Pulling back the curtain to shine light on ‘scary’ insurance phrases

triggershock_lions-and-tigers-and-bears

Reinsurance/ILS, Blockchain, and insurance financials.  Not quite lions, tigers, and bears, but for many who follow insurance the three concepts are as daunting and pose discomfort in understanding. Why then the mention?  Because in an earlier social media post I noted that the three words do not generate a lot of media content traffic, and if there is a related posting, not much response.  A wise connection dropped the key hint to that puzzle- the words need to be discussed in context that makes sense to the reader.  A cool idea, Modern Accelerator .

Patrick Kelahan is a CX, engineering & insurance consultant, working with Insurers, Attorneys & Owners in his day job. He also serves the insurance and Fintech world as the ‘Insurance Elephant’.  Image

Let’s dive into the three concepts with a full recognition that this blog will serve merely as an overview and whetter of appetites causing the readers to want to consume more. Fair warning- even keeping the topics brief- TL:DR may apply.  That’s OK.

Insurance Financials

There is plenty of government oversight for accounting that dovetails with plenty of regulation, we can’t touch on all the respective countries’ agencies and regulators but in essence they all serve the key roles of making uniform 1) how insurers account financially for their business, and 2) how insurers account for how solid they are in being able to serve their policyholders relative to the agreed scope and cost of risk.

It’s an alphabet soup of government orgs or standards: GAAP, FASB, SAP, IRDAI, NYDFS, SEC, IFRS, FCA, FSDC, SUSEP, NAICOM, ICLG, ASIC, APRA, etc. (almost) ad infinitum.

Fundamentally there are three accounting principles (of the many) with which insurers must comply, just in a slightly different manner from most business organizations :

  • Revenue Recognition Principle
  • Matching Principle
  • Historical Cost Principle

Without complicating things too much, insurance companies have financial stability burden to prove continuously- a carrier’s ability to fund the risk costs that it has agreed to.  All those policyholders have an expectation of indemnity or payment if a loss or occurrence to which their policy agrees to cover /pay comes to fruition.

The three principles noted above are part of the key differences between insurance companies and others, primarily because what insureds receive for premiums is a risk agreement that elapses over time.  Receive $1000 for an insurance contract today for twelve months’ cover.  Money in the bank for a promise over time.  So in respect to compliance with the Matching Principle, premiums are deemed  ‘written’ only until an increment of the policy’s time is expired, wherein the portion of the premium that matches the period is booked as ‘earned’.  One month’s policy duration allows 8 ½% of the written premium to become earned, six months’ earns 50%, and so on.

So you can see how a carrier with a ton of cash on hand might not be as liquid as one thinks if there are an according ton of policies on the books whose expiration extends over twelve months or more.  Written and earned- key concepts.

Here’s an example of a P&L statement showing the written and earned premiums, from German insurer, DFV_AG or Deutsche Familienversichurung:

DFV Inc

The sharp eye will note in addition to written and earned premiums there are lines showing the ‘Share of reinsurers’; that will be touched on in the Reinsurance portion of our discussion.

Traditionally the written and earned difference followed a solid calendar pattern due to typical annual expiration of polices.  But what of on demand or ‘gig’ policies?  The covered period may be a few hours or days, so there is little lag between written and earned status.  Knowing a carrier’s business model has become more important than ever since a heavily funded entrant’s cash may be more restricted if it’s a traditional style insurer in comparison with an on-demand player.

Carrying the discussion to the Matching Principle (matching costs to the period in which the costs were incurred) suggests a few important financial factors:

  • Costs of policy acquisition is matched to immediate written policy premiums, e.g., agency/brokerage commissions, marketing, admin office costs, digital format costs, etc., but
  • Costs of policy administration, e.g., adjusting expense, loss costs paid, etc., may be charged to earned premiums in a different incurred cost period.

As for the Historical Cost Principle, regulators want to know concretely what amount a carrier assigns to portfolio assets.  Insurers need to be liquid in their asset portfolio so assets can easily be converted to cash if loss payment volume so demands.  For example, bonds might fluctuate in value over time due to variances in interest rates, but carriers need to maintain a historic cost to keep regulators content for solvency calculations.

Quite a rabbit hole are financials, so the conversation will conclude with THE common comparative measures for P&C carriers-  loss ratio, expense ratio, and combined ratio.  These measures will give the reader a clear idea if earned premiums (revenue) exceed or are exceeded by expenses and loss cost.

So,

loss ratio = claim payments + adjustment expense/earned premiums, expressed as a %

expense ratio = expenses other than adjustment expenses/earned premium. Expressed as a %

combined ratio is a sum of the LR and CR.

Ideally CR is < 100%, meaning earned premiums exceed costs and underwriting activity is profitable.

What must be remembered as carriers are compared- the maturity of a carrier in terms of time in business, how aggressive is growth relative to existing book, the nature of the carrier’s business and how that affects reserves (immediate draw on profits.)  Entrants may have LR that are in the hundreds of %; consider trends or peer comparisons before your lose your mind.

Reinsurance

Reinsurance is insurance for insurance companies.  There, that was easy.

Rei was once an easier financial concept to grab- carriers would sign treaties with reinsurance companies to help protect the primary insurer from loss outcomes that exceeded typical loss expectations.  Primary carriers do not plan (or price) for an entire region to be affected at the same time, but sometimes things happen that require excess over planned loss payments, e.g., wind storms, wildfires, tornadoes, earthquakes, etc.  Primary carriers will purchase reinsurance that for a specific period, and in an amount that is triggered once a carrier’s loss payments for the treaty peril or perils is incurred.  Pretty direct and expected by regulators, and part of claim solvency calculations.

What has occurred over years is that reinsurers have evolved into other types of excess risk partners, covering more than just catastrophe losses, and becoming excess risk options.  If you again review DFV_AG’s income statement and consider the premium and loss cost portion of the carrier’s P&L shared with reinsurers, you’ll understand the firm has ceded premium and costs to backers to help smooth growth and provide backstop to the firm’s ability to pay claims and serve its customers.  This has become a common methodology for startups and existing carriers, allows more product variety for reinsurers and spread of risk.

Another evolution over the past years beyond reinsurance is the advent of Insurance Linked Securities (ILS), capital vehicles that are designed solely as alternative risk financing.  Insurance-linked securities (ILS) are derivative or securities instruments linked to insurance risks; ILS value is influenced by an insured loss event underlying the security.  What’s that?  ILS are capital vehicles that simply are designed to pay on an outcome of a risk, e.g., hurricane, earthquake, etc., sold to investors looking for diversified returns in the capital markets.  A hedge against a risk for insurers, an option for better than normal market returns for the holders.  Often referred to as Cat bonds, these bonds serve an important role in the risk markets, and are an opportunity for holders for income.  Often ILS are sliced and diced into tranches of varying risk bonds to smooth the outcome of a linked event.  Don’t be surprised if ILS become a more accepted means of financing more common, less severity risk within the industry, or in use in unique new risk applications, an example being pursued by Rahul Mathur and colleagues.

Blockchain

So much promise, so much confusion, overreach and failure to launch.  Or maybe Blockchain’s connection with the perceived wild west of value transfer, crypto currency, has colored the insurance world’s relative arm’s length view of the concept.

A quick search of definitions produces many references to bitcoin and other crypto currency (I’ll leave those to my knowledgeable Daily Fintech colleagues), but we simply want a definition that maybe doesn’t sound simple (Wikipedia):

“By design, a blockchain is resistant to modification of the data. It is “an open, distributed ledger that can record transactions between two parties efficiently and in a verifiable and permanent way”. For use as a distributed ledger, a blockchain is typically managed by a peer-to-peer network collectively adhering to a protocol for inter-node communication and validating new blocks. Once recorded, the data in any given block cannot be altered retroactively without alteration of all subsequent blocks, which requires consensus of the network majority. Although blockchain records are not unalterable, blockchains may be considered secure by design and exemplify a distributed computing system with high Byzantine fault tolerance. “

Open. Distributed. Peer-to-peer. Decentralized. Immutable. Cool for generating crypto, but not so much for the wild data sharing needs of insurance.

So why is Blockchain not taking hold for insurance?  The use case is tough for carriers- unstructured data (of which carriers have a ton) do not play well in a Blockchain (Blkcn) environment, many changing players in an insurance claim, and so on.  Blkcn holds data securely, but doesn’t guarantee cyber security outside the ledger. Blkcn can be more cumbersome for data retrieval across consortia-based ledgers.  Multiple writers to the ledger, multiple efficiency issues to overcome.

But what of uses for reading data once placed in the ledger? Can be very cool. Anthem is a US health insurance provider serving millions of subscribers nationally, the company recently initiated a Blkcn pilot wherein the company is making ledger access an option for the test participants, with patient records stored in the ledger, and individual subscribers given the option to give providers access to health records via use of a QR code that has an expiration date.  Subscribers have the power over their records and access is given for read only permission.  There are many potential benefits to health insurance Blkcn but the options must dovetail with data security.

Another positive scenario for Blkcn application- crop insurance in previously under-served markets.  OKO Insurance provides micro crop insurance policies in Africa, backing by reinsurance but administered in part by distributed ledger, each farmer’s information residing in the ledger, and access provided to underwriting and reinsurance.  And- if payment is made a partnership with digital payment systems to facilitate settlement.  An active Blockchain as a service company, BanQu, is expert at facilitating these frameworks and has a portfolio of projects around the globe where ‘first mile’ and ‘last mile’ data are administered within a ledger for the respective customer and its affiliates/suppliers.  Permissioned but not written by multiple players, QR codes to allow involved sources access to a supply chain.  And the sponsor of the ledger has a clear data record of each step in a supply or value chain.  Speaking with the firm’s business development executive, Brady Bizal, we discussed how a Blkcn ledger such as BanQu provides could serve as an ecosystem initiative for regions, including the details of insurance for a farmer, payment records, link to in country digital payment systems, risk mitigation firms, and as warranted, the transaction/finance data can be accessed by permissioned bankers at the customer’s choice- the magic of QR codes.  It’s an entrée to a trust system that may otherwise not exist.  Opportunity.  Maybe not the original thinking for Blkcn and insurance, but sit for a few minutes and you will think of many similar possibilities for blockchain use in health insurance alone.

Sorry, there is so much that could be written about the three concepts and I’m hopeful the article answered some questions about finances, blockchain and reinsurance/ILS.  It’s certain readers and experts will advise me of missing sections, and that will be the foundation for a next article on the subjects.

You get three free articles on Daily Fintech; after that you will need to become a member for just US $143 per year ($0.39 per day) and get all our fresh content and archives and participate in our forum.

 

The post Pulling back the curtain to shine light on ‘scary’ insurance phrases appeared first on Daily Fintech.

Speaking of Blockchain, what of its place in insurance?

blockchain

I’ve felt as an orphan child within the Daily Fintech family, at the end of the common table but the uncomfortable ‘outsider’ because the content I produced for publication was not Fintech or Blockchain oriented.  The Insurtech content has always been embraced as an integral part of the blog, but like the student who does not quite know how to affix the sash on the uniform I have been feeling a little insecure.

Patrick Kelahan is a CX, engineering & insurance consultant, working with Insurers, Attorneys & Owners in his day job. He also serves the insurance and Fintech world as the ‘Insurance Elephant’.

image

Hard to believe that lede?  Should be, and is.  My DF colleagues are experts in what they write of- finance, crypto, and by extension, Blockchain, and collegially embrace the InsurTech discussions.  So not under any pressure to do so but having an intellectual and industry curiosity I figure it’s time to discuss insurance and Blockchain- unmixed oil and water, or tasty salad dressing?  Blind dates or maybe life partners?

I am privileged to have insurance connections/colleagues who understand Blockchain and are willing to share perspectives, so I reached out to several for background and explanation.  See, while I am no expert at Blockchain (BKCN), crypto, distributed ledgers, etc., I do understand the basics, and have yet to find a ‘tipping point’ application of the principle for insurance.  One might figure if there was, a 5 trillion USD industry would have integrated the idea already.  Instead, there are rumblings of the benefits of BCKCN but few projects at scale.

Consider some projects with traction (thanks, Walid al Saqqaf, Insureblocks founder; readers can find these ideas and many others at his podcast, https://www.insureblocks.com/):

  • Addenda, an insurance subrogation solution founded by CEO Walid Daniel Dib, and located in the U.A.E. Addenda has developed a BKCN alternative to what has always been a manual process fraught with delays and errors, subrogation of claim payments.  The decentralized, trusted nature of BKCN lifts much of the existing barriers to efficient subrogation settlement through placement of immutable records of the loss that the parties can mutually access.  With sufficient subscription by companies, is it possible the volume of liability arbitration would be reduced in other markets?
  • B3i– a Property Catastrophe Excess of Loss Reinsurance application, with John Carolin at the helm as CEO. B3i is a vanguard of what might be commonplace for the insurance BKCN future- a Distributed Ledger Technology (DLT) that is owned by 18 insurance market participants, with active involvement by 40 insurance companies, shareholders, etc.  As such the question of who supports the ledger financially is answered, who has participation rights, and how is the common ‘language’ or protocol of data insertion determined.  As John states, placing reinsurance has traditionally been a very analog process, with the height of innovations being email communication of terms and bids.  BKCN through B3i ‘democratizes’ the data, and access to the players, and encourages use of smart contracts with their basis being the set terms within the ledger.  Can this democratization and sharing of costs be expanded to include other types of insurance, and a far broader community of permitted companies?
  • Blockclaim, a BKCN innovator founded by Niels Thonéthat has an aim of clarifying what is now fifty shades of gray (not that one!) that are generated by the many participants involved with insurance claims, and the volume of data that claims generate. Changing a cumbersome multi-lateral, manual/digital approach of claim handling to a permissioned ledger allows concurrent access to immutable claim facts for all involved parties, leading to less cumbersome (read as more prompt) claim handling.  Can this principle also be broadened to include underwriting characteristics for insured property?  One might think so with sufficient mutual ledger support across a spectrum of companies.
  • Ryskex, a “blockchain based ecosystem for alternative risk transfers”, championed by CEO and co-founder, Dr. Marcus Schmalbach. Ryskex stands for ‘risk exchange’, focusing on new forms of identified risk, and/or previously non-insurable risk in a B2B environment.  The firm’s principle- if these unique risks are typically outside an indemnity risk prediction form, applying parametric principles to these risks, in conjunction with AI methods for determining indices and with trigger forms/indices stored within a ledger for transparency and ease of payment, BKCN can facilitate risk vehicles in less insurance traditional forms that capital markets are more apt to adopt.  Can insurance evolve into a capital risk model and less of a peril/indemnity model?  Dr. Marcus makes a case for it.  In parallel with the risk model changes Marcus is supporting a soon to be released book with John Donald, “Heartbeat in the fog – Parametric Insurance for Intangible Assets”.  While this second book of John’s has a focus on newer risks, e.g., cyber, its principles lend well to parametric and BKCN.  And who am I to question its utility, as Dr. Marcus cites John as the “master mind” and “one of the smartest guys I ever met.”   We won’t let Dr. Marcus kid us about being a smart person in the room; his upcoming journal publication that focuses on insurance of 2030 has a fascinating excerpt speaking of an insurer of the future:

if you have sufficient capital at your disposal, you can be an insurer.  Capitalism meets Anarchism- an ecosystem based on transparency and security of blockchain technology…because of a risk trading ecosystem instead of industrial insurance.”

An additional recent insurance blockchain success deserves mention- insurance startup Etherisc’s quasi-parametric project conducted with partner firms Aon and Oxfam- micro-policies for crop failures for Sri Lankan farmers.  Not a direct parametric solution but a transparent form where the policy data and payment expectations resided within a blockchain ledger, and automatically triggered.  Progress.

And are there firms working in the background to facilitate organizations’ migration to blockchain environments?  Yes, of course.  Global consulting firms are actively pursuing blockchain programs as are startups and independents.  A US-based firm, Fluree, is actively developing data platforms for what they refer to as the ‘Fourth Industrial Revolution.’  In discussion with Kevin Doubleday, Marketing Communications Lead at the firm, Fluree (as do many companies) recognizes the traditional database structure of data, middleware, and now APIs is being overwhelmed by the volume and form of data and business processes driven by same.  Many suggest that blockchain is not the ideal option for use in insurance claims processes due to the varied forms of and demands on data (thanks, Mica Cooper and Chris Frankland for that discussion), but as Kevin and I discussed perhaps considering eating the elephant one bite at a time by choosing insurance processes that would have narrow but meaningful applications, e.g., subrogation (as noted above), transparency and immutability that would facilitate anti-fraud efforts, or deed and title data repositories.  Fluree is also focused on having a universal access format that will accommodate all users.  Current users of Fluree’s services includes life insurance solution startup, Benekiva, whose co-founder and all-around smart tech person, Bobbie Shrivastav  introduced me to Fluree.  Quite a bilateral endorsement.

So, Blockchain and insurance, dating but not yet in a committed relationship.  Seems we might be wise to plan a formal ceremony a few years from now when the relationship ‘learnings’ have been resolved.

And, perhaps now I can have a seat at the big blockchain table at DF.  😀

You get three free articles on Daily Fintech; after that you will need to become a member for just US $143 per year ($0.39 per day) and get all our fresh content and archives and participate in our forum.

The post Speaking of Blockchain, what of its place in insurance? appeared first on Daily Fintech.

Corda powered SWIFT GPI Link could be a game-changer in global trade finance

In September, SWIFT – the inter-bank messaging firm, announced the successful proof of concept (PoC) of the “GPI Link” platform in collaboration with R3. The SWIFT Global Payments Innovation (GPI) platform has previously trialled Hyperledger without much luck.  However, with R3’s growing network of corporates, the pilot seems to have gone better. The pilot also […]

The post Corda powered SWIFT GPI Link could be a game-changer in global trade finance appeared first on Daily Fintech.

Two live Blockchain use cases in Mutual Funds administration and four pilots

In Blockchain world everybody wants to be `the World`s first`. The term started being a must in white papers, now it is all over social media, with announcements about The World`s first tokenized equity The World`s first STO The World`s first regulated Crypto bank The World`s first Initial Wallet Offering The World`s first Regulated ATS […]

The post Two live Blockchain use cases in Mutual Funds administration and four pilots appeared first on Daily Fintech.

FCA pioneers digitising regulatory reporting using DLT and NLP

Too many TLAs (Three Letter Acronyms), I agree. Earlier this week the Financial Conduct Authority (FCA) published the results of a pilot programme called Digital Regulatory Reporting. It was an exploratory effort to understand the feasibility of using Distributed Ledger Technology (DLT) and Natural Language Processing (NLP) to automate regulatory reporting at scale.

Image Source

Let me describe the regulatory reporting process that banks and regulators go through. That will help understand the challenges (hence the opportunities) with regulatory reporting.

  1. Generally, on a pre-agreed date, the regulators release templates of the reports that banks need to provide them.
  2. Banks have an army of analysts going through these templates, documenting the data items required in the reports, and then mapping them to internal data systems.
  3. These analysts also work out how the bank’s internal data can be transformed to arrive at the report as the end result.
  4. These reports are then developed by the technology teams, and then submitted to the regulators after stringent testing of the infrastructure and the numbers.
  5. Everytime the regulators change the structure or the data required on the report, the analysis and the build process have to be repeated.

I have super simplified the process, so it would help to identify areas where things could go wrong in this process.

  1. Regulatory reporting requirements are often quite generic and high level. So interpreting and breaking them down into terms that Bank’s internal data experts and IT teams understand is quite a challenge, and often error prone.
  2. Even if the interpretation is right, data quality in Banks is so poor that, analysts and data experts struggle to identify the right internal data.
  3. Banks’ systems and processes are so legacy that even the smallest change to these reports, once developed, takes a long time.
  4. Regulatory projects invariably have time and budget constraints, which means, they are just built with one purpose – getting the reports out of the door. Functional scalability of the regulatory reporting system is not a priority of the decision makers in banks. So, when a new, yet related reporting requirement comes in from the regulators, banks end up redoing the entire process.
  5. Manual involvement introduces errors, and firms often incur punitive regulatory fines if they get their reports wrong.
  6. From a regulator’s perspective, it is hard to make sure that the reports coming in from different banks have the right data. There are no inter-bank verification that happens on the data quality of the report.

Now, to the exciting bits. FCA conducted a pilot called “Digital Regulatory Reporting” with six banks, Barclays, Credit-Suisse, Lloyds, Nationwide, Natwest and Santander. The pilot involved the following,

  1. Developing a prototype of a machine executable reporting system – this would mitigate risks of manual involvement.
  2. A standardised set of financial data definitions across all banks, to ensure consistency and enable automation.
  3. Creating machine executable regulation – a special set of semantics called Domain Specific Language (DSL) were tried to achieve this. This functionality was aimed at rewriting regulatory texts into stripped down, structured, machine readable formats. A small subset of the regulatory text was also converted to executable code, from regulatory texts based on this framework.
  4. Coding the logic of the regulation in Javascript and executed using DLT based smart contracts.
  5. Using NLP to parse through regulatory texts and automatically populate databases that regulatory reports run on.

If the above streams of efforts had been completely successful, we would have a world of regulators creating regulations using DSL standards. This would be automatically converted to machine executable code, and using smart contracts be executed on a Blockchain. NLP algorithms input data into the reporting data base, which will be ready with the data when the smart contracts were executed. On execution, the reports will be sent from the banks to the regulators in a standardized format.

This would have meant a few Billions in savings for UK banks. On average, UK banks spend £5 Billion per year on regulatory programmes. However, like most pilots, only part of the programme could be terms as successful. Bank’s didn’t have the resources to complete all the above aspects of the pilot successfully. They identified the following drawbacks.

  1. Creating regulatory text in DSL, so that machines can automatically create and execute code, may not be scalable enough for the regulators. Also, if the creation of code is defective, it would be hard to hold someone accountable for error prone reports.
  2. NLP required a lot of human oversight to get to the desired level of accuracy in understanding regulatory texts. So, human intervention is required to convert it to code.
  3. Standardising data elements specific to a regulator was not a viable option, and the costs involved in doing so is prohibitive.
  4. While the pilot had quite a few positive outcomes and learnings, moving from pilot to production would be expensive.

The pilot demonstrated that,

  1. A system where regulators could just change some parameters at their end and re-purpose a report would enable automated regulatory reporting.
  2. Centralizing processes that banks currently carry out locally, create significant efficiencies.
  3. Dramatic reduction in the time and cost of regulatory reporting change.
  4. Using DLT could reduce the amount of data being transferred across parties, and create a secured infrastructure.
  5. When data is standardised into machine readable formats, it removes ambiguity and the need for human interpretation, effectively improving quality of data and the reports.

In a recent article on Robo-Regulators, I highlighted the possibilities of AI taking over the job of a regulator. That was perhaps more radical blue-sky thinking. However, using NLP and DLT to create automated regulatory reporting definitely sounds achievable. Will banks and the regulators be willing to take the next steps in moving to such a system? Watch this space.


Arunkumar Krishnakumar is a Venture Capital investor at Green Shores Capital focusing on Inclusion and a podcast host.

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email


Are Stock exchanges fast and efficient?

financial-markets

The Austrian school of economics view is that

Stock Exchanges are the fastest and most efficient data-processing large scale system that we humans have designed so far.

Stock exchanges need roughly 15minutes of trade to determine the effect of a piece of news – political, scientific, ecological, societal etc – on the prices of shares.

Whether this will change with DLT technology and when is up in the air. For now, we have old and powerful institutions running these data-processing systems and it won’t be easy to take steal their Cheese.

The Frankfurt Stock Exchange is over 400 yrs old with a market cap putting it in the 10th position globally[1]. The London Stock Exchange (LSE) and the New York Stock Exchange (NYSE) are both over 200yrs old and are in the 3rd and 1st respectively by market cap. Just a few blocks away from the front runner, there is NASDAQ only 45yrs old and with a 2nd ranking in market cap.

The 29yr old Australian Securities Xchange (ASX) ranking 14th in size, is actually the bravest in that they were the first to explore DLT technology for their settlement and post-trade activities. Digital Asset has been their partner, with whom they have been designing a replacement of their Clearing system CHESS since 2015, which they actually own (not the case for other stock exchanges). The full launch has been pushed out again from 2020 to 2021.

The architecture of this system maintains the messaging-based interaction with its participants and does not require them to have to run a node on the network in order to participate.

“We are often told by many, including other market infrastructures, ‘You’re so brave that you’re going first, you’re using DLT’ — we actually genuinely consider it brave to embark upon a large transformation program and not adopt this technology,” said Cliff Richards[2] ASX`s executive general manager of Equity Post-Trade Services.

NASDAQ is the most active stock exchange by being involved in several different DLT initiatives that are, however, recent.  In Spring 2016, in a post about Fintech in action on Western stock exchanges, I had mentioned Linq, a private blockchain company focused on private securities issuance. Linq allowed unlisted private companies to represent their share ownership digitally and securely. Later, Linq and Chain[3], a blockchain services provider, used DLT to register digitally ownership of private shares.

In May 2017, Nasdaq partnered with CitiConnect for Blockchain and took Linq to the next level. They went through a seamless end-to-end transactional process for private company securities.  Payment and reconciliation magic via DLT.

In October 2018, NASDAQ also partnered with the Azure blockchain service of Microsoft[4]. The aim is to integrate it in order to improve buyer-seller matching, management of delivery and payment. The key advantage they present is that this deployment will allow for interoperability with customers using various blockchains.

What really caught my attention is the Nasdaq`s use of DLT technology in their newswire services. They are starting to use smart contracts for time-sensitive data like corporate announcements, press releases, regulatory filings, etc and the associated valuable meta-data. Nasdaq seems to have filed for a patent around this  – Nasdaq Gets Patent for Blockchain Newswire to Solve Gaps in Audit Trail Gaps and Errors[5]!

For me, this latest use case can be big. Distributing meta-data through smart contracts and giving access to it on a pay-as-you-go basis, will be a huge business in financial markets and Nasdaq can dominate in this. If this then gets integrated into their market analytics business, then bingo.

[1] Data source from the Visual Capitalist as of April 2017 – Comparing the largest Stock exchanges

[2]Here’s what to expect from ASX’s blockchain-based CHESS replacement

[3] Chain was acquired by Stellar in Sep 2018

[4] Microsoft to Integrate Blockchain Offering Into Nasdaq Services Following New Partnership

[5] Nasdaq Wins Patent for Blockchain-Based Newswire Service

Efi Pylarinou is the founder of Efi Pylarinou Advisory and a Fintech/Blockchain influencer. 

Get fresh daily insights from an amazing team of Fintech thought leaders around the world. Ride the Fintech wave by reading us daily in your email.