Demand in shark and ray products such as meat, shark fins and livers and ray gill plates is on the rise. Sharks are being extracted out of the ocean by some estimates at 75 to 100 million individuals yearly and 25% of all shark, ray and related species are threatened with extinction due to overfishing and illegal catch. Protection efforts for these vulnerable species are improving through no take zones and catch restrictions through international agreements like CITES and CMS. However, Illicit catch, landing and trade in vulnerable and protected species is evermore present and current monitoring and enforcement measures have proven to be largely ineffective to protect these species from being extracted at unsustainable levels. A study published in 2017 established that around 30% of shark fins found on the Hong Kong market originate from species assessed as threatened by the IUCN; HK being the global shark fin trade hub which accounts for 40-50% of the global shark fin trade importing a total of 4,980 tons of shark fin in 2017. Seizures by HK customs authorities in 2017 amounted to a total of 2.6 tons (11 cases of which 10 transported by sea), equating to around 0.05% of total fin imports, demonstrating the huge lack of effective monitoring and enforcement at this neural point of entry.
Our solution is a risk scoring tool for individual shipments based on specific shipping documents that contain the relevant information. International shipping carriers as well as the entry and exit ports represent the bottlenecks where such trade can most efficiently be monitored. Our proposed solution takes specific data available on shipping documents and screens them against the purpose-built database to calculate a risk score of how likely a certain shipment contains shark fins. The case of shark fin is selected to run a proof of concept and design and build a prototype. When the prototype has been shown to work on the shark fin case, it can be scaled and other unwanted or illegal wildlife parts, products and derivatives can be integrated into the tool.
Consumption, trade and trafficking of illegal and unwanted wildlife products will increase in the future following the constant increase in demand.
Shipping companies are genuinely interested in following through on their pledges to no longer carry certain wildlife products.
Port and customs authorities will be interested in the solution because it provides a very resource effective way of identifying the needle in the haystack.
Compliance and regulatory frameworks will emerge as a hot topic for the commercial shipping industry and there will be a need for cost and time-effective solutions.
An non-proprietary system is more efficient and effective than several isolated company-developed solutions.
The value generated by machine learning and pattern analysis will transform compliance in the shipping industry and can be expanded outside the realm of wildlife trade and trafficking.
Reducing plausible deniability and increasing accountability will either help or prevent organizations from using our tool.
The most powerful lever created by our solution is the reduction of time and personnel required to manage risks pertaining to the illegal wildlife trade. This will enable companies and authorities to concentrate their efforts on high risk shipments and deploy their activities more effectively. Other benefits include a reduction in errors by way of automating a part of the screening process, reducing misstatements and corruption by providing a traceable log of screenings against which shipping companies and authorities can be held accountable. Our solution is designed to reduce plausible deniability by dramatically lower overall cost, time and personnel required for effective compliance screenings and the detection of illegal or unwanted goods in cargo.
Build a prototype to validate the use case and patent and license the technology that underlies the database and query interface. Build a first version of the database and interface and run a trial in 2019 to improve the technology and refine the technology. The ultimate goal is the roll out at scale to commercial shipping companies and competent authorities tasked with overseeing cargo import and export to increase detection rates from currently only 0.05% (2017).
We're currently working on data model design and developing the use cases and get started on building a first working prototype. If you have technical skills and experience in data analytics, different applications of machine learning or web development we'd be excited to hear from you! Interested in contributing to combat the illegal wildlife trade and have other relevant skills you could bring to the table? We'd be stoked to have a chat.