XBRL creates a new equities research value chain & democratizes the stock market

Democratized data

This is Part 2 of a 2 Part Research Note, where we look at how XBRL could enable a new equities research value chainIn Part 1, on Wednesday, our Research Note described how regulation and market pressure is forcing transparency on equities research and how that is leading to cost pressures. Our thesis is that the only way out is to reduce cost via automation and that is where XBRL is ready for its prime time. A new breed of micro research firms will enter the market opened up by regulation and empowered by XBRL. They will start by solving a huge pain point in small cap equities research. There are investing bargains to be had in small cap. On the other side of the table the small cap companies have been neglected; they are in “small cap hell” and want to be discovered by investors. New value chains will form around new business models that use XBRL automation.  

XBRL 101

  • XBRL stands for eXtensible Business Reporting Language.
  • It is an open standard based on XML, created by an accountant named Charlie Hoffman.
  • If you tag content consistently, software applications can more easily analyze the data and present more useful information. Think of XBRL like a barcode on financial statements. Yes, that sounds like the Semantic Web, and we all know that the Semantic Web has faced the chicken-and-egg problem (i.e. not enough content is semantically tagged yet and so developers don’t create tools to parse the semantic data). Imagine a Semantic Web standard where governments around the world tell companies that they must tag data that way. That is XBRL
  • XBRL gained attention when the SEC in the US in 2009, mandated that public companies report their financial results in XBRL.
  • The SEC XBRL mandate motivated almost every major market around the world to follow suite.
  • XBRL is being used across almost every asset class. In this post we focus only on equities.

For more research, go to XBRL.org

It was this superb article in Wired called Radical Transparency in the dark days of February 2009 in the thick of the Global Financial Crisis that first got me excited about XBRL.

Two reasons why XBRL will move to prime time in 2016

  • # 1: High Frequency Trading killed the Day-Trading business. When speed of trading is the game, computers will always beat humans. When you work on small gains every day, the front running done by HFT hurts. So there are a lot of retail investors looking to find the next game, looking for new ways to make money in the stock market. The winners in the market will now be stock-pickers who can go either Long or Short based on fundamental analysis.
  • #2: The XBRL rollout on US stocks is now complete. So we can move from the production phase of XBRL (all costs, no benefits) to the analysis phase (lots of benefits, very low costs).

XBRL is one of our Top 10 Fintech Predictions for 2016:

“XBRL will start climbing out of the slough of despond but won’t be recognized yet as moving into the plateau of productivity.”

Three reasons why XBRL fell into the slough of despond

It has been 7 years since XBRL was mandated by the SEC and got public attention. That is too long in our attention deficit world. We see the same thing with something as complex as Bitcoin, which is also about 7 years old, that is losing attention because the results have not been quick enough. There are also three reasons specific to XBRL why it fell into the slough of despond:

  • # 1: XBRL is a complex story that requires an understanding of both technology and accounting.
  • #2: The XBRL production process took longer, cost more and was more error-prone than forecast. In the production phase it was all costs and no benefits. It was all problems and no results.
  • # 3. There have not yet been any success stories for journalists to write about.

Why you will continue to hear these negative stories

XBRL democratizes fundamental stock analysis in the same way that PCs democratized computing and social media democratized HTML.

When you can compare the cash holdings across 100 companies with a single entry in your spreadsheet, or see quarter to quarter revenue growth for every company in the index that you devised, do you need mega brokers and their me too reports churned out by freshly minted MBA graduates in an outsourcing center somewhere?

That is disruptive to the current financial value chain (aka Wall Street). Those threatened by disruption always point out the flaws in a new technology and in all new technology there are plenty of flaws (XBRL is no exception).

When you see issues with XBRL, remember how klunky the Internet was in 1994 (cue sound of a screeching dial up modem). When something promises to automate a task 100% and only achieves 90%, it is easy to point out the flaws that meant 100% was not achievable. The reality shouting at us is that 90% automation is game-changing. The firms who mastered the business of deploying people to do things manually (i.e the threatened incumbents) have the money and the motivation to convince you that this will never work.

Those who have been toiling in the XBRL world know that the data is still not totally reliable. So, they will be defensive when they hear the incumbents talk about all the problems with XBRL. True there are problems with XBRL, but it is still way better than what we have now (manually cutting and pasting from HTML into Excel). To the retail investor, finding a data problem is an opportunity. They have the time. If you use XBRL to screen 100 stocks based on some parameter and end up with 3 that “look interesting”, you can easily eyeball those 3 on your short-list to spot where the data errors might be or why a stock that looks crazily undervalued based only on the numbers is still a lousy stock to buy. Automated analysis of the basics enables more time for value added analysis (“Alpha” in Hedge Fund speak).

New technology usually gets a foothold in a market that has major pain where the market participants will over look something klunky because the need is so great. This leads us to looking at the “small cap hell” pain point.

Getting out of “small cap hell”

When I was writing the SAAS Insights Report in 2010, only Big Caps (over $2bn market cap) had to report in XBRL. Now I can get all the SAAS stocks in XBRL; or I can get all Biotech, Oil, Property, e-commerce stocks, financials/Fintech. I can get whatever is the focus of my research. Then I can set up automated screening programs to find the investing gems (long or short) in those markets. Those screens are not just based on something as crude as price or PE or PSR. They are based on data that you can only get by digging deep into the 10Q statements and – this is what matters – knowing what you are looking for because you understand the market that you are researching.

Today, Small Cap stocks are in “Small Cap Hell”. When your market cap is below $2bn, mutual funds cannot buy your stock unless the Fund is specifically mandated to buy Small Cap Stocks.

It is worse than that. Since ETF trading took off, fundamental research declined even more. About 75% of stocks now have no research. Only Mega Caps or recent IPOs get research on a consistent basis.

When everything changes, one law that remains constant is the law of supply and demand. When all of the research supply goes to a few stocks and the demand is screaming from the rest, there is a window of opportunity.

So, XBRL needs stories of a couple of geeky young Warren Buffet like investors to make a fortune this way. That will get them onto CNBC or Fortune or Business Insider. A good reporter with a nose for the story will ask “how did you do it?” and that is where the newly-rich investors will go against their best interests and reveal that XBRL analysis tool they used.

Investors win in inefficient markets. Small Cap is an inefficient market. Here is a report from Credit Suisse that shows why trading in Big Caps is a mugs game for retail investors, but how there are big opportunities if you can quickly find the undervalued/overvalued small cap stocks. The TL:DR summary of that Credit Suisse report:

“Shares in small and mid cap companies are, for the most part, less liquid than those of large caps. The typically higher risk of an investment in small and mid cap stocks is reflected in higher risk and liquidity premiums and has a positive effect on performance over time.”

In other words, Small Cap stocks are ideal hunting ground for individual retail investors. With the small sums they trade, the lack of liquidity is less of an issue.

Qui Bono and Qui Amisit?

Translation – who wins and who loses?

  • Private Equity Funds – lose a bit. They are currently doing very well in an inefficient market. They can afford to have analysts screen for small cap value and take them private. As other investors figure out how to do this – meaning the market becomes efficient and small cap bargains go up in price – the easy arbitrage will be gone. PE funds have many other ways to make money; this is just some easy-pickings that will go.
  • Small Cap Funds – gain a bit. Their existing holdings will go up in value. They will have to work harder to find bargains in future but as that is what they do for a living, they will figure out how to add value in the new value chain.
  • Me Too Research – lose a lot. Investors will demand a lot more value and insight. Me Too Research, even with lots of fancy charts and visualization, will be downgraded.
  • New investing services – gain a lot. There is room for a new Yahoo Finance (free, ad supported) or a new Bloomberg or a new (pick your favorite subscription based service). This is a high risk/high reward game that is subject of a future Daily Fintech Research Note. The winners will be distribution channels for the Micro Research Firms (see below).
  • Micro Research Firms – gain a lot. This will be like the blogging revolution. Suddenly everybody can be a research firm. All you need is insight; the mechanical part is automated. I call this latent alpha. For example, somebody with decades of experience as an oil geologist might have valuable insight into the oil business, but lacked any way to monetize that insight.
  • Jane Q Public – gain the most. Some will become Micro Research Firms. Most will simply invest smarter. This is how the stock market was supposed to work. This will be a democratized stock market that will help to reduce inequality. Wall Street is based on information asymmetry. It is like a car dealer with all the data. That era is coming to an end.

Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech. Bernard Lunn is a Fintech thought-leader.

Riskgenius – the Google of Insurance Policies

By Rick Huckstep

In the world of commercial insurance, brokers and agents are reviewing policy agreements in their evenings and at weekends. These contract reviews are consuming masses of labor, are time consuming and open to error. This isn’t a small cost to the industry either. The 150 largest Independent Agents alone employ around 500,000 people with half of them in admin roles. There has to be a tech solution to this…let me introduce you to Risk Genius – the Google of insurance policies!

The issue is this. Insurance professionals across the world are struggling with contract reviews.  And this inefficient process is impacting underwriters, agents, and brokers alike.

The industry is full of anecdotes of professionals reviewing contracts at the weekend whilst they’re “watching” their kids at soccer school. Or of agents reviewing contracts for customers in their travel time between workplaces. And of product underwriters who simply do not have the time to review all of the contracts they are sent.

Let me put this into context with a simple Use Case

Today, commercial insurance brokers and agents need to review insurance policy agreements when advising clients on their insurance requirements. They do this by comparing different policy agreements and documenting the comparisons in a ‘like for like’ format in a spreadsheet format.

This is a manual review process. The agent or broker often does this as a side task, out of office hours, at home in the evenings or the weekend.

And here’s the rub. It’s a thankless task that is time consuming, repetitive, and open to human error. It also relies heavily on human decision-making in less than perfect circumstances. This is cause for concern for insurers from the associated risk and exposure of giving bad advice based on a poor contract review process.

This is where RiskGenius comes in.RGlogo_988p_Web_Mixed_Stacked

To tell me how they plan to transform the commercial P&C industry, I Skyped with co-founder and CEO, Chris Cheatham. Better known on social media as the ‘Dr Dre of the Insurance Industry”, Chris is an attorney by trade with a love of rap music, science fiction and machine learning technology. Chris has already established a successful startup in ClaimKit, a collaboration platform for claims management in the surety, insurance and legal space.

Over the course of an hour, Chris explained to me how he and his co-founder, Dan Burchett designed and built a platform that applies machine learning to the review process for commercial insurance policies.

“Its been a tough nut to crack and taken a lot of hard work and effort”, according to Chris, who gives all the credit for the technology solution to Dan, who’s more Tony Stark than your typical CTO.

What we do is take an insurance policy and load it up onto the RiskGenius platform. First, it is analyzed and indexed, which takes a minute or two. We’ve written algorithms that can break down and understand an insurance policy. And, just like Google, RiskGenius will look at the content, organize it and make sense of it. We use the algorithms to categorize and structure the content of the policy documents so that they can be reviewed. The output is a simple to understand and review policy, and the user can export out results in a spreadsheet format.

“We’re going through the same process as the agents. It’s just that RiskGenius is reading the text faster and applying more rules using machine learning technology.”

The purpose of RiskGenius is really clear. This is a solution that benefits the Insurance agencies.

As Chris told me, “a key challenge for insurance agents is sales. How do they go get business in a competitive marketplace?  RiskGenius is their best tool for fixing this. First, we take the pre-existing policy. By reviewing it with others, the agent can see the gaps in the cover and the weaknesses in the policy conditions. Now, the agent can explain these gaps and help the commercial client to get the right cover for their commercial business. Up until now, this has been time consuming. But with RiskGenius, the sales agent can process the policy very quickly and then go and explain any shortcomings.”

And this is not the end of it, because once a contract has been indexed and cataloged then the fun starts. Now agencies and brokers can start to build libraries of policy agreements across their client base and within the firm. It is common for many variations in policy wording for the same terms and conditions. These are often unnoticed and hard to review in their entirety across the firm. With RiskGenius, agents can comment on and review multiple variations of similar clauses with clients and with the agency to establish the most favorable for all parties.


RiskGenius is about to go live in February and this week they secured $1.8 million in series A fund raising from lead investor Flyover Capital (reported here on Startland News, Kansas City’s Home for Innovation News).

The approach they take will significantly increase the speed, consistency and accuracy of the contract review process.

Quite simply, RiskGenius are using technology as an alternative to hard labor and in so doing; they reduce the contract review process completion time from days to minutes.

As Chris says, “Can you imagine why anyone would manually review contracts in 5 years time?”

The author, Rick Huckstep is an InsurTech thought leader. Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech.



Regulatory & market pressure forcing transparency on equities research


This is Part 1 of a 2 Part Research Note, which describes how regulation and market pressure is forcing transparency on equities research and how that is leading to cost pressures on the research business.

In Part 2 on Friday, we will look at possible technology solutions and business model innovation that can bring lower costs through automation and open up new market opportunities, in order to alleviate pressure on the bottom line.

Who pays for equities research? 

Historically it was the sell side that paid for research. That got hammered after the Dot Com bubble burst, when it became clear that there were too many conflicts of interest if the sell side paid for research (investment bankers were publishing sales pitches disguised as research).

Then the buy side started paying for research. This was better, as the buy side was not conflicted and they benefited from good research. However this was not done in a transparent manner. Funds paid via commissions on brokerage fees. Well actually the Fund’s customers paid, which is an issue that the regulators are now focused on.

Regulatory Pressure

The European Commission proposed that asset managers “unbundle”, meaning that they have to report how much they are spending on third-party research via Commission Sharing Agreements (CSAs) with brokers. The UK’s Financial Conduct Authority (FCA) has suggested that it wants to ban CSAs.

This now forms part of MiFID II’s clampdown on third-party inducements and time is running out. This comes into place at the start of 2017.

This is likely to go global very quickly if it happens in Europe, because the admin burden of reporting in different ways in different jurisdictions is too hard. In other words, an American or Asian Fund that wants European investors may offer the same transparency to their American or Asian investors. In the end, market pressure from investors will replace regulatory pressure. Once investors get educated about fees, they demand lower fees.

Future Scenarios

We envisage three future scenarios:

  • Scenario # 1. Asset Managers bring more research in-house. If Asset Managers want proprietary research for a competitive advantage, bringing research in-house makes sense. If their customers refuse to pay for research and they have to pay for research out of AUM, they might as well budget for research as part of their core operating expenses. This will make them highly motivated to look at automation as a way to cut costs.
  • Scenario # 2. New micro research firms emerge. New technology and new low cost digital distribution channels will enable these new micro research firms to come to market at very low cost and thus offer lower cost high quality research services. Some will be almost in-house by offering exclusivity within domains (accentuating Scenario # 1). Some will offer free high quality research as part of a content marketing strategy to win clients (accentuating Scenario # 3).
  • Scenario # 3. Free research gets better. Free research maybe monetized by advertising (the old model before Ad Blockers) or higher value services (using the open source to Freemium direct revenue model). The free layer will gradually encroach in quality terms on what is now a paid for service, raising the bar for everybody. The new micro research firms will both produce some of this free research and will also use the free research from others to keep their costs lower.

It is likely that the future will bring a mix of all three scenarios and that new value chains will form around these scenarios.

The future scenarios will be enabled by new technology and business model innovation that enables new players in the value chain to a) reduce cost via automation b) open up new markets that were too price sensitive earlier. We will address this in Part 2 on Friday.

Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech.

Structured products & Securitization moving online


By Efi Pylarinou

“Structured finance isn’t dinner table conversation for most people — and the terminology, market dynamics and ecosystem can be imposing”                                 Hyung Kim, Co-Founder of Ldger

Structured products are one of the tools used in financial markets to re-allocate risk and create customized payoffs that are suitable for each investor class. Pensions funds and hedge funds, are naturally positioned in different areas of the risk return space.

A structured product is a derivative product. You can think of it as a “machine” that transforms a typically large pool of cash flows into a few different categories of some newly created instruments. One simple example, is pooling credit card cash flows and then creating 3 new buckets in which you allocate the pool of cash flows. The “top” bucket is higher credit and gets paid first (lower yield), the second gets paid once the first one is paid off (of course higher yield), and the third one are the residual cash flows. There are so many variations of these structures that they cant even fit in one fat book.

There are two main areas for Fintechs to offer value in the structured market area. One relates to more transparency in all the stages of the product cycle and the other to improving the structuring process. Structured products are highly customized with a wide range of underlying assets and lots of entities involved. Inefficiencies exist in:

  • Discovering the structure that is “optimal” or suitable
    • For example, I have a view on oil, what is the best structure to express this view
    • Or, I want to hedge an exposure, what is the best structure to attaint this
  • Issuing a structure
    • For the asset holders (owning a pool of cash flows) who want to replenish capital
    • For an asset manager who wants to own a portion of a homogenous pool of cash flows
    • Too many entities involved (issuer, primary & backup servicer, paying agent, trustee, custodian, rating agency etc)
  • Pricing and Liquidity
    • A transparent structure with an improved mark to market and risk valuation mechanism of the underlying poll of cash flows
    • A reasonable bid offer spread of the structure

There are two Fintechs in the broad structured product space. Contineo who is focused on equity linked structures in the Asian market, which has traditionally been a large user of structured products due to local regulations. It is backed by industry lead names, like JP Morgan, Barclays, Goldman Sachs. Contineo aims to deliver to the players (B2B) in this market, Buy side and Sell side, a win-win tool. It is like the Algomi of structured products. The former aims to solve the fixed income conundrum and Contineo, the structured products conundrum. Quotip is a Swiss Fintech startup, tackling the same problem for the Western markets. Quotip was recently, selected for the Accenture Fintech Innovation Lab in London and is not in the dis-intermediation business but rather addressing a complex mutli-issuer and mutli-asset market that needs to be revived. It offers a platform for structured product idea generation, request for quote, and audit/life-cycle management, as explained in the Forbes article “More collaboration than disruption in Accenture’s London Fintech Lab”.

Two Fintechs also in the structured product space but strictly in securitizing assets from the new lending marketplaces, are PeerIQ and Ldger. This niche focus, adds more complexity because the underlying cash flows are sourced from unregulated entities and through a direct match making process of borrowers and lenders. The market is not yet comfortable with current risk assessments because there isn’t enough history to extrapolate default rates.

PeerIQ is positioned as a P2P credit risk analytics platform and loan data provider in the space. They are developing benchmark analytics and tools like the Marketplace Lending Securitization Tracker, that are essential to institutional investors wanting to get involved in the space. Their mission is to be an enabler for improved secondary market conditions in the origination space and to offer more transparency and understanding that will lead to an increase in the volume of securitized deals.

The backers of this startup are from the incumbents (e.g. John Mack, Vikram Pandit, and Arthur Levitt, to name a few as mentioned in “Bold-Faced Wall Street Names Back Loan Data Startup PeerIQ).

Ldger is also a startup founded by lawyers that aims to be the Lego land for securitized deals with building blocks only from lending marketplaces. “Build your own securitization” as JJ HORNBLASS dubs Ldger in “Why Marketplace Lending Is Set to Boom”. Imagine a platform that one can build customized tranches from pools of cash flows originating from lending marketplaces. The aim is not to facilitate lower denomination deals to happen. On the contrary, the aim is to enable larger deals to happen. Ldger wants to be there as the deal flow, increases which is one of the prerequisites for a decent securitization deal (i.e. to ensure that the pool can be scalable and with a long life). Ldger wants to lower the cost of the process, make it faster and with wider distribution. The deals that will be custom tailored on their platform will be transparent and audible. Ldger will integrate cash flow servicing and reporting. Ldger is inviting origination platforms to integrate their APIs to the Ldger platform.

Like a child’s Lego game, securitization involves many different players and can create various outcomes even though using always the same blocks. Regulation is challenging for structured products and even more for structured finance. All Fintechs involved in this space are helping regulators and buy/sell side in creating a safer, larger, more liquid and more mature market.

Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech. Efi Pylarinou is a Digital Wealth Management thought leader.

Who is afraid of P2P securitization?

By Efi Pylarinou

In my last research note I discussed the role of WebBank in the triangle of Lending marketplaces in the US. The function of this regulated entity is clear and brings to the forefront the roles and responsibilities left to the unregulated Lending platforms.

Lending marketplaces are predominately accessing the creditworthiness of the borrowers and servicing the loans.

These two important functions are not as simple as they may seem. Lending platforms have been continuously improving on both fronts and IMHO the standard (algorithms, data and process used for creditworthiness & servicing processes in case of delinquencies and defaults) has increased. This makes it more difficult for all those flirting with the idea of launching yet another lending platform and salivating to get institutional money involved in funding borrowers (still a large underserved market). In addition, the overall online lending market has predominantly been catering to the higher end of the credit spectrum because of course, it is the safest entry point and large enough up until now.

Now that the lending market has enough deal flow, the market is looking for the next more mature stage. It is no other than the traditional securitization process, which remains “naughty” but at the same time is a process that serves many purposes. First and foremost it transforms illiquid assets (the P2P loans) into marketable securities (the tranches of the securitized deal); it provides access to a new asset class (risk/retrun payoff) for asset managers, pension funds, and wealth managers; it lowers cost of funding for the originators; it replenishes capital. The risks on the other hand, are all hidden in the details (the features of the underlying pool of assets; the opaqueness of the servicing of the pool; leverage, etc).

Given the painful experience of the 2008 blowup that was triggered from such deals, one would think that there is a collective experience that will be applied to such mechanisms this time around. Ratings agencies, Servicers of the pools of loans, Trustees, Custodians, paying agents, underwriters, and end investors; are all probably wiser this time around. The higher standard of transparency again instigated by a self-regulatory culture from the large Lending marketplace platforms, are also helping the cause.

Screen Shot 2016-01-25 at 9.06.33 AM

Source: Investopedia CLO definition

Most of the securitizations deals over the past 3 yrs had been private placement deals and not noteworthy in size (ranging from $30mil-$100mil typically). The tipping point was the first rated and large size deal by SOFI. Even though the market’s first choice wouldn’t have been student loans as the topic pick for a pool of underlying loans, it set a precedent.

The other two large and rated securitization deals are from Citigroup and Blackrock. Their babies respectively are: the Citi Held for Asset Issuance (CHAI) deal and the Consumer Credit Origination Loan Trust (CCOLT) deal. The latter is an SPV created by Blackrock for the purpose of this deal. My focus is more on these two deals because they are the first rated ones with a heavy involvement of a regulated and rated financial institutions (not only as underwriters but custodians, or paying agents, etc).

Both deals are similar in many ways (detailed data can be found in “Comparing CHAI to CCOLT” by PeerIQ):

  • Size: CHAI $420mil – CCOLT $306
  • Consumer loans mostly 3yr average and avg. borrowing rate 13%-14%
  • FICO: slightly above 700
  • Number of loans $25k-$30k with average loan size $11k

The significance in these deals is in the fine print which defines delinquency and default procedures. The CHAI deal obtained an A3 rating for its Class tranche (whereas CCOLT has longer Weighted average life Class A tranche with a lower rating Baa3) mainly because the Backup service provider in the CHAI deal is a rated entity (Citibank). The CCOLT has First Associates as the backup service provider, which is a 30yr old business and is the fastest growing and largest third-party consumer loan/lease and backup servicer in the United States with $7billion under management.

“Who is afraid of securitization?”

Everybody says “yes” to be safe (not because they necessarily thought about it) from the originators of the underlying loans, the underwriters, to the rating agencies and the investors. The fear is coming from being burnt and wanting to be compliant (the new norm) which makes all stakeholders more cautious and conservative.

“Be afraid of what you don’t know”

These are not unchartered waters and Wall Street veterans are out there to deploy their expertise to make securitization work this time around. The 4th quarter of 2015 (as reported by PeerIQ in their Marketplace Lending Securitization Tracker Q4) saw $2.7bn in securitization issuance. This is five-fold from the 2015 Q4 issuance ($0.5bl), with market conditions in credit markets not all favorable during this quarter (widening of credit spreads).

Roughly 43% of the 4Q deals were rated (mostly by Moody’s). Consumer loan pools are twice as much as student loans. The growth will continue as long as there is no misstep in the servicing, in the borrower selection practices and of course, no black swan that triggers defaults that weren’t priced in.

The securitization market first needs to grow in a similar direction as the CHAI and CCOLT deals. Ideally, the market needs more consumer loan deals and also some SMB securitization deals. Funding Circle and Zopa, for example, need to get involved and OnDeck deals need to get rated. Such growth in both verticals (consumer loans and SMB) can pave the way towards deals structured from the Lending platforms themselves (similar to the SOFI deal).

Daily Fintech Advisers provides strategic consulting to organizations with business and investment interests in Fintech. Efi Pylarinou is a Digital Wealth Management thought leader.

Swiss Vollgeld initiative could end Fractional Reserve Banking

Safety comfort

It was an odd Xmas present to the global banking industry. On 29 December headlines were announcing that:

“Switzerland to vote on banning banks from creating money”

The Swiss referendum would strip commercial banks of the ability to create money using Fractional Reserve Banking. Banks would have to back loans 100% with reserves. As an article in Stratfor pointed out, this has implications globally and

“could shred core business assumptions that have underpinned the banking model over the past three centuries.”


The idea of what the Swiss call Vollgeld (translation is “full money”) was first outlined in a 2012 paper from the International Monetary FundIceland is also considering this, but Iceland is tiny compared to Switzerland. This research note look at Iceland as one of the alternative Fintech Capitals, which is # 84 on the Global Financial Centers (GFC) index and tiny in GDP terms. So any move they make can be dismissed as irrelevant by the banking industry.
However if Switzerland makes the move it cannot be dismissed as a blip. Zurich alone ranks # 7 in GFC and Geneva ranks # 13. Switzerland is a global leader in Wealth Management.

Vollgeld would be a totally radical move that would hurt traditional banking in Switzerland in the short term, but it could vault Switzerland into a leadership position longer term. If Switzerland does it, other centers will have to follow. This is a case of disrupt before you are disrupted. Together with the move by Xapo from Silicon Valley to Switzerland and the growing crypto expertise in Zug, this could put Switzerland on the Fintech map.
How the people will vote is obviously unknown. Most bankers will warn of bad results, but one can see a populist case forming that citizens are fed up with bailing out banks and that Vollgeld eliminates systemic risk.

Some forward-thinking bankers and Fintech entrepreneurs may also make a case within the Banking industry along these lines:

  • The transition from creators of capital to conduits of capital is already happening in the lending and equity crowdfunding marketplaces. So why fight the inevitable? Get ahead of the trend aka disrupt before you get disrupted.
  • The  line of business least impacted by Vollgeld will be Wealth Management, where Switzerland excels. Investors will pay directly for having assets protected. This maybe called negative interest rates today. It might simply be called direct fee for service – pay to have your assets secure and protected.
  • If banks are paid to store assets, banks can also offer to lend money based on these assets as collateral. This is different from fractional reserve banking because the risk is the individual customer’s risk. There is no systemic risk.

This seems like an odd move for Switzerland given how important Financial Services is to the Swiss economy (over 10% of GDP and 5% of workforce).

Maybe they are seeing the Fintech writing on the wall that banking will return to a utility model, a subject I covered in an earlier post.

The implications globally – both for incumbents and startups – will be profound.

Will a referendum pass and when?

In Switzerland’s direct democracy, a referendum can be held if a motion gains 100,000 signatures within 18 months of launching.

What will be the implications if it passes?

This will move Banking to a utility direct revenue model. Banks will charge directly to store (custody) your assets whether they be cash or securities or gold or bitcoin or anything else. There will be zero systemic risk and no need for taxpayer bailouts or government insurance schemes.

Bankers everywhere – not just in Switzerland – will have to track Vollgeld and plan for that as one possible future scenario.

Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech.

What’s the point of InsurTech (and what are the incumbents doing about it)?


By Rick Huckstep

Earlier this week, a packed house attended a TechUK meeting in central London under the heading “Insurance Disruption”. The stage was shared by two insurers, three startups and a global SI. This was a coming together of the established and the emerging worlds of insurance and InsurTech. The subject: digital innovation and the transformation of the insurance industry.


Deconstructing Insurance

InsurTech will replace digital on the CEO agenda”.

A bold statement to open the meeting and arguably already true. Present tense not future!

The meeting was held at TechUK, a body that represents the UK’s technology industry. And it was excellently marshalled by Nigel Walsh, Head of UK Insurance for Capgemini.

The audience was predominantly from the supply side of the insurance industry – vendors, consultants, suppliers. And they had gathered at the TechUK offices just off Fleet Street to hear the views of innovators from established carriers and emerging startups in this world of InsurTech.

For summaries of the meeting, including photos from the stage, go here for Nigel’s, and also here to read the perspective from Greg Brown, Founding Partner at Oxbow Partners.

In the “Established” corner was Martin Pluschke of Ergo and Serge Taborin of Aviva Garage. Both facing the challenge of how to bring digital innovation and transformation to a large and complex organization that is massively hampered by legacy and a culture of “this is how we’ve always done it!”. These challenges are well reported in this excellent 2015 report from KPMG, subtitled, ‘The insurance innovation imperative’.)

Of course, the established insurers do have a few things working in their favor, such as plenty of resources, money, experience and, above all, customers…16 million of them in Aviva’s case!

In the opposite corner and representing the “Emerging” world were three startups from the Startupbootcamp InsurTech cohort that started two weeks ago – RightIndem, massUp and Fitsense, featured here on Daily Fintech last October. (If you go to Greg’s post, he includes a short profile on all three startups.)


Digital is in the DNA of the startup

Whilst they might be short of a few bob and hours in the day, the startups are free of legacy and able to focus totally on the customer experience. They also “get” digital from the outset. These are common themes I have seen from interviewing over 50 InsurTech startups in the past year.

As Nigel Walsh said in the FT on Monday; “Customers are getting more savvy. Expectations have gone up but insurers are not meeting those expectations.”

It’s a point well made without much resistance from the industry. But it isn’t all bad for the established players. With the high cost of regulation being a significant barrier for new entrants, insurance is far less likely to experience uberization than many other industries.

And to quote David Moschella of the Leading Edge Forum in his report Disruptive Innovation comes in Waves; “Technologies that sustain incumbents can enable just as much societal progress and change as those led by new firms.”


Clearly, the notion of eating your own lunch doesn’t effect the emerging players, but it certainly does for the established. Rather timely, I noticed this comment today in an article on Pymnts.Com. It was made by American Express CEO and Chairman Kenneth Chenault at a retail conference last week in NYC.

He said; “you need to be focused on customer needs,” while embracing a process that may even include “cannibalising yourself.”

The fact this is from the boss at Amex is irrelevant; the point is that established players across many industries should accept cannibalisation as an intended outcome of their innovation agenda.

Which is why you see insurers dividing themselves into “run the business” units that are completely separate from “build the business” units. This is a strategy that removes the burden of legacy for those who are tasked to build new ways of working. And an invitation to eat their own lunch!

Investors, Innovators and Transformers

When I look at the incumbents, I see three different strategies for embracing the InsurTech world of the startup.

Figures just released from CB Insights reported that investment in InsurTech in 2015 was $2.65bn. And no doubt it will be reported as high, if not higher in 12 months time. One group of investors contributing to the figures is the established insurance carriers themselves.

I call these “The Investors” and they include the likes of Mass Mutual Ventures and Commerz Ventures who are investing directing into InsurTech startups. This is a VC model where the investments are targeted at insurance businesses.

Then we have “The Innovators”. These are the established insurers who are getting involved in the startup landscape through accelerator programmes, bootcamps and hackathons. They seed their own innovation people directly into the startup support ecosystem, mixing with the emerging InsurTechs outside the walls of the established insurer.

They include carriers such as Munich Re/Ergo who are active at Startupbootcamp and the soon to start Mundi Labs insurance accelerator in Madrid (where I mentor on both programs, excuse the shameless plug).

The Startupbootcamp Executive in Residence is Martin Pluschke, mentioned earlier, and he is one of the most enlightened people I know from the established insurance world. He really gets digital innovation and is an asset to both Ergo and SBC.

Also in this category are carriers such asDirect Line Group and  Generali, with their Innovation Challenge in collaboration with Microsoft. Here they focus on three defined market problems and invite startups to pitch solutions to solve them using the Skipsolabs platform.

Finally, we have “the Transformers”. This is the class of established insurer that creates the digital innovation lab approach inside their own walls. Innovating from within, insurers are investing in their own digital innovation and transformation capabilities by hiring expertise from the outside.

The defining characteristic of the Transformers is that they give the innovation team a direct line to the CEO’s office. The corporate governance process and policies are (largely) set aside so that the innovation team can work unencumbered by internal bureaucracy.

A great example is Aviva, where the 5 person leadership team for the Digital Garage’s in London and Singapore report directly into CEO Mark Wilson.

Of the other major global insurers classed as Transformers, I include;

For the final word on this, I quote Dr.Thomas Blunck, member of the management board of Munich Re;

We can’t wait for the structural changes to occur before we start moving; we need to address these changes now if we hope to offer the business new growth opportunities over the next 5 years.”

For me, this quote sums up the call to action agenda for the insurance incumbents in the digital age.

The author, Rick Huckstep is an InsurTech thought leader. Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech.