"It is key that AI use is carefully designed and implemented to ensure customers are treated fairly and consistently for both service and decisions."
FR: Tell us more about your company and its offering.
Fignum was founded in 2019 and forms part of the Bluestone Group. We are a software development company for loan origination and servicing solutions, catering for multi-asset classes, including mortgage, motor, specialist asset, personal and any type of loan.
At Fignum, we noticed that many users encountered friction with legacy platforms during the lending process, with technology that was unintuitive and difficult to use. Likewise, many new technological offerings can pose similar organisational challenges, with lengthy and expensive project and implementation timeframes.
As a result, we wanted to create a platform that is modern, highly configurable, and easy to integrate with new and existing systems. By doing so, we create wider accessibility to specialist and complex credit markets.
FR: How is technology assisting in providing loans to complex credit customers?
As ongoing cost-of-living pressures have prompted a rise in the number of customers with complex credit, lender technology must adapt to meet evolving consumer needs. In addition, advisers need to be particularly mindful of Consumer Duty compliance, placing a greater regulatory focus on providing (and demonstrating evidence of) good customer outcomes.
In such cases, technological solutions, such as Fignum’s loan origination solution, can allow users to customise workflows, and define additional data requirements dependent on certain criteria or client circumstances. This allows for a faster and more accurate credit score and affordability calculation. At the same time, complex credit customers benefit from receiving quicker and more accurate lending decisions.
The proliferation of open banking has transformed the mortgage process, particularly in complex credit cases. For example, Fignum’s integration with Experian which encompasses the Work Report solution and credit searches, enables lenders to make quicker and more informed decisions, thanks to the availability of customer data almost instantaneously at their fingertips. With greater access to a customer’s financial history, lenders are best positioned to tailor mortgage finance solutions to their specific borrowing needs, which can open doors for unconventional borrowers or those with adverse credit.
FR: How has technology evolved to meet the challenges of the volatile mortgage market?
I think it’s fair to say that fluctuating rates have been one of the defining characteristics of the mortgage market in the past months! The introduction of low-code, event-driven systems like Fignum’s where the entire system is defined through configuration enables a rapid rate of change at a low cost, permitting lenders to respond to market and regulatory changes. This ensures that they can take advantage of beneficial market changes, (e.g. being first to market with a product that fits a new demand) and react quickly to market changes (e.g. implementing product changes, rate changes, or pipeline hedging strategies) in short timescales.
FR: Where do you see the future of mortgage tech? Does AI play a role in that?
Ultimately, balance will be the key to the future of successful mortgage tech, particularly when it comes to the implementation of AI. It would be fantastic to see the industry significantly implement automation throughout the lending and loan servicing process, but these developments should be tempered with well-designed breakouts to human intervention. At Fignum, our goal has always been to provide very high levels of low-code configurability, allowing specialist lenders to reduce costs and increase speed and consistency, whilst still providing a high-quality service that looks after the individual through the human intervention points.
That being said, AI, in its many forms, undoubtedly provides a huge potential for both automation and data interrogation. Some exciting use cases for AI on the horizon include risk rating and fraud detection, which, when coupled with human oversight, can reduce risk for the lender whilst ensuring customers are treated fairly and consistently.
Similarly, we’ve seen the emergence of AI agents, allowing customers to get instantaneous answers to questions without needing to wait for a human. However, no two loan applications are the same, and so this approach should be coupled with a real human agent to handle complex or higher-risk issues. This provides customers with a better, faster experience whilst maintaining the quality of advice through the hybrid approach.
It is key that AI use is carefully designed and implemented to ensure customers are treated fairly and consistently for both service and decisions.
