Open Finance: An Alternative to Traditional Financial Services
What is Open Finance?
*Updated November 2020*
Also known as DeFi (decentralized finance), open finance can be defined as financial products and services built on public blockchains. While Bitcoin itself is technically considered a form of open finance, a new crop of open finance applications largely built on Ethereum are now at the forefront of innovation in the crypto and blockchain space. These applications offer a glimpse at how the financial world might look if it were decentralized and truly open.
With open finance, there are fewer restrictions to participate and, with the digitally-native nature of the applications, offered products and services extend cost and time savings relative to similar offerings provided by traditional brick and mortar offerings.
Open finance applications can offer these benefits because the core innovation is a trust layer that is inherent to the software development itself. This innovation is revolutionary because it makes financial services “permissionless.” In the same way that there’s no need to get your account approved if you want to send and receive Bitcoin, using open finance tools, anyone can, in theory, get access to more complex financial services. Importantly, this also lowers the barrier to entry for new financial service providers, thereby improving the competitive landscape and further driving innovation.
In this post, I describe open finance applications for lending, forecasting, exchanging, derivatives and data collection, and their business models. Note: all areas of open finance aren’t covered.
Lending is an extremely important part of any economy. With effective lending, economies can increase their gross domestic production because capital is allocated to those who aim to spend it productively. This in turn can boost economic output. Today, banks most commonly act as a bridge between those willing to lend surplus money to earn interest, and those wanting to borrow it to spend productively.
While this sounds simple, lending has become increasingly complex. Individuals seeking loans or wanting to lend, face convoluted institutional lending requirements. These requirements have the effect of limiting both who can create financial products and who has access to them. Primarily access is limited to well-capitalized institutions and people in developed countries. Add in opaque lending agreements, inefficient credit scoring methodologies, complex lending on-boarding, and excessive fees, and you have an area of finance ripe for disruption.
Open finance lending applications have recently seen a rapid increase of popularity. These applications directly connect borrowers and lenders without any intermediary, offering a range of improvements over current traditional practices. Improvements include global access to lending and borrowing opportunities, transparency of fees, new credit scoring formats, fast approvals, and programmatic lending agreements.
There are few players handling most open finance lending activities although it seems to change frequently based on incentives their offer for users to lend assets.
Compound is a decentralized finance application, built on top of Ethereum, that has created incentives to encourage user participation. This is achieved firstly with their autonomous interest rate protocol and secondly with the COMP governance token.
At the protocol level, Compound brings together different participants with opposite but complementary motivations. They include suppliers of tokens and cryptocurrencies seeking yield (who can earn interest by depositing digital asset collateral) and borrowers of tokens and cryptocurrencies seeking utility and/or leverage (who pay interest in exchange for borrowing).
Compound uses on-chain smart-contracts to custody tokens and cryptocurrencies. Interest rates are determined algorithmically by a protocol. These innovations effectively remove centralized custodianship and decision making from lending in Compound. The benefit to participants is that using their own private assumptions, they can estimate forward interest rates and decide for themselves whether supplying and/or borrowing makes sense. Of course, Compound is entirely permissionless. To use it, all you need to do is connect a Web 3.0 wallet (which is anonymous) and send transactions to the Compound protocol.
Maker is another lending protocol. With Maker, anyone can use approved Ethereum-based assets to generate DAI, which is a cryptocurrency pegged to the USD ($1). To generate DAI, you create a collateralized debt position (CDP) by depositing approved Ethereum-based assets into a smart contract as collateral for a loan. Once the CDP holds the assets deposited by the user, the user can then generate a defined amount of USD value in DAI.
The stability of DAI is ensured in part by over-collaterization of the loans that are used to create it. When a user ties up assets to create DAI, they are getting a loan for DAI, which they can use as they wish. The point here is that there are new models made possible by decentralized open finance which create new financial utility for participants.
New open finance applications are aggregating liquidity outside traditional distribution networks. Popular decentralized digital asset exchanges (DEXs) such as Uniswap and Balancer use smart contracts to facilitate trading and build market depth.
In addition to being permissionless, a key difference between open finance exchanges and traditional ones, is that open finance exchanges do not keep custody of customer assets. Instead, open finance exchanges consist of a series of smart contracts that facilitate and automate trading. People who put funds into the smart contracts are effectively trading assets on a peer-to-peer basis (without intermediaries). While centralised exchanges are susceptible to bankruptcy, in part due their status as honey-pot targets for hackers, the key risk for decentralised exchanges is the integrity of the code that governs them. And while the business practices of centralised exchanges are often opaque, the code that governs DEXs is transparently verifiable. This means that, at least in theory, a DEX with perfect code would be immune to the risk of bankruptcy.
Not taking custody of assets can be considered an attractive feature for many DEX users. On the other hand, it directly contributes to a problem that has long prevented the growth in adoption of DEXs: lack of liquidity. While centralized exchanges leverage their access to users’ assets to engage in market making activities that reduce trade slippage, DEXs traditionally had no way to do this. So, while it was fast and efficient for traders to move in and out of positions on centralized exchanges, doing so on DEXs (with a layer-2 or scaling solution) can be slow and potentially costly.
Slippage results in token purchasers experiencing a capital loss in their purchase order for a token. This occurs in shallow liquidity pools where a token does not have enough depth to satisfy the order, and thus the price slips during the transaction filing.
Uniswap is perhaps the best known example of an automated market maker (AMM), which is a class of DEX that relies on mathematical formulas to set the price of a token. Rather than maintaining a list of buy and sell orders and matching buyers to sellers like in a centralized exchange, AMMs use smart contracts to govern trades. This is similar to swap services like ShapeShift and Changelly, but there’s one key difference: the method for creating liquidity. While ShapeShift, as an example, is a company that uses its own reserves to provide liquidity by acting as the counterpart to trades, AMMs offer a way to build distributed liquidity pools that anyone can contribute to.
Uniswap’s protocol incentivizes people to add liquidity to the exchange by distributing the 0.3% trading fee to liquidity providers. To become a liquidity provider for a given trading pair on Uniswap, users lock up the equivalent value of both sides of the pair into a liquidity pool. For example, if ABC token is worth 0.01 ETH, a user would need to lock up 100 ABC tokens and 1 ETH. This is done by sending both assets to a liquidity pool smart contract. That smart contract then automates payments (0.3% of all trades made on the pair) to all pool contributors based on the proportion of the pool they represent.
From a trader’s perspective, when you initiate a trade, you are sending one asset into the liquidity pool for that trading pair, and receiving the other asset in exchange. A mathematical formula determines how many tokens from the other side of the pair you receive in return. The formula is a hyperbola (approaching infinity and zero at its extremes), meaning the slippage rises exponentially as trade size increases. Trading pairs with larger liquidity pools can handle larger order sizes with minimal slippage.
Balancer, another type of AMM, provides a good demonstration of the rapid innovation that is occurring in the DEX space. Balancer integrates several features that differentiate it from Uniswap. The main difference is that Balancer liquidity pools may consist of more than two tokens, whereas Uniswap liquidity pools may only consist of two. Also, the weight of each token in a Balancer liquidity pool may be customized, whereas the initial weighting of liquidity pools in Uniswap is an even split between ETH and the paired ERC-20 token.
While trading on Balancer may involve a higher amount of slippage, Balancer’s innovations make it easier for people to earn fees on their Ethereum-based idle assets. This is because, thanks to the above-described features, users can deposit their entire portfolios into Balancer’s self-rebalancing liquidity pools and earn fees as other users trade against their portfolio. With Balancer, anyone can effectively create their own self-balancing index fund or invest in someone else’s.
Derivatives provide stability to financial market participants. At their core, derivatives are used to transfer risk from one party to another. One party wants to hedge their risk, the other wants to be exposed to risk. The hedging party will neither lose nor gain during the derivative contract, while the party exposed to risk stands to lose or gain.
As it stands, parties entering into a derivative contract rely on centralized intermediaries to enforce the contract. This has benefits and drawbacks. One drawback is that derivatives are not generally inclusive financial instruments.
Open finance applications can remove intermediaries. For example, take dy/dx. Their protocol allows anyone to create, issue and trade decentralized derivatives. By democratizing access to derivatives, dy/dx offers users an efficient way to enter into risk mitigating financial instruments without compromising on security.
Like decentralized exchanges, the main difference with decentralized derivatives relative to their centralized equivalent is there is no clearing house verifying transactions. The parties to a derivative contract retain custody of their funds, cutting out the middle-man.
Decentralized derivative platforms make it possible to create a contract around any position (longs, shorts, etc.) or receive real-world asset exposure. For example, using the Universal Market Access (UMA) protocol, sponsors can create a tokenized derivative of the S&P 500, or a basket of stocks. This concept provides access to and fractional ownership of assets for those who may otherwise be shut out from participation in capital markets due to censorship, geographic location, or high investment minimums
Synthetix enables the creation and trading of on-chain synthetic assets, which are financial instruments designed to imitate “real-world” assets.
A synthetic asset owner doesn’t own the underlying asset itself but should have a similar price exposure to an owner of the actual asset. For example, the owner of a synthetic version of AAPL (Apple), doesn’t have a legal claim over the stock itself, but she does have exposure to AAPL’s price action.
The reasons people may have for wanting to own synthetic assets vs owning the actual asset include a smaller minimum investment. While, for example, the minimum investment for a share of Amazon can be thousands of dollars, synthetic assets have no minimum investment. This has potential to democratize access to certain assets.
Exposure to assets that are regionally limited. US equities, for example, have outperformed most other equities markets since 2015, but access to US equities is extremely limited. Synthetic versions of US equities make it possible for people located in any region to gain price exposure to an asset in any other region, again bringing the potential to democratize access to certain assets.
Potentially lower exchange fees. On the Synthetix exchange, users can exchange any synthetic asset for another by paying only the gas (ETH) needed to confirm the transaction. This means that the fees for trading wildly different assets like Gold versus Amazon are reduced compared to status quo methods for doing so, which would involve transaction fees for different accounts. Synthetic assets effectively bring all assets into a single “account.”
The Synthetix network leverages economic incentives to drive adoption of the platform. Like Uniswap, the Synthetix protocol rewards users with fees (0.30%) generated by exchanges made on the platform. The difference is that rewards are paid out the native token SNX and they are made to those who provide the collateral needed to create synthetic assets.
To create a synthetic asset and receive the SNX rewards, the Synthetix platform requires collateralization of at least 750% (meaning, for example, that for every $750 worth of SNX locked up, a user will mint just $100 worth of sUSD — synthetic USD). This over-collateralization cushions the synthetic assets in circulation from unexpected price swings.
Note that since collateral is required to mint synthetic assets, it means these assets are debt-driven. The Synthetix platform also creates debt pools, which effectively allow synthetic asset issuers to pay back their debt with any type of synthetic asset, not just the one they minted. The result is a kind of ‘infinite’ liquidity, which — in theory — enables endless shifts between synthetic assets without upsetting the system’s balance.
Financial analysts make a living from their market predictions, and company performance & valuation analysis. They typically deploy complex models to derive their forecasts. However, these models can suffer from inefficiencies such as failing to integrate the newest information, overreacting to existing information, or failing to report on time. All of these inefficiencies combine to make analysts’ predictions unreliable. Is it possible to develop more accurate financial forecasts?
Prediction markets are a type of decentralized forecast model that have potential to outperform traditional forecasting models. Prediction markets, in a decentralized capacity, have been made popular by Augur. The Augur protocol allows anyone to choose an event to trade on. It rewards users for correctly reporting and forecasting events, and penalizes them for incorrectly predicting or reporting on events. In this way, participants are incentivized to act on their private information (by reaping financial rewards), without publicly disclosing this information. The result, however, is a sort of crowdsourced wisdom where the market tells you the likelihood of a certain event happening. This makes it a potentially very useful tool.
For example, consider an analyst who wishes to make an earnings forecast. This analyst can, using Augur, crowdsource knowledge for questions such as ‘will Amazon’s Q3 earnings per share exceed $7.00?’ By opening up the question to global participants, analysts can efficiently aggregate a large amount of information such as realistic beliefs and data. This can eliminate bias specific to individuals or small groups, providing more accurate forecasts.
Another benefit of prediction markets is that they also allow participation all the way up to event occurrence. The enables forecasts to integrate all the latest information, as it’s uncovered.
Altogether, prediction markets should make forecasting more reliable than ever. In some cases, they have already proven their worth. Research from Circle, for example, shows that they reduce forecast error by 5% on average compared to surveys when evaluating certain economic indicators.¹ In addition, corporations like Hewlett-Packard have witnessed prediction market forecasts that were 70% more accurate than traditional forecasts in the price of computer memory three to six months ahead.²
We rely on data to make decisions. Today, we have data aggregators that take unstructured data and structure it for users to review in the course of their decision-making. Generally speaking, a centralized party, such as the reporter or data feed, certifies that the information is truthful as it is made available.
In the decentralized world of open finance, there is a real issue with ensuring data integrity when reporting offline events in an online environment.³ Said another way, how do we verify others are telling the truth when reporting data and events to a blockchain? After all, people can have different views over the state of reality.
Open finance applications that rely on real world data all face this important issue. One solution to this issue is by using “oracles.” An oracle is an agent that finds and verifies real-world occurrences and submits this information to a blockchain to be used by smart contracts.⁴
Oracles can take many forms, the most common being software such as websites and online databases. Oracles can also be hardware, or even people (most commonly groups of people). Leveraging a variety of mechanisms, oracles are incentivized to report truthful information and face penalties for not reporting truthfully.
Take ChainLink for example. It is an open finance application providing oracle services which give smart contracts access to systems outside decentralized computing networks. Through ChainLink, users can automate the collection of market and event data from off-chain oracles and bring it on-chain.⁵
By doing this, ChainLink can bring determinism to the financial sector, eliminating counterparty risk. Financial products can be automated and verified without the need for intermediaries who collect fees and who may not act in the best interests of their clients.⁶
Adoption of Open Finance applications is underway. But by any measure, we are still early in the movement. We encourage those in the financial services industry to prototype open finance applications. It’s never too early to get started.
If this post has inspired you to learn more — or perhaps it even has you thinking about how your organisation can apply Open Finance — please don’t hesitate to get in touch. I specialize in helping businesses create new value using decentralized applications and digital assets. Here is my website and LinkedIn.
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We partner with new ventures to build, launch and scale digital assets. www.hexadigital.io
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Tags: cryptocurrency, digital currency, blockchain, open finance, bitcoin.
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 Ria Bhutoria. “Prediction Markets,” Circle Research, November 13, 2018.
 Ria Bhutoria. “Prediction Markets,” Circle Research, November 13, 2018.
 Michael Hirn. “Introducing Rlay, a Decentralized Protocol for Blockchain’s External Data Problem.” Medium, June 19, 2018.
 Blockchain Oracles,” BlockchainHub, accessed May 25, 2019.
 Chainlink. “44 Ways to Enhance Your Smart Contract With Chainlink.” Chainlink Blog, May 22, 2019.
 Chainlink. “44 Ways to Enhance Your Smart Contract With Chainlink.” Chainlink Blog, May 22, 2019.