Distributed ledger technologies such as blockchains are beginning to herald a new era for audibility and accountability through tamper-proof logging of data and recording those responsible for updating or changing data sets contained in ledgers. However, although blockchains track changes of an object state in a ledger, they do not guarantee that the reason the change was made will be logged.
Why is this important?
When an audit investigation takes place in any industry or sector, the reasons for changes need to be verified and validated. In blockchain, records are ordered chronologically and linked to one another via references and these references can be used to identify records. However, the reasons for the change may not be present or may be too shallow in that they don’t indicate all the factors for operations leading to updates. As time goes by, investigations become more costly since figuring out why operations have been carried out is resource-intensive.
Current DLT and blockchains store operational changes without reasonable causativity. Assured Ledger Technology (ALT) strengthens blockchain and its application in business processes by allowing a full history and causativity of actions to be maintained, together with the reasons why data within the ledger has been updated. This is useful, for example, in contracting, since the origins of all operations can be traced for legal purposes, and the integrity of the reasons is guaranteed (assured).
This is why we need assured ledgers which don’t just link the records chronologically by time of creation or registration, or require users to enter excessive detail into entries. Instead, enterprise needs a ledger which links all the reasons for each change to make it simpler to identify why a transaction took place.
Assured Ledger Technology: how it works
In Insolar’s Assured Ledger Technology, each new record has a reason for why it was created: a link to the actions which justified its creation. As such, there is a data object about, for example, a user making an order for something. This order will go through several stages, changing hands and location before the user receives it. Every time an action is completed the order’s (object’s) state in the ledger alters and the actions are performed by actors within this process. The reason for change therefore becomes a reference to the actor doing something and the state of the order.
To show how it works, let’s consider an example in which someone purchases an order remotely. In this example there are four different levels where ALT works: 1) user level; 2) shop level; 3) courier level; and 4) item level. The levels are categorized to highlight the complexity of a single operation — the delivery of an item from a store.
Example of ALT implementation: Item delivery from warehouse to user
From the image above, you can see that each action doesn’t just have a simple consequence (order item — receive item), but creates a web of further actions that need to be taken in order to satisfy the request. This is present throughout all business logic. As such, this simple yet powerful feature allows to reduce resources spent on conducting audits when necessary, as retracing each step can take place within a single system.
The table below highlights how each action has a reason behind it which can create a “reason registry”, making it easier to audit why certain transactions take place. The table below highlights all the actions which lead to an update of the ledger and the reason for the actions.
Let’s run through a quick example from the table and diagram above. To illustrate how it works, we will work backwards from the courier dropping off the order. When the courier delivers the order, a record is made that it has been delivered, and this record is tied to the previous record which details the said courier’s previous state. If we want to see why the courier collected the order, we can look at the reason record which details all the elements in the chain of events, starting from the placing of the order by the user, all the way up to the order being collected.
As mentioned above, the reasons for business transactions are multi-faceted. When an end user makes a decision to complete a transaction, this sets off a chain of actions, each with its own reason. ALT allows us to trace the origin of each action without leaving the chain and/or looking for any additional data and ensures the integrity of these reasons. While blockchain and DLT both ensure data integrity on their own, ALT adds multi-tiered reason proof for each action, since every business works on a multi-level hierarchy.
ALT greatly simplifies and reduces the cost of legal investigations or reporting as the reasons for each operation are recorded. Business operations imply a multi-tier separation of concerns in a multi-actor environment. This means there is a need to trace why an operation (based on a single user request) should take place at every step of its execution. Instead of just recording all changes in sequence, ALT also tracks causativity as the chain of reasons why the ledger was updated and a change was made to a certain object that is represented on the ledger. This feature will save businesses a tremendous amount of resources where they need to carry out an audit on operations and transactions.
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