Lead Forensics
New Podcast with Robert Wiest, CEO, MS Re


Seeing the future, AI, and a fully digital value chain – Robert Wiest, CEO, MS Re

12.02.24 AdvantageGo

The Voice of Insurance podcast featured the CEO of MS Re, who provided his views on the transformative role of data, analytics and technology in the present hard market, and into the future.

There is one sure way in which the recent reinsurance market turn differs from any in the market’s history – and that is the ability of technology to play a leading enabling role for an industry embracing digital transformation.

Digital  transformation was a running theme in Robert Wiest, CEO of MS Re’s appearance on the Voice of Insurance podcast, in which he explained the role of data, analytics, and – increasingly – of artificial intelligence (AI) in driving efficiency and better decision-making insights for the market.

MS Re is a mid-size reinsurer with a giant Japanese parent (Mitsui Sumitomo), which gives the company some strategic advantages, such as in its ability to secure and deploy capital, and also to deploy platforms for digital transformation.

By education an electrical engineer, Wiest describes himself as “a Swiss Re child” after much of his career spent at that reinsurer. He also keeps firmly in touch with his “geeks” origins, he confessed.

“We have a digitisation programme with a lot of components for AI embedded and already in production,” he told host Mark Geoghegan.

The hardened market has accelerated the reinsurer’s overall strategy in most regards, he revealed.

“We are now almost two years ahead of our plan, because the market has changed in a positive way… we continue pushing, we just continue pushing,” he said.

Conversation turned towards a fully digital value chain, and where that will take the market of the future. Wiest said he sees three major aspects, starting with current inefficiency. He cited the example of where premium goes, after the consumer pays for it, along the risk transfer chain.

“Let’s be generous, we’re eating up between 15 to 30%, just by doing our stuff, and that’s very inefficient, which ultimately you see in expense ratio,” he said.

“The second thing is automation in the processing parts, in the middle and back office, technical accounting and claims handling. You will see it in the improved quality of decision making that’s underwriting,” he continued.

For underwriters’ efficiency he is most focused on gains through improved quant decision making. While of these some technology improvements on the loss ratio might in time be negated by competition, as the market embraces the same technologies, for now there is a competitive edge to digital transformation, he noted.

That said, technology’s enabling role for the most recent market turn has been limited, he thinks, with data mining still in its early stages across the market.

“Partially, yes, but in our case was limited by the capability to digest these data, because we’re still rolling out our transformation progressively,” he said.

Future gazing is increasingly scientific, but actually seeing the fires before they happen remains the domain of sci-fi writers and dystopian novelists, which is perhaps a good thing for the industry, he suggested.

“Here’s my philosophical remark: if everyone is getting more information and a more transparent view of the underlying risk, you’re shooting at the uncertainty which drives our business. If I know exactly that’s going to happen, who’s willing to pay me the premium? More data is good. Ultimately, the Holy Grail of knowing everything, would be bad for us,” he said.

The technical capabilities are already in place to absorb huge volumes of data, he emphasised.

“We have the data legs already; we have the infrastructure already in place. We’re using AI in the middle office, technical accounting, claims area to address the efficiency points. We’re not yet using it on the underwriting part,” Wiest said.

Wiest signalled that MS Re will likely deploy AI into its underwriting processes “one year ahead”.

Mark brought up the topic of triaging tasks for the underwriter, using AI and its underlying data.

“We know we can use the same technology in the underwriting space, addressing exactly that processing component, so we can increase productivity in the underwriting space…However, it is not a case where you get a black box, you switch it on, and it works. It takes time to tune that machinery to get what you aspire to on efficiency,” Wiest said.

He remains more sceptical about how to improve the quality of information.

“We know we can take a lot of information, filter it out and provide it as a starting point to the underwriter. We don’t know yet how much of the decision making part, where today you need an experienced underwriter, you can substitute with the machine,” he said.

He sees even more usage for AI at the portfolio analysis level.

“What are the correlations of the various portfolios; do we have our diversification component, which is a factor in the solvency calculation? Small changes make a huge difference on your return on capital, for example, so getting more insights is for a reinsurer very interesting, Wiest added.