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Tech
Special Report: Mortgage broking will never be the same after Effi, an AI-based machine learning platform, which has revolutionised customer service and business for brokers.
When Mandeep Sodhi, the founder of mortgage comparison website HashChing, came up with Effi a software as a service (Saas) system to streamline the heavy-going paperwork requirements for mortgage brokers it was music to their ears.
“The power of the Effi platform is in its artificial intelligence and machine learning,” said Sodhi, Effi’s chief executive and founder.
For years, mortgage brokers have been weighed down with antiquated systems for communicating with customers and processing their personal information that take up a lot of valuable time.
It is still commonplace for mortgage brokers to contact clients individually by email to request personal details and financial information, and many reminders may be issued before they comply.
This can lead to long waiting times and frustration for customers who want to move into a new house but are held up in processing systems through no fault of their mortgage broker.
More so, if a broker’s email goes into the spam folder of a customer’s email account.
The result of all this is a poor customer experience and unnecessary stress for brokers.
A sub-par digital experience can directly affect business outcomes in the competitive broking market.
For example, a customer may approach a mortgage broker for a home loan and be told to expect an email later that day with some documents to read.
“By the time they arrive, the whole world and the Internet knows the customer is looking for a home loan and the customer is seeing ads from everywhere,” said Sodhi.
“When the broker is in contact again, the customer has already moved on,” he explained.
Sodhi, a finance professional with a background in banking, saw all this first-hand and resolved to do something about it.
As the founder of HashChing, he knows mortgage broking well and also understands the difficulties brokers face in their day-to-day work.
“The kind of thing that I was hearing was they are looking to grow their business, but they did not have a good system to measure their productivity,” said Sodhi.
How much better would it be if customers had access to an internet platform into which they could securely enter their personal details and which managed the process seamlessly without issue.
“After talking to them about their pain points, I would ask a broker ‘what do you do typically in a day?’
“And the surprising answer I got was, ‘I spend one-third of my time looking at the landing pages of websites and marketing’,” Sodhi said.
“I said, ‘Well, you’re a mortgage broker. Why are you looking at marketing?’”
“The brokers were just looking at information on websites they probably should have had to hand anyway.”
It was this eureka moment that led Sodhi to come up with a new mortgage broking platform to serve the profession called Effi, short for efficient.
Effi is an artificial intelligence-driven software as a service (Saas) platform that uses bots to do all of the legwork of issuing requests and reminders, collecting information, and responding to questions.
“It’s so surprising that nothing like this existed for mortgage brokers. When we did a demo of Effi to finance companies they were asking if they could license it,” said Sodhi.
The Effi platform has been running for three months, and is already producing impressive results.
“Loans and mortgage applications are being approved more quickly with the new Effi service.”
It may have taken older systems several days to accumulate required documentation for mortgage applications, whereas for Effi the process can be cut down to hours.
Instead of sending reminders to customers with requests to fill in forms and provide personal details, mortgage brokers can turnover this process to customers themselves with better results.
“When a mortgage broker signs up to Effi they get a broker app and a consumer dashboard which is all white label to them,” he said.
The white label aspect of Effi means individual mortgage brokers can adapt it to their business needs.
After receiving an initial text containing a link to register with the Effi website, customers are guided through the mortgage application process and told which information to supply for the process.
Not only that, Effi has a capacity for predictive learning, in that it adapts to individual customer behaviour.
For example, one customer may respond immediately to a text from his mortgage broker, while another customer may only check his emails each evening.
Effi will tailor its responses appropriately, by sending texts to the second customer in the evening.
The Saas platform uses bots or virtual customer assistants to engage with customers, issuing prompts for information, and responding to questions they have on their mortgage application.
Effi uses its artificial intelligence to pick up on changes in customer responses and, learns to adapt its responses to meet customer expectations, to ensure communication is clear and has a positive tone.
For instance, on one occasion the Effi bot misinterpreted a customer’s answer as an appointment time, but it quickly changed its response through machine learning.
“This one client said, ‘I am with ANZ at 3.49 per cent. Can you beat that?’ and the bot said ‘Yes, I’ll call you at 3:49 pm’,” said Sodhi.
“Now when you say to Effi, ‘I’ve got an interest rate at 3.49 per cent’, the bot says, ‘Can I call you back to see if I can find you a better deal?’,” he said.
“It’s getting trained on a daily basis in real time,” said Sodhi.
“We’ve noticed that engagement levels with customers have gone up,” he stated.
Often times, customers are unaware they are interacting with a bot when they engage with Effi.
“They are excited and say, ‘Well, I didn’t know I was talking to a bot’,” said Sodhi.
Behind Effi is an extensive team of artificial intelligence software engineers that Sodhi can call on.
“Currently, we’ve got 23 engineers working with us, but if we need to go to 50, we can. I can always reach out to them and they can help us scale up and build new things,” he said.
A next step for Sodhi is to integrate Effi with bank finance portals that aggregate many different mortgage loans to save even more time for brokers.
“The challenge we are overcoming now is how do we integrate both systems so that any information is updated in Effi and the aggregator system,” he said.
“We are already working with one aggregator on this,” he said.
“Brokers are currently writing 57 per cent of home loans, and we believe they should be writing 70 per cent,” said Sodhi.
Effi can hand brokers an advantage by providing them with feedback and critical data to help them improve their customer engagement levels.
“In may be that in your area a successful broker generally calls back his customers within 5 minutes, but you are taking 10 minutes.
“Effi may say, ‘Maybe you should call customers within five minutes and your conversion rate will go up’,” said Sodhi.
Voice response technology for Effi is another aspect that could further enhance customer experience.
“We are trialling some voice technologies including an in-car Voice Assistant for mortgage brokers because they are always traveling and are on the go,” said Sodhi.
The potential market that Effi can serve is not just Australia, but overseas mortgage broking too.
“Right now, we are just focusing on mortgage brokers and there are 18,000 in the country, but we would like to go beyond Australia.
“This is a platform that can work really well in the UK or US markets. There are 600,000 brokers in the US alone,” he stated.
Fintech could revolutionise the mortgage finance industry after the Royal Commission into the banking and finance industry.
Sodhi had several business ventures under his belt, prior to the successes of Effi and HashChing.
His first start-ups included a liquor delivery service that he sold, and a location-based shopping platform that gave him a good grounding in expanding his knowledge of customer expectations.
“The previous start-ups were a big learning curve for me. HashChing allowed me to build my network in the mortgage broking space,” he said.
The idea for HashChing came to Sodhi when, as a bank employee, he was looking for a mortgage.
“I was looking for my first home loan, and a friend of mine who had never worked in banking got a better mortgage deal, even though I had a discount as a bank employee. My friend had used a mortgage broker,” he said.
Sodhi attributes his success to his MBA studies at Sydney Business School, and to his banking and consultancy work, for giving him opportunities to build his leadership skills.
He was awarded the accolade of Young Business Leader at the India Australia Business & Community Awards in 2017, and he was a finalist for Optus’s Young Business Leader of the Year award the same year.
This article was developed in collaboration with Effi, a Stockhead advertiser at the time of publishing.
This article does not constitute financial product advice. You should consider obtaining independent advice before making any financial decisions.
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