Algorithms and machine learning

As buzzwords become more ubiquitous, it’s easy to tune out. Disruption, virtual reality, fintech, chatbots, blockchain, robo-somethings, robo-everythings, algorithms, machine learning… the list goes on.

The good news is we’re here to wade through it all for you, serving you up what you need to know when you need to know it, and breaking down in simple human-speak what this means for your business, and what we can adopt on your behalf to help your bottom line.

We do want to talk to you here about algorithms and machine learning, as we’ve been doing some great work behind the scenes in this space, and we have high expectations when it comes to the tangible benefits on offer to you as an AFG broker.

We’re fortunate in that we have a vast repository of data, as do our lenders and our business partners. The more data we have, the richer it becomes, and the easier it is to turn into proprietary algorithms which is where the real value of data lies.

In tech speak algorithms are encoded rules of operation guiding how customers interact with your products or with your services. In human speak, think how Facebook knows who to tag in your photos, think Amazon or Alibaba who know what else you may like to add to your cart, even before you do, think Uber who use algorithms to connect drivers and passengers, or drivers and hungry homebodies.

And what exactly is machine learning? Machine learning essentially means deep learning or pattern recognition — giving computers the ability to learn without being explicitly programmed. It devises algorithms that lend themselves to predictive accuracy and uncovers hidden insights to keep businesses on the front foot, leading to strategies to fuel profitability.

The application of the algorithm and machine learning in the mortgage broking space means figuring out how different finance customers behave and respond, helping us to define ideal products, processes, experiences and messages to help create a tailored customer experience time and time again. What this enables is better customer experience, and helping build better business and better bottom lines.

Machine learning needs data, and a lot of it, and it also needs it sorted cleverly, tagged correctly and categorised perfectly, and that’s just what we’ve been doing. This sort of human recognition at computer scale can be used to drive desired behaviours into sales, predicting propensities to buy and to discharge, forecast loyalty, anticipate risk, and help better segment at customer level and better cross and upsell.

Watch this space as we roll out machine learning across our SMART program, starting with the red alert campaign as we take this powerful campaign to even greater heights when it comes to best predicting customers at risk of discharge.

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