The reinsurance industry is awash with discussions about data these days, not least thanks to the insurtech wave that continues to drive interest from the venture and private equity community.
But what are reinsurance and insurance-linked securities (ILS) market participants trying to do with data?
Yes, there’s a push for straight-through processing of claims along the market chain, which makes having one true view of underlying data absolutely critical (we’re not there yet).
Yes, there’s increasing sophistication in risk modelling and an expanding array of models, covering ever widening numbers of risks and perils as well (much more to do here).
Then there are initiatives and products related to marketplaces, electronic trading, following form using still relatively unsophisticated algorithms, and the still-early days of a machine learning wave that promises to deliver greater visibility of and transparency into risks, and a whole lot more.
But what is the industry trying to do with all of this, where will it lead?
Using data, I believe the industry is trying to ascribe meaning to risk.
By this I mean wrapping more understanding around risk, as well as the flows of risk and capital in the industry.
It’s also about redrawing, or installing, the boundaries around risk that will also aid in understanding it, but perhaps more importantly in structuring it, developing new product opportunities, classes of business and contract forms.
As well as deriving meaning in risks that have previously been lacking understanding, a key opportunity for the data-ready re/insurer or ILS fund.
The industry is also aspiring to derive more meaning from its risk data, of course.
But, by putting some additional meaning (or understanding) around the risks it covers, the reinsurance market can greatly expand its usefulness, by being able to manage and handle its risks, and portfolios of them, a whole lot more effectively.
Data comes in many forms and in ever-increasing quantities.
It’s important to be able to warehouse this, move it around your organisation, share it with your counterparties and generally leverage it to your advantage.
That doesn’t mean it has to be industry-wide standardised, that’s not what I mean.
Trying to get the industry to put its many systems and strategies behind single standardised data formats is not going to happen anytime soon, aside from in certain specific or niche business use-cases.
Ascribing meaning to something enables us to gain a greater or higher understanding of it.
This enables us to make more intelligent decisions, which is precisely what the reinsurance and ILS sectors’ need to begin to do.
There are going to be data winners and losers, as a result, with your ability to wrangle data in ways that allow you to extract more meaning and value from it set to become a key differentiator.
Data equals power, in a number of ways.
In reinsurance, the major globally active broking and underwriting groups hold a lot of this power, given they see a significant proportion of the data related to all of the business ceded across the market.
These major players have had a head start in putting data to work usefully, providing them a competitive-advantage over the last few years.
A number have done this particularly well and will prosper because of it. But some others have clearly squandered this opportunity, as they now languish behind in terms of their data abilities.
The top-tier of reinsurance brokers, in particular, have done a very good job of maximising value from data and their access to it and control of it.
You can see this not just in their pure data and technology-related initiatives, but also in some of the ways they’ve put their data-advantage to work to create underwriting facilities and capital pools for their clients.
An enhanced understanding of risk, capital and market activity gives an edge that can help brokers bridge the divide to the underwriters.
As such, it’s another area we, at Artemis.bm and Reinsurance News see reinsurance brokers and reinsurers becoming increasingly competitive.
It would be remiss not to mention the promise of machine learning and artificial intelligence, in helping risks be better understood, portfolios be better managed, and generally enabling a greater understanding of the predictability, or otherwise, of insurance risks.
Maximising your data advantage may be critical in reinsurance in years to come, so seeing more business can give an edge.
But, more important is having the technical plumbing and infrastructure to gather, arrange, sort, and understand this data lake, so you can better ascribe meaning to it and enhance your understanding of it.
Walled-gardens vs setting it free
In some industries it’s not just owning and securing data that’s important, it’s also having an understanding of how to use it to clients advantage, setting it free to allow it to be used in ways that ultimately deliver value and earnings back to you.
We’ve seen tech giants profit massively by allowing their clients to ride on their data coat-tails.
Reinsurance brokers can do this too, letting both cedents and capital providers surf their waves of data.
Which in turn will deliver more insights back to them and further enhance their ability to ascribe meaning to risk and market data, as well as to understand it (both how it’s used and what it means).
At the moment though, the data flow is really quite one-way and lacking transparency, unless you’re paying a lot for it and that’s likely on top of all your other brokerage costs.
Pricing (and clearing) data is king
In future, marketplaces could be one of the ultimate data-winners, as those that gather and own the true data insights on the pricing of risk, plus the technical ability to understand that data, will own one of the biggest differentiators in reinsurance.
There’s the market price. The fixed or range of costs attached to a risk or group of risks.
But there’s also the actual price it/they clear and trade at.
Knowing both and having the deep technical ability to harness data to the benefit of clients placement and trading of risk, while also extracting data insights for your own needs and to benefit the marketplace users, are significant areas of advantage in risk transfer.
This has played out in capital markets and one day it will in reinsurance too.
The push-back is increasing
This is already playing out to a degree, as reinsurance brokers send letters to clients cautioning them against using marketplaces, effectively saying “if you do, we can’t guarantee you best-execution.”
Which is a fallacy of course, as using technology to find the best price to clear trades at is accepted as the optimal mechanism, superior to human trading, in almost every asset class, except for risk (so far).
With a clear data advantage, if they can gain broad market adoption, a reinsurance marketplace or trading platform would also be the best venue for beta-style capital deployment, or following-form, or establishing facilities and the like.
Something reinsurance brokers are all too aware of, which is one of the factors causing the delivery of letters to clients that we’ve seen, and also something now holding back broad adoption of reinsurance marketplace tech, I believe.
So this area, of reinsurance brokers vs marketplace tech, could be where the data battle comes to a head.
Although the broker-reinsurer battle is set to accelerate as well.
Data wrangling = opportunity
Which brings me onto where the startup opportunities could be.
Helping cedents understand their data, apply meaning to it, manage it better, derive insights from it, is going to be key.
Once upon a time (25 years ago) I thought capital (how it’s managed, structured, deployed) would be an efficiency driver in reinsurance.
The capital markets and ILS have made a huge difference, but still haven’t gone as far as I’d thought they would (yet).
Data and the technology to use/understand it, has similar potential as an efficiency driver in reinsurance.
The industry is still in its infancy when it comes to utilising data, in really effective ways.
While reinsurance is a data heavy market, the future could see enormous gains made as streams of data are effectively put to work.
It’s advancing fast and is going to be a real point of both differentiation and competition in the reinsurance market.
Ability with data, has the potential to give some players additional leverage over their competition and an edge that others may struggle to match.
Steve Evans 