Unlocking business value with smart legal contracts

11 minute read  02.11.2020 Paul Kallenbach, Jonathon Blackford Jason Watling

We explore how smart legal contracts can help your business, and explain how you can identify clauses that may be amenable to automation.

How can smart legal contracts help?

Smart legal contracts can help businesses:

  • reduce the costs of contract management (via automation and standardisation);
  • increase contractual compliance (via automation and consensus);
  • increase the speed at which contractual obligations are performed (via automation);
  • provide for faster negotiation and execution of agreements (via templated smart contracts);
  • gain improved insight into contractual obligations and point-in-time states (via automatic data capture); and
  • improve a party’s capability to simulate possible future scenarios.

Let's look at each of these in more detail.

Reduced costs and increased compliance

Contract management can cost between 10-20% of the total value of a contract. Improving efficiency through automation helps to reduce these costs. For example, rather than manually processing notification requirements under contracts, these can be handled automatically. Instead of manually calculating rates, formulae can automatically do this in compliance with the contract – and feed these into other systems.

Automation can also prevent human error (eg when transcribing a result into software) or malfeasance, removing associated costs and increasing contractual compliance. By requiring clearly defined contractual obligations and by providing the ability to clearly track performance, smart legal contracts can facilitate increased compliance with the agreed contractual terms.

Faster performance

Automatic systems can make decisions and execute accurately in a fraction of the time humans take. This can result in faster performance of contractual obligations. When multiple automated decisions are chained together, this effect compounds as automatic execution eliminates delays from waiting for human decision makers.

Faster execution

Once a template agreement is established, contract execution can be achieved more efficiently, as variables can simply be plugged into the contract. The nature of the information to be incorporated can be enforced through template input restrictions, allowing deals to be closed faster.

Appropriate workflow checks and balance can also be implemented automatically, by requiring reviews from the right people and distributing relevant information to them before a contract is digitally signed by the organisation.

Improved insights and simulation capability

Smart legal contracts can provide the data needed to measure contractual performance and spend, by directly integrating analytics. For example, a smart legal contract can automatically capture the exact time that certain goods arrive based on an RFID chip, which can be fed into a real-time inventory management system.

At a higher level, many common contractual obligations will be expressed in code or at the very least in a standardised manner. This means that smart legal contracts provide an instantaneous view of portfolio level obligations, instead of the current manual process of analysing all contracts to understand these obligations.

A history of minor non-compliances can be automatically recorded, and across a portfolio of agreements, terms can be negotiated in that trigger defaults after certain thresholds are exceeded – or the information used to determine which vendors are performing better. By building this data into all of your smart legal contracts, you can facilitate the capture of data from all vendors and build this level of analysis into your contract management process.

This wealth of data also allows you to better simulate future scenarios, by modelling the impact of different parameters against actual performance. For example, if a delivery time is consistently missed, you could model the impacts of extending timeframes, pushing for higher penalties etc – and determine how this compares with historical data.

How are smart legal contracts currently being used?

While most work in this field remains theoretical, commercially useful smart legal contracts have started to be implemented in the last 5 years. Overseas, we've seen smart legal contracts automate:

  • parametric insurance for solar energy providers, where a claims obligations and a bordereau are automatically generated based on weather data ingested via an API; and
  • fuel surcharges in freight transportation contracts, where applicable fuel surcharges are automatically calculated based on public fuel price data and shared to a blockchain.

We expect to see more use cases internationally as the technology matures.

What benefits does a smart legal contract have over traditional electronic data interchange (EDI) systems?

By bringing the potential for automation earlier into the negotiation process, smart legal contracts can help parties unlock more business value by establishing legal positions that are amenable to automation, as discussed above.

Smart legal contracts also have the ability to provide for richer automation in a standardised and more transparent manner. A smart legal contract can, for example, execute an agreed process in a transparent manner via a trusted third party or blockchain, thus preventing the need for results to be double checked at both ends. This can allow for untrusted business processes to be executed in a coordinated and trusted manner. In contrast, a traditional EDI system only provides a way for parties to pass data back and forth between each other and their respective internal systems.

There are also significant contract management benefits in using smart legal contracts to reduce the amount of paper/human management to answer business queries around contractual positions. Smart legal contracts prevent the current arduous process of manually assessing all contracts to provide a view of obligations across a large portfolio.

Smart legal contracts can also enable parties to more effectively manage their risk than traditional EDI systems. Find out more in Part 3.

Which clauses could we automate?

In working out which clauses are amenable to automation, there are a few key factors we'd suggest considering, set out below.

Business as usual (BAU) clauses

Clauses which reflect 'business as usual' arrangements are likely to unlock more value via automation, as they're what's used most often, so automation will likely have the greatest impact.

Eg automating the monthly payments under a lease

Trusted data sources (oracles)

Clauses which can rely on trust data sources (both external and internal) are better candidates for automation. Data sources can be, for example, published data available through a web API, or information sent by an Internet of Things (IoT) sensor

Eg automatically pulling through the Bank Bill Swap Rate into a financial instrument

Easily capturable logic

Clauses which have clear, easy to capture logic are more likely to be automatable. In contrast, 'fuzzy' concepts like reasonableness are more likely to require human intervention.

When drafting it is worth considering what business value maybe unlocked by parameterising a clause so that it can be automated (ie setting out specific criteria and tolerances)

Eg a parametric insurance contract for drought events

Business value unlocked by state-based triggers

Clauses where business value can be unlocked by triggering external actions depending the state of that clause are excellent candidates for automation

Eg automatically triggering notice provision under an SLA when a breach is detected, to start the clock sooner

Value in seeing the point-in-time state of the clause

Clauses where there is value in seeing the state of rights, obligations or other parameters at a particular point in time are good candidates for automation

Eg automatically detecting stock shortages via RFID embedded goods

Underscoring all of this is a balancing of the commercial value obtained against the cost of implementation. Developing automated clauses can take significantly more time than writing them in natural language. Reviewing and testing to ensure accurate execution adds further costs. However, if the right candidate clauses are selected, the commercial value of automation can outweigh these costs even in the short term, and over the lifetime of a contract savings will accrue. 

Industry examples

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Rent review clause

Let's take the example of standard rent review clause in a lease, with standard CPI + 2% rent reviews, and a market review every 5 years.

Consider the factors about automation above:

  • Rent reviews are part of BAU arrangements (ie they will regularly happen unless something intervenes)
  • There is a trusted external data source available for CPI (a government published figure)
  • Standard rent reviews have logic that is easy to capture – the simple formula of (last year's rent * 1+ decimal CPI + 0.02))
  • Market reviews require manual intervention for which a human will need to be notified

In the analogue world, before the start of each rent review date, the landlord needs to find the CPI, calculate the new rent, update their systems and notify their tenant of the new rent. When it comes time for market review, the landlord needs to remember to do this within the relevant notice periods – a further administrative burden.

With a smart contract, the CPI + 2% increases can be handled automatically. If the tenant also ties into the smart contract, then their payments can also increase automatically. When it comes time for market review, the contract can automatically notify the landlord that it needs to propose a new rent and the timeframes in which to do it, with reminders pre-programmed if a new rent is not input.

At the portfolio level, with varying commercial details between leases this has the potential to save significant administrative costs – and as more contractual obligations are automated and tied together, these savings can compound.

Rent reduction based on turnover

Continuing with our rent example, consider a negotiated rent-reduction due to COVID-19 – where for 6 months, rent is discounted by the percentage fall in turnover compared with last year's turnover. By authorising the smart contract to access the tenant's accounting software automatically, it can compare and calculate the percentage fall in turnover and automatically apply this to rent on a daily basis. This allows a fair rent reduction to be automatically applied, while also exposing the exact state of expected rent to the landlord on a day by day basis. This extra data can then be used to precisely forecast expected revenue, and keep track of how rental revenues are performing on a daily basis.

Reviewing this scenario against the automation viability criteria above:

  • Rent reductions will be part of BAU arrangements for at least 6 months – they will regularly happen unless something intervenes
  • There is an external data source available (the tenant's accounting software) – though this is likely less trustworthy than the CPI example above
  • Rent reduction has logic that is easy to capture – the simple formula of (rent * (this year's turnover/last year's turnover)) where this year's turnover is less than last year's turnover.
  • There is great value in point-in-time state information, as it can help the landlord understand their actual rental yields.

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Managing complex supply chains

Consider a complex medical supply chain, where minimum levels of various medicines need to be kept in stock by a hospital network. A smart legal contract could automatically order these as supplies ran low, track delivery progress and provide updates about equipment locations through RFID tags.

Let’s compare this scenario with criteria for automation set out above:

  • Business as usual – medical supply levels are a critical task that needs to be continuously monitored
  • Trusted data sources – RFID chips physically embedded in goods would provide a trusted data source for the smart legal contract
  • Easily capturable logic – the purchasing logic might be difficult to capture, as unless prices are locked in well in advance of shortages, an automated purchasing system might be exploitable and result in higher prices being charged
  • State-based triggers – being able to immediately order supplies below a certain threshold could be invaluable in ensuring sufficient resources are available

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Construction site monitoring

Let's take the example of a construction site with permitted hours of work, where workers sign onsite using an app on their phone, which in turn records hours on site to the cloud. Using a smart legal contract connected to the site's cloud, the contract could track the site against hours of work permitted under the contract, and notify the parties if this is not adhered to. If the permitted hours of work change, this can also be updated in the system automatically.

Reviewing this against the criteria above:

  • Trusted data sources – using an existing safety app as the data source provides both workers and employers with strong incentives to report this accurately
  • Easily capturable logic – determining if something is in permitted hours is easy to capture (assuming daylight savings and the like are taken into account)

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Interest under facility agreements

Interest under facility agreements in Australia is frequently calculated by reference to the Bank Bill Swap Rate (plus a margin). Automating the calculation and requests for payment across a large portfolio of agreements could provide significant cost savings and make administration and changes to these contracts much easier – particularly if the BBSW were to be replaced with a risk free rate as is happening with LIBOR.

Comparing this with the automation criteria above:

  • Interest calculations are a frequent occurrence, especially across a large portfolio
  • The BBSW is a published rate in which there is a great deal of confidence
  • The logic behind interest rates is already encapsulated in a formula, and therefore is a prime candidate for automation.

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Water allocation

A series of interconnected smart legal contracts could potentially assist with water management; connecting smart meters to a network would enable entitlements across a river system to be automatically calculated and even priced.

Let's consider how this fits the automation criteria above:

  • Business as usual – water draws are consistent process that could be monitored at more frequent intervals if automated
  • Trusted data sources – water flow levels could be automatically monitored at various points along a river system, with this data automatically ingested. Controls could be put in place to detect unusual changes and detect tampering. However, there is the potential for bad actors to underreport their water draw (eg by using an unmetered pump) that would need to be considered
  • Easily capturable logic – water allocations can be determined by a transparent and easily capturable formula, based on rainfall etc
  • State-based triggers – being able to rapidly shift allowed water draw as a result of unexpected rain, or automatically reduce it during droughts, would enable more efficient and fair allocation of resources
  • Point in time data – data would be invaluable, as tweaks to water allocation formulae could be easily tested to see point in time impacts on water levels.

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