Skip to main content

Digitize Land Registration

Traditionally manual land registration systems have created a dearth of data, and rendered the land transfer process delayed, costly, and inefficient.

Nearly 100 million acres of US farmland is expected to change hands in the next few years as elderly farmers retire, impact investors and developers as well as farmers. The industry norm in the past was often to pass land down informally, and through spoken arrangements, driving a dearth of data on land ownership.

Context & Challenges

The practice of handing land down informally, and without official record, creates a situation whereby the rightful owners of land are difficult to prove, requiring a great deal of administrative work to bridge the gap between available and necessary data. As a result, the time between signing a contract and transferring a title to three to six months and finding farmland is one of the main challenges facing young farmers.

In addition to lacking the data to facilitate seamless transfers, the land registration and transfer process faces a host of other challenges, three examples of which are listed below.

  • Land registration fraud – e.g. counterfeit ownership documents, forged signatures
    • Insufficient fraud detection systems & lagging communication between relevant parties
    • Opacity and a complex supply chain with multiple intermediaries (brokers etc.)
  • Defective foreclosure and mortgage documents
    • Poor identification of Errors
    • Difficult to track the origin of Error
    • Bulky administrative process to correct Errors
  • Discrepancies in Regulation and Processes across Borders
    • Lack of standardization makes international or even cross-state transfer complicated
  • Farmers
    Lengthy payout delays lead to planting and harvesting delays, causing farmers to produce smaller yields and incur a myriad costs.
  • Brokers, Agents, and Financial Institutions
    The bulky and labor-heavy administrative process creates inefficiencies for brokers and any other agents managing the process, inherently driving cost and waste.
  • Government Bodies
    Managing land title registries are labor-intensive and costly for governments, compelling some such as the New South Wales government in Australia to outsource and sell the rights to them to private entities.
  • Anti-Fraud Bodies
    Entities like the FBI must perform intensive fraud detection and resolution processes, many of which are ineffective due to lack of data and automation.

The Good News

In Sweden integrating blockchain into land registration and transfer has been shown to produce cost savings of more than 100 million euros per year for taxpayers by creating immediacy and eliminating extraneous labor, time, and resource costs. A STRATO solution could enable an incorruptible ledger of land records, linking them to sovereign ID or digital ID so that they would be untouched even by natural disasters or wars. This drives a number of benefits, listed below.

  • Ease labor and time costs – automating and digitizing processes
  • Allow near real-time traceability and transparency around the sale and purchase of land
  • Close the gap between purchase and procurement – faster transactions

This potential for positive impact has motivate governments of countries beyond Sweden, including Ukraine, the US, and the Republic of Georgia to experiment with this use case with great success.

Solution Benefits

  • Automate manual and labor-intensive verification processes
  • Implant a land title’s logic in a smart contract to automatically execute on any imbedded terms
  • Settle and verify transactions with minimal manual intervention
  • Link land record to sovereign or digital IDs to ensure permanence, and avoid fraud

Any STRATO insurance solution leverages STRATO’s enterprise grade features

  • RESTful APIs for direct connection of relevant devices to the blockchain network
  • Identity Management, OAuth and SSO capabilities for simplified IoT authorization and user login
  • Privacy via private chains to keep any competitive/operations data private
  • Enterprise Data Modeling for integration of existing and land registration data models