Bridging
Embracing automated intelligence: Why the bridging sector can no longer bury its head in the sand – Smith
While many organisations are eager to adopt and integrate it into their daily operations, I prefer to look at it through a slightly different lens. I refer to it as ‘automated intelligence’.
Despite the enthusiasm in some quarters, a number of businesses are actively pushing this technology away. Some feel threatened by it, and others are deeply worried about its competency and consistency. There is also a very real, understandable anxiety regarding the damage it might do to the shape of employment, and how the workplace will be staffed in the years to come. But here is the reality we all must face: we cannot ignore it.
And at Black & White Bridging, ignore it we won’t. Embracing automated intelligence, however, does not mean plugging in an algorithm and hoping for the best. The most successful technology projects, regardless of the surrounding hype, always start with the fundamentals. Before a business can truly leverage AI, it must first have a comprehensive understanding of its data, its permissions, and its governance position. Without that bedrock, any AI initiative is built on sand. In the bridging sector specifically, we have to be realistic, as bridging is a highly nuanced, relationship-driven, and complex business.
Every deal has a story, and because of this, it will be very difficult for AI to play a vast, autonomous role, but what it can and will be is a tool that provides powerful, helpful assistance to our business.
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If we can use automated intelligence to help our humans do what humans do best, everybody wins. Our aim has to be leveraging AI to establish rigorous oversight on lending decisions, allowing our experts to make those decisions quickly and accurately.
A perfect example of this is the impact AI is already having on audit and compliance. As highlighted in a recent article in Mortgage Solutions by Dawid Kotur of Curvestone AI, the value AI can bring in providing immediate, comprehensive oversight is going to be invaluable.
Historically, compliance has relied on a ‘risk-based approach’ of spot-checking perhaps 10% of case files, simply because manually reviewing 100% of cases was financially and operationally impossible. But the maths of compliance is changing, and AI can now step in to do the heavy lifting, discovering context, identifying vulnerability flags, and connecting information across thousands of pages of data in seconds.
Crucially, as the article points out, this isn’t about letting a ‘black box’ algorithm make sweeping subjective judgements. It’s about transparency and efficiency, as the machine does the reading and the surfacing, moving the compliance team away from a ‘needle in a haystack’ search. This frees up the accountable human auditor to focus entirely on judging whether the outcome was actually right for the client. It is the perfect symbiosis of automated speed and human judgement.
We cannot afford to reject these tools simply because they challenge the status quo. We must be nimble. This is an elephant in the room, and a very big elephant, so we must address it head-on so we are not left out in the cold.
By taking a thoughtful approach to data and governance, and by using automated intelligence as an enabler rather than a replacement, we can elevate our service, tighten our oversight, and ensure we continue to deliver the speed and certainty our brokers and borrowers rely on.