Gefen’s AI technology may be used in a wide range of businesses, potentially creating opportunities for increased revenue development.
Artificial intelligence (AI) is becoming more incorporated into our daily lives, affecting industries all around the world.
From e-commerce to automobiles, advertising to banking, AI is slowly but steadily changing our societies.
AI technology has assisted insurers in assessing risk, detecting fraud, and reducing human error in the application process across the financial services sector, most notably in insurance.
Gefen International (ASX:GFN), an ASX-listed firm, has fully embraced AI, building its own unique AI technology, a foresight choice that has allowed the company to place itself at the forefront of the global insurance (and financial) market.
Gefen claims that its in-house engine can be expanded across multiple areas and that its application will almost surely open up new verticals, allowing the company to increase income.
The GQL, or Genetic Qualitative Learner, is Gefen’s proprietary AI engine.
“We developed this engine to function like a human gene, where DNA provides information to the entire body on how to become stronger,” said Orni Daniel, Gefen’s CEO.
According to Daniel, the GQL could predict with a high degree of certainty what other insurance products a customer could want based on characteristics such as age, salary, and interests.
“A lot of the information and factors out there are beyond the capacity of a human being to understand, and we’re unable to match them to a final outcome,” Daniel explained to Stockhead.
“So we created GQL to analyze a massive quantity of data and provide a result that neither you nor I can see.”
AI engines, according to Daniel, acquire and analyze fresh data on a constant basis.
He claims that the more input he has, the smarter the outputs will be.
“If the technology provides an output with a chance of less than 50%, we will not reveal it to the insurance agents and we will not sell the consumer a new plan,” Daniel explained.
“However, if the ultimate result or output has a possibility of greater than 80% or 90%, we could reveal it to advisors, who might then utilize it to sell customers new products like health or auto insurance.”
Daniel highlighted that large businesses such as Amazon have employed a similar technology extensively.
The Amazon platform provides consumers with a personalized “Things you might enjoy” suggestion, which has resulted in 30% to 40% greater purchases on the site.
This, according to Daniel, is a perfect illustration of how Gefen’s technology may be used in businesses other than insurance and banking.
Gefen’s platform is now focused only on the insurance and financial industries.
In short, Gefen offers advisers a highly compliant platform that includes features like messaging and sales and marketing that would otherwise be unavailable.
It successfully provides a distribution network of resources that every insurance/financial adviser requires to personalize their service to customers without requiring the clients to become specialists.
“Around 60% of family income is spent on insurance and finance right now, so that’s already a large market for us,” Daniel added.
“The challenge now is how AI can help agents capture this market and sell additional items to the same family or customer?”
“How else could it be applied in other industries?”
Gefen’s GQL AI technology, according to Daniel, was designed as a general platform, which means it may be readily used in industries other than insurance and finance.
He indicated that Gefen is concentrating its efforts on businesses where human counsel is critical.
This refers to industries with complicated goods and transactions that take more than two clicks to accomplish.
“Getting a mortgage or investing in a fund manager takes more than two clicks,” Daniel explained.
Pharmaceuticals, automobiles, and even real estate are some of the other industries that might be attacked.
“With our AI technology, it’s all about enabling the agents in those businesses,” he continued.
“Those agents may not be able to comprehend the technology and may not have the time to do so. “They may even be required to follow regulations,” Daniel remarked.
“Without the adviser having to learn anything new, our platform could address all of these difficulties for them.”
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