The fintech revolution: who now assesses your personal loan application?
Article by Ben Tosi
In an age of rapid technological disruption, Aussie banking practices are constantly changing and there is now a piece of technology that could be responsible for assessing your creditworthiness when you apply for a personal loan.
Personal loan provider, Harmoney, kicked off the new year by teaming up with DataRobot, an automated machine learning platform, in the hopes of improving both the speed and accuracy of its application process.
“With our deployment of DataRobot, we’re now using artificial intelligence to reduce risk for our lenders,” Brad Hagstrom, joint-CEO of Harmoney told CIO.
The new partnership means that the peer-to-peer provider now boasts turnaround times - from application to funding - of under 24 hours.
“Our marketplace, which has more than 15,000 members and has facilitated more than $700 million in loans, will now feature the same credit risk assessment capabilities used by the best banks in the world,” said Hagstrom.
What is machine learning?
You’ve probably heard of it, even if you’re not entirely sure of what it is, and that’s because the term ‘machine learning’ was first coined back in the 1950’s.
Falling under the broader term of artificial intelligence (AI), machine learning is a form of technology that gives computers access to data and the ability to learn without necessarily being programmed to.
While this kind of technology is already being used across a range of industries, Deloitte’s recently released Technology, Media and Telecommunications Predictions report for 2018 predicted that machine learning practices would continue to intensify across a range of businesses.
“The number of implementations and pilot projects using the technology will double compared with 2017, and they will have doubled again by 2020,” it said.
How will it affect my personal loan?
Well, a human may not actually be responsible for approving your personal loan anymore, with Harmoney now using machine learning technology to improve the accuracy of your credit risk assessment upon application.
Essentially, this technology is used as a super accurate and legitimate way to determine whether you’re reliable enough to make the required repayments on your loan - meaning less risk for both investors and borrowers using a peer-to-peer platform.
But more than that, it is incredibly fast too.
“These models have proven to be so accurate in their real-time predictions of credit default that Harmoney has been able to improve profitability for lenders, reduce costs to borrowers, and sharpen the company's competitive position against incumbent lenders in our market,” said Hagstrom.
“With DataRobot, we have decreased the time required to deploy predictive models from 12 to 16 weeks to minutes.”
While not every personal loan provider has taken machine learning on board, Deloitte’s bold predictions mean it is hard to imagine a future where this type of tech isn’t commonplace for financial lenders.
In the meantime however, you can shop around for a great loan with a cheap rate and nifty features using Mozo’s personal loan comparison tables and check out are some of our top tips to getting your personal loan approved, below.
Tips to getting your personal loan approved
- Make sure you can prove you’re ‘creditworthy’: Have information on your current financial situation, make sure you have a stable income and pay off any debts that you can before applying.
- Make your application realistic: Get an idea of how much you can realistically borrow, without landing yourself in hot water, by plugging some numbers in the repayment calculator.
- Show you have a positive credit history: Can you prove you’re on time with your previous credit repayments or other bills? If so, you could be judged as a responsible borrower.
- Show a good savings record: If you’ve never applied for a line of credit before, having a good track record of savings can also be taken into account when deeming your creditworthiness.