The creators of a mortgage broking fintech have integrated artificial intelligence technology into the platform that continuously learns from broker behaviour to deliver leads that improve each day.
Launched late last year, HashChing is a young fintech platform that matches customers to a mortgage broker in their local area for further credit advice.
To continue reading the rest of this article, please log in.
Looking for more benefits? Become a Premium Member.
Create free account to get unlimited news articles and more!
Looking for more benefits? Become a Premium Member.
Speaking to The Adviser recently, HashChing founder and chief information officer Atul Narang explained that his team has integrated into the platform an algorithm that learns from brokers’ behaviour.
According to Mr Narang, the algorithm looks at the length of time that a broker has taken to respond to a lead, in conjunction with the consumer’s feedback and rating whenever the lead is closed.
“If a broker has, let’s say, received 20 five-star ratings and his or her response rate is really good, he or she will automatically come into the top list of brokers,” Mr Narang elaborated.
“Whenever the algorithm is matching a consumer with the broker, it looks at those things and then based on that, it assigns more leads to that broker,” he said.
Mr Narang also told The Adviser that HashChing has future plans to branch into predictive analytics to leverage the large volumes of consumer data that the platform captures.
“What are we going to do with that data? The next step is to learn from it,” Mr Narang said.
“For example, how many people are clicking on the same deal from postcode 2000? What will happen is that when a new user enters their details into the platform, our algorithm will know straight away with geo-targeting that they are from postcode 2000.
“The platform will then instantly display a particular deal to the customer which it knows that other users from their postcode are interested in.”