Jason is working on a few of the complex processes we’ve been wanting to automate for some time now and he’s seeing some positive results.
“[We’re] looking to automate the home loan process - very document driven - trying to condense that, trying to extract data they can send into our decision systems for me to make a decision,” Jason says.
“The really exciting part is in today's world, using the old school techniques [such as neutral networks and gradient boosted models], we can make a decision after all those processes have been conducted within four seconds.”
A faster decision means customers don’t need to find supplementary documentation or spend time waiting for approval. They can get their answer and focus on what’s important: getting into their new home.
But it’s not just the home loan process that’s seen the benefit of new technologies. Our Institutional team has been using machine learning for the past few years and Sreeram says even three years ago the team saw the promise the tool held. Now, they’re seeing results.
“I'm excited because it is really good for our staff. You know, there's so much value added from an individual point of view because banking can be notoriously paper intensive,” he says.
“This is a combination of technologies and capabilities. The machine now…the transfer of paper to image, the quality and accuracy of imaging, the ability to read, the ability to interpret and then the ability to process; this is coming together for the first time, at least in my career.
“We have seen cases where 50 per cent of the manual effort before has been. We have seen cases where our internal times have improved roughly 40 to 50 per cent. So I think it's absolutely made things better.”
Although Sreeram reminds us that “comes with its challenges and caution and management of governance, as with any technology.”