Artificial intelligence could be used to hunt rogue brokers

A new prescriptive algorithm has been created which could one day be used by ASIC to spot fraudulent behavior by rogue brokers. Launched by tech start-up Veriluma, the platform can be embedded behind an aggregator’s CRM system to track important data such as client details and product information. It is designed to spot any subconscious bias the broker may exhibit when delivering their services. “Bias can be by omission; bias can be hindsight; bias can be familiarity,” Richard Howard, advisory board member for Veriluma, told Australian Broker. “What happens if I have dealt with a particular bank several times? Bang, bang, bang – three loan successes. Immediately I throw the next loan to that bank but is that the suitable product?” The firm has already talked to ASIC about new tech that gives the regulator better oversight over the 23,000 brokers and advisors in Australia, said Veriluma CEO Elizabeth Whitelock. This would ensure advisors are acting in the best interest of clients with the products they are recommending, allowing ASIC get on top of individual brokers before they go rogue, she added. “From a strategy perspective, we may not know who the rogue individuals are but what we might be able to spin up is a model which actually shows us what the behaviour may look like. “We can take real data and ingest that from different scenarios. This might start to give us a flavour so that when we start to see that behaviour coming through, we can stamp down on it before it gets out of hand. That way, we can be more proactive.” A better fit The algorithm may also help brokers find the best products for clients by feeding information about the individual and certain products into the system, Whitelock said. “That could sit in the background doing a quick assessment based on what we know about the client and what they’re looking for – are these the right fit?” This means the broker no longer has to sift through hundreds of individual loan products one-by-one, she added. “It’s not only the suitability of the product,” said Howard. “That’s an idealistic scenario – which products am I most suitable for – but then what’s my probability of approval?” The background assessment would be looking at both of these factors, Howard added, and would compile a list of suitable products ranked by the likelihood of approval. “That’s a process which could take a broker days,” he said. However, this system was not meant to be a replacement for broker-led decisions "but it can be a check,” he added. Veriluma tackles individual problems – such as which loans will be most suitable for a client – and then examining what that problem looks like. “What’s the question you want to answer and what are the elements that make up all of that?” said Whitelock. “Underneath all of those elements, there may be a dozen further elements, so we may end up with a hundred different issues that become information points. That’s where we start.” The flexibility of Veriluma’s prescriptive analytics allows it to be tailored to the needs of each broker’s clients. “The algorithm’s already patented so we don’t touch that. The only thing that changes is the clothes that you want to wear,” said Whitelock. “It becomes a layer on top of the engine.” This means that, for mortgage brokers, Veriluma could train some of the firm’s analysts to build a model specifically for the type of clients being catered to. The company is currently gathering research in the financial services sector by talking to brokers, aggregators and other parties in the value chain to see how the algorithm can be used in the mortgage space, Howard said.