How Global Insurer AXA Uses Quantum Computing to Prepare for the Future

Highlights:

• Although quantum computing is still in its infancy, most industries aren’t attuned to its enormous potential.
• Finance applications using quantum algorithms and quantum software are already gaining a foothold, but there are plenty of untapped growth opportunities within the insurance industry.
• AXA, one of the world’s leading insurers, is preparing for a future that includes quantum computing for insurance and risk analysis applications.

By their nature, insurance companies need to think about — and prepare for — the future. The business problems of today are going to be solved with the technology of tomorrow. So it’s unsurprising that global insurer AXA is exploring breakthrough technologies today to address its future needs.

With this mission in mind, AXA’s Marcin Detyniecki, Head of Research and Development and Chief Data Scientist, and George Woodman, Quantum Computing Lead, are looking far ahead to future-proof the insurance industry, and bringing their colleagues along.

“Quantum computing,” Marcin explains, “is going to disrupt our world.” But instead of just hopping on the bandwagon and throwing around another buzzword, AXA is really trying to understand the fundamentals of quantum computing. Getting ahead of a powerful technology now is a smart move toward outsized future gains — especially when there’s little current competition.

In an episode of The Qubit Guy podcast, George and Marcin discuss how forward-looking enterprises are embracing quantum computing, building support for quantum applications within large companies, and how looking forward into the future can solve critical business problems.

Quantum computing: Get ready for the future

Within the world of finance, quantum computing is already somewhat established — with applications in risk analysis to portfolio optimization and credit risk. 

Most of the insurance industry hasn’t gotten quite as far.

“There's been less activity from the insurance side,” George observes. In the here and now, quantum annealing and universal gate-based quantum computing might solve parts of the bigger problems the industry faces.

“We don't do pharmaceuticals, but our customers do, and that could affect them,” says George. “We need to keep them informed about that, because that's the technology that's probably going to progress the most, the fastest, and they need to be aware of that.”

But insurance research and development efforts involve looking not just at how current technology can solve current problems, but also what the future holds as well — as far as 15 years or more away with some quantum solutions.

“Risk analysis and the Monte Carlo Speedups [have] potential,” George says, referring to a method that uses random sampling to estimate numerical quantities which are hard to calculate outright via other mathematical methods. He continues: “But then you get more optimization based problems that could have a shorter timeline, based on how the technology grows and which technology we are going to use.” 

It’s a dynamic situation in the sense that you’re responding and adapting to what’s in front of you, which could be constantly changing.

At the same time, it’s important to remain levelheaded about quantum’s potential and not get caught up in the hype. “We try to give [our customers] a good baseline [of what to expect] — not to oversell the technology, but so that our business lines understand when it's going to be available,” George says. Essentially, it’s about managing expectations on the road to quantum solutions in production.

A fully quantifiable business solution is a long way off, but that doesn’t mean leaders in insurance and other industries shouldn’t prepare now in order to get an edge on competitors. Gaining awareness of the benefits of quantum now could pay serious dividends in the future.

How to get your company on board with quantum computing

Given that quantum computing is in the early stages, it can be a challenge to pitch its applications to current business problems. “The business part of the problem is very important,” Marcin says. 

“If people come and tell me I can accelerate Monte Carlo sampling from N to the square root of N … what does it mean in practice?” 

How do you get companies into quantum computing? George and Marcin have some valuable industry insight. Here’s what to keep in mind:

1. Build internal competency. Quantum technology is complicated. But that doesn’t mean external consultants or providers should take charge of its course within your organization — ensuring relevant in-house expertise is crucial here. “You need to internalize … that knowledge,” says George.

2. Keep the prototyping cycle short. “Everyone wants to have short cycles,” explains Marcin. Months — rather than years — is the goal, but it’s important to be realistic. The timeline will depend on the problem. Bigger problems require more time.

3. Scalability. Choosing something that scales is important for embracing quantum on an organizational level. But it’s equally essential to acknowledge that non-scalable quantum algorithms can have larger impacts at lower levels than scalable algorithms.

4. Hardware portability. Related to scalability, this is the hardware-specific fine-tuning that takes place after the business problem — and potential solutions — have been identified. “Then you want to optimize this very specific architecture,” says Marcin.

5. Integrate non-quantum experts.When it comes to building the quantum team, who you’re bringing in depends on the business problem you’re trying to solve. Depending on the circumstance, you might need to bring in trade, life insurance or chemistry experts. “Business experts … have short-term missions, results and objectives”, Marcin says. “The whole challenge is to [show that] it's not just one dimension — the technology, the scalability, the architecture — it's really everything [coming together] to make it happen.”

Hone in on these key areas — while firmly focusing on the business problem at hand. “We are still a business, and to sell the technology to the stakeholders, you need to show proof that it's working,” George explains. “There's a lot of balancing between proving something that could potentially work now, to something that could potentially work in 10 years but won't work now.”

From here to there

It’s important to differentiate between realized technology — like quantum annealing — and current research — like a Monte Carlo Simulation. Both can be harnessed to solve different business problems on different timescales.

“The algorithms of today are definitely not going to be the algorithms of seven years from now,” says George. Even with the foundations in place, the technology changes. Selecting the right algorithm for a current problem is tough — projecting a decade forward is even tougher.

Success might very well hinge on collaboration. The key is to create awareness of what quantum computing can do to support organizations — be it quantum algorithms, quantum software, quantum computing insurance, or quantum risk analysis.

“It's about trust,” says Marcin. “It's about sharing and working together.” Because we’re in the very early stages of quantum computing within business, being transparent about what we know and what we don’t know is of paramount importance. 

The emphasis should be on trying to share — rather than withholding — information. It’s being open rather than secretive. Collaborative rather than competitive — for the benefit of all.

Because most of all — to unlock quantum power for real organizational change — there needs to be deeper understanding, and working together accelerates that change.

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This article is based on an episode of The Qubit Guy podcast, which explores business and technical questions that impact the quantum computing ecosystem. Hosted by Classiq CMO Yuval Boger, the interview podcast features thought leaders in quantum computing.