serve up a suggestion.

We’re also releasing a new experience that listens to broker-client conversations and summarises not just what was talked about but also the commitments that both the broker and customer made around the next steps. It can present that in a template for the broker to send to the customer immediately after the call finishes.

These are just two examples of where we’re using sort of a product-led approach to technology to drive a better customer and broker experience. And there are many, many more in the pipeline.

Tune in to hear more!

You can find out more about the Lendi Group’s use of AI and technology to accelerate the broker offering in the Mortgage Business Spotlight podcast, here:

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Lendi Group is one of Australia’s fastest growing fintechs, building market leading technology to transform the home...

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