Ensuring that decisions are made promptly, with accuracy and precision, is paramount to the future success of the mortgage industry.
One only has to look at the recent 'de-banking' fallout in political circles to see the reputational risks associated with decision-making that is not watertight.
It’s in this context that artificial intelligence can play a key role in ensuring the mortgage industry remains vigilant in its own fight against biases, while streamlining processes so that they are fairer, more efficient and, above all, transparent.
Traditional mortgage approval processes, despite the guardrails already in place, can still be riddled with subjectivities that are not conducive to better outcomes for either the applicant or the lender.
Irrespective of experience, these can seep into assessments and human underwritings that result in unfair rejections or approvals for mortgage applicants, and even wrong rates being offered.
Humans are, consciously or not, inherently prone to biases that can lead to concerning outcomes. AI, on the other hand, can be highly effective in combatting these biases while reducing lending risk.
First, AI makes standardised decisions solely based on preset internal rules, algorithms and datasets rather than personal prejudice, political views, or emotions.
This enables AI-driven know-your-customer (KYC) and know-your-business (KYB) processes to analyse thousands of data points and assess risks without fear or favour, ensuring applications are evaluated on their merits alone.
Some platforms also ensure that all decisions made use the same criteria and rules for every company or individual through pre-populated templates, leading to greater consistency and fairness not just within but across industries too.
AI also has the advantage of continually evolving and learning as it gets fed new data, ensuring it becomes increasingly accurate through training.
This becomes highly advantageous, given its ability to process vast amounts of quality data sources instantaneously, something that may take a human several days or more and precipitate fatigue and flawed decisions in itself.
Greater efficiency and fairness as a result of this means faster approvals, quicker responses to customers, and overall a more streamlined lending process, which can provide lenders with a competitive edge.
Reassuring customers that the decisions made on their applications are demonstrably not hinged on gut feelings and intuitions is a powerful tool in any business’ arsenal.
Furthermore, for advisers and brokers, adopting AI means streamlined operations and reduced workload, with less time spent on manual paperwork and data processing, enabling more time to focus on providing better customer service.
Increased AI-driven decision-making must also be balanced with vigilance for privacy concerns and potential algorithmic bias.
There may be times when, even though the algorithm itself is unbiased, the use of biased or historically flawed data can lead to algorithmic bias regardless.
