Banking on AI – the technology mortgage brokers need to know

The benefits and risks of artificial intelligence for brokers

Banking on AI – the technology mortgage brokers need to know


By Ryan Johnson

New technologies like generative artificial intelligence could revolutionise the mortgage industry – for better or worse, according to an international fintech provider.

“AI is changing the face of the workplace and companies need to begin adapting now to find the balance between their human workforce and the many possibilities of AI,” said Nick Aronson (pictured above), VP APAC country management at FIS, which helps financial institutions develop streamlined solutions.

“Brokers should find ways to incorporate AI tools into their work through investing in this technology or identifying a strong technology partner.”

What’s happened in the AI space so far?

As the most publicly visible form of artificial intelligence, chatbots have been revolutionising the way the world understands and interacts with generative AI.

From OpenAI’s ChatGPT to the newcomers of Microsoft’s Azure AI and Google’s Bard AI, the power of generative AI and its impact on the workplace has become undeniable.

Outside of public chatbots, Aronson said AI had already played a significant role in boosting automation in the mortgage lending process.

“Machine-learning AI tools are extremely effective in extracting relevant detailed data and analytics from a credit application for digital processing. They can also make relatively simple lending decisions,” Aronson said.

“Generative AI has developed rapidly in a short period of time. It’s not just about direct customer service – it can dig deep into data and create accompanying textual or visual content, rather than just replicating manual processes and human decisions.”

However, Aronson said this also had the potential to make generative AI “a dangerous way to cheat the system”.

Concerns about AI in the mortgage industry

While generative AI has the power to revolutionise financial services like mortgage lending, it’s also making many industries nervous.  

New research claims that 75% of organisations worldwide are planning to ban ChatGPT and other generative AI tools due to privacy, cybersecurity breaches, data security and job loss fears.

With generative AI being able to expand past automated, repetitive and mindless tasks, Aronson said this worry was valid – not just for data roles but also jobs across creative and cognitive areas.

Yet there is much upside to the uptake of digital technology.

With the property market generally going from strength to strength in recent years, significant technological investments within the residential space have digitalised many of the processes.

From CRM systems and online applications to digital marketing tools, technology has transformed the residential market, especially when compared to the commercial space, and has driven broker market share from 40% to nearly 70% within the decade.

And while this shift has brought with it extra risks such as the rise of cybercrime, the benefits largely outweigh the risks.

“The right technology aids brokers in their ability to quickly adapt to the ever-evolving mortgage landscape and manage this increasing workload,” Aronson said.

“As interest rates continues to rise and people tighten their purse strings, it is essential for brokers to forecast how the market will change over time and emphasise the level of risks involved in presenting certain loan packages to clients.”

Aronson said some ways generative AI could assist brokers included:

  • Commenting on credit applications – giving customers constructive and detailed feedback on the reasons for lending decisions
  • Financial analysis and forecasting – using complex sensitivity analysis to predict what could happen to customers or markets in the future and managing risk accordingly. As such, brokers can customise mortgage loans for each customer accounting for rising interest rates and other market changes.
  • Credit assessment – determining the creditworthiness of a client without a credit history.
  • Assisted credit memos – providing all the background information lenders need for human analysis.
  • Fraud detection – translating unstructured data into meaningful insights and flagging warning signs.

Improving processes in the mortgage industry

Not only could generative AI assist with the specific loan activity, but Aronson said it could also help brokers “dive deeper into their customer base, improve processes, and prepare teams for the future”.

Aronson pointed out the following potential use cases:

  • Know your customer – early identification of problems and taking it to the next level.
  • Service generation – digesting data points about customers to recommend them at the right point in the business cycle.
  • Report generation – personalising accessible reports and dashboards to the needs and sophistication of the client reviewing them.
  • Model and case study training – generating potential real-life scenarios to educate and train the team so they can become leaders in their field.
  • Sentiment analysis – interpreting data from an assortment of mediums, so brokers can use their emotional intelligence to discuss opportunities with a human element.

What about the human touch?

While new artificial intelligence tools such as Chat GPT could streamline processes for mortgage brokers, one thing that it lacks is empathy – a quality that is crucial in becoming a leading broker.

“When the financials are inconclusive, a good gut feeling or understanding of the client can lead to an even more successful deal,” Aronson said. “Ultimately, emotional intelligence in conjunction with the utilisation of AI tools has a major part to play in successful credit assessments and loan management for clients.”

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