At #D1Conf in Cancun, Ron Bernstein of Augment Partners led a fireside chat on the topic of this post that bent minds a little bit. The discussion also featured Jack Peterson of Augur and Martin Köppelmann of Gnosis and focused on the complementary nature of prediction markets and decentralized insurance, and what this may hold for the immediate and long-term future.

What are prediction markets?

Prediction markets are a relatively new phenomenon, even if discussion of them has been going on for decades. They aim to leverage the so-called wisdom of crowds to provide accurate predictions of everything from financial markets, results of sports events, elections, and natural events — such as hurricanes, droughts, and earthquakes.

The three fireside discussion participants have each committed to these markets:

Ron Bernstein is founder and CEO of Augment Partners, which exists “at the nexus of old and new, charting an exciting future in decentralized trade,” according to the company website.

Jack Peterson is a physicist and entrepreneur who founded Augur this year to create a decentralized platform on Ethereum for prediction markets. He believes in the “chance for real money trading profits” through the platform.

Martin Köppelmen founded Gnosis Ltd. earlier this year after spending some time with Consensys, also to create a decentralized platform for prediction markets on Ethereum.

Augur promises “stunningly accurate forecasts on any topic,” while Gnosis notes that it raised US$12.5 million in 12 minutes through a cryptotoken offering through the Dutch auction process. The key word seeming to fuel all this confidence is “decentralization,” which is of course the heart and soul of the blockchain (i.e., distributed ledger) technology.

Ron Bernstein (Augment Partners), Jack Peterson (Augur), and Martin Köppelmann (Gnosis)

Decentralization is the key

Given that insurance as a whole is based on sharing general risk, and that emerging parametric insurance applications are based on sharing specific risks, the idea of an intersection between “betting” on insurance payouts and looking to prediction markets for insight seems logical enough. Adding the decentralized, immutable nature of the blockchain to the parametric discussion turns this logic into excitement.

For one thing, as Jack noted in the discussion, “one of the nice things about (being) decentralized is you have access to a global liquidity pool.” The question then arose as to what degree this pool would be populated by calculated risk takers, speculators, and increasingly, algorithms.

There is such a wide extent of possibilities for parametric insurance and prediction markets that this question is not easily answered. As Martin noted, “you can ‘bet’ on an earthquake occurring somewhere (and the damage it would cause),” even as other groups of offers can be made for more routine matters, such as the Flight Delay application we’ve developed at Etherisc.

Martin said he prefers to use the term “tokenized conditional payments” rather than “prediction platform” to describe what is going on here, even as the term seemed clunky to Ron’s ears and presumably many ears in the audience.

In any case, the similarity with parametric policies and prediction market bets is that the bettors (or investors) are seeking a payout — the key difference is that insurance is meant to mitigate an unfortunate circumstance (whether a flight delay, crop failure, fire, etc.), where prediction markets are centered around the notion of winning something (an Oscar award, an election, a football game, etc.).

Ron Bernstein (Augment Partners), Jack Peterson (Augur), and Martin Köppelmann (Gnosis)

All participants seemed to agree there is a need in some level of a standard — perhaps, a token standard. With claims tokenized, they can then be bundled and traded. This provides a great deal of flexibility and theoretically consequent liquidity to prediction markets and the policies running on them.

The issue of claims adjustment also arose, with Ron thinking that “a fully decentralized system might eliminate claims adjustment. Parties could be paid automatically on the parametric position they have in the marketplace.”

Martin mentioned a real-world complication to this notion, explaining how he had a connecting flight to the Cancun conference from Europe. His first flight was delayed, causing him to miss the second. Should the payout be automatic to him? After all, the oracle will show that the second flight was on time. Further, “what if the first flight was delayed, but I still make the connecting flight and arrive on time?” It would seem no automatic payout is warranted in that case, as what the oracle reports (the first flight was delayed) does not reflect the final outcome of this specific case.

Jack jumped in here, asking whether prediction markets can therefore replace oracles in claims adjustment. He doesn’t think so, saying “an oracle and prediction market are complements. It’s important for a market to know it will eventually converge on reality, so it’s important that the oracle remains independent.”

They had to talk about asymmetry

This led to a discussion of information and potential information asymmetry, which is an enormous issue in the insurance business, as well as financial markets. For example, Jack said it may be easy enough to find data on a rainfall in a specific country, but not on the precise rainfall on an individual farmer’s land. How can a payout be automated in this case?

The idea of a comprehensive IoT / Smart Grid was raised as a solution in this case, clearly taking the participants and audience into the future. This distinction between “micro” and “macro” views, of widely divergent granularity, will be a major issue if prediction markets and parametric insurance policies grow and prosper in the coming years.

This was a fascinating panel that addressed the current state of things, as well as potential futures, from three people who have invested in these potential futures.

With respect to this, Martin noted, “we will be able to insure ourselves against all kinds of risk, at a much better price (in the future). We become more like beta scientists than speculators.” Furthermore, Jack noted that “decentralized prediction markets by their nature are open and anyone can participate, so people with the best information will want to participate. So, they are also open to insurance companies and what they think the proper price and proper probability would be.”

For details, watch the video.