AI on Our Minds: Firms Struggle with How to Incorporate AI

Artificial intelligence

The hype of artificial intelligence is far from fading—actually, it’s more like a building tidal wave. Wei-Shen wonders if the capital markets will catch the wave, or get smothered by the tide.

Previously just a topic for technologists, artificial intelligence (AI) is now on the lips of most everyone, from associates on up to the C-level. In my previous column, I also touched on AI: how financial institutions should not approach AI like one would approach a Whac-A-Mole game at a carnival. And in the August issue of WatersTechnology, there are several articles explaining how firms are trying to harness AI, and the challenges therein. 

AI is, indeed, everywhere—at least as a topic of conversation. So far, curiosity hasn’t killed the cat, but maybe it’s draining some of its energy. It comes down to how firms are tackling AI and what it is being used for, and even deeper, what specific techniques within AI are being used and what datasets are needed for it. 

Do we have an existing problem that AI can help with? Do we have enough data surrounding that problem? Is the data clean? Is it easily consumable? The questions keep on coming. It can be like going down a rabbit hole. 

The message passed down from top management matters too. Often, when it comes to the topic of AI, employees are afraid that their jobs will become redundant, but this is not the way it should be looked at, said Ryusuke Sato, head of data science at Tokio Marine Holdings, speaking at this year’s Tokyo Financial Information and Technology Summit. 

“Management [at times] can’t see what can and can’t be done in AI,” he said. “They think as long as you have the data that AI will deprive jobs for human beings.” Instead, to him, AI can best be used for tasks that are too difficult to employ robotic process automation (RPA).

A live poll was conducted during the session, and 36% of the audience said they already have an AI strategy. Subsequently, 53% said their firm already has an AI strategy for a specific business area. Following my previous column, at least they’re not Whac-a-Mole-ing at problems. 

An interesting way property/casualty insurance company Tokio Marine is using AI is with satellite imagery and geological data that helps it determine flood assessments in Japan, and hence, if it should pay out claims. Sato explained that Tokio Marine uses AI to analyze the images to measure the depth of the submerged areas.

This reduces the time necessary for on-site assessments and speeds up the process of payouts, while helping them to better decide if a payout is necessary at all. Tokio Marine is working with satellite analytics platform provider Orbital Insight for this particular use-case. Sato said the insurer is now working on collecting accident images to feed into its database of traffic accidents, which will help it calculate and analyze the probability of accidents. 

Also during the panel, 40% of the audience answered through a live poll that they would turn to tech companies or consulting firms as their primary source of AI expertise, rather than having to hire internally.

There seems to be more of a willingness to cooperate with clients, competitors, and other industry participants when addressing technologies such as AI. For example, Mizuho Bank formed Blue Lab with WiL LLC—short for World Innovation Lab—for the purpose of creating new businesses based on technological advances. Tatsuya Shirakawa, senior digital strategist at the bank, also said Mizuho is looking at more collaborative opportunities with other financial institutions and banking groups to share know-how and information on improving efficiency. 

Deutsche Bank has also indicated that it wants to work with its clients and even competitors more directly with the aim of making transactions between corporate and institutional clients a more efficient endeavor. It recently hosted a hackathon in Singapore with messaging platform provider Symphony, which saw nine companies—including both clients and competitors—participate side-by-side with DB teams in creating a solution aimed at hyper-connectivity among firms and automation of workflows. 

Moving forward, it will be interesting to see how firms come together as a community to work on making the financial ecosystem more efficient, or if they decide to go back to the old days of doing it alone.  

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