A refusal of your Canadian visitor visa application can be a frustrating and disappointing experience. However, it is important to remember that a visa refusal does not necessarily mean you cannot visit Canada. There are steps you can take to overcome a visa refusal and increase your chances of a successful application.
Temporary resident visa refusals often arise from concerns regarding the applicant’s intent to come to Canada temporarily. Other common reasons include lack of financial means, limited family and economic ties to home country.
Navigating the application process for a Canadian visitor visa can be challenging, particularly for those unfamiliar with Canadian immigration laws and procedures. Working with Tamber Law PC can help ensure your application is complete and accurate, increasing your chances of a successful application. Our service goes beyond filing forms and documentary evidence. It includes the preparation of a detailed legal and factual submission that references the law, previous cases like yours, speaks to and draws from the supporting documentation, review and direction regarding all supporting documentation, where applicable checking your immigration history and addressing any concerns in particular inadmissibility checks.
A knowledgeable Immigration lawyer can significantly improve an applicant’s chances of success when reapplying for a TRV. We can help you review the application, address officer’s concerns and help gather strong evidence, but if we believe there was an error or unfair judgement, we can assist in pursuing a judicial review through the Federal Court of Canada to correct any mistakes in the original assessment.
We have helped multiple applicants in the past with successful reapplications through Federal Court.
How is AI used in Canadian Immigration?
When people submit applications to Immigration, Refugees and Citizenship Canada they typically have spent significant time carefully completing forms and assembling documents. They expect that their applications will be processed by visa officers who carefully review the information before them. However, applicants need to understand that their artificial intelligence is playing an increasing role in visa processing, as is the bulk processing of applications.
Advanced Analytics
The history of the use of advanced analytics in IRCC decision making can be briefly summarized as follows. Much of the following is paraphrased from the ATIP below.
In the deployment of advanced analytics, two sets of rules are utilized. First, a set of automated triage rules was deployed in April 2018 to identify TRV e-Applications submitted from China that meet these rules. The automated triage rules, also known as the ‘Officer Rules’, were created by IRCC’s Beijing office using statistical information, industry trends, and historical data. Second, after the Officer Rules/triage rules are applied, an analytics model is utilized to identifyTRV e-Applications which meet rules established by data analytics software using industry best-practice methodology. ‘Model Rules’ are created by the SPSS Modeller software using historical data on prior processed TRV applications from China. It is important to understand these two terms.
The Machine Learning uses a decision-tree model, which can be graphically represented as splitting the dataset into a series of branch-like segments forming an inverted tree originating with a root node at the top (see Image 1 below).10 Each split, where the large data group is broken into progressively smaller groups by posing an either-or scenario, is referred to as a node. The bottom nodes of the decision tree are called leaves {or terminal nodes}. Each node represents a fact about an applicant and the leaves represent classes of acceptance or refusals. For each leaf, the decisoin rule provides a unique path for data to enter the class that is defined by the leaf. The leaves are mutually exclusive, i.e. they are designed so that no application oculd meet the conditions of more than one leaf.
Once data sets are identified, they are studied by the modeller in search of ‘features’ or ‘characteristics’, called variables that can be used to build the Model Rules. The variables/flags are the data fields used to find patterns and correlations and make reliable predictions of the outcome. From the various fields of information extracted from IRCC records, the analysts must determine which ones are relevant and contain reliable and consistent data for modeling purposes.
The data that are the flags/variables comprising the Model Dataset, including the outcome/decision, are used by the advanced analytics software to ‘train the algorithm’. The SPSS software tries millions of combinations of applicant characteristics (flags/variables) in search of patterns and to assess how they correlate with approval or refusal of a given application, i.e. the identified target variable. When it finds insightful combinations that repeat and reliably and consistently lead to the same outcome, it formulates these patterns as decision rules-the ‘Model Rules’. The reliability and consistency of a Rule leading to an outcome is referred to as the confidence threshold of the given rule.
The Officer Rules are created as a set of triage rules, which are applied prior to the Model Rule triaging.
The Model Rules are created using historical, personalized applications for each line of business and using analytics software to identify trends, patterns, and commonalities within those applications.
In Luk v. Canada (Citizenship and Immigration), 2024 FC 623, Madam Justice Aylen held that the use of algorithms or artificial intelligence to process applications is not in of itself a breach of procedural fairness.
Chinook
In addition to automated triaging IRCC has also introduced software so that officers can bulk process applications. The software tool is known as Chinook.
According to an affidavit that IRCC filed in Federal Court, Chinook is a standalone tool that streamlines administrative steps. Applicant information is extracted from their applications and presented in a spreadsheet. Visa officers are assigned a workload of applications through Chinook. They are able to see multiple applications at a time on a single spreadsheet. This allows them to review the contents of multiple applications on a single screen, and allows them to complete administrative steps through batch processes. It also allows visa officers to create “risk indicators” and “local word flags” so that officers can identify possible applications in the processing queue of concern or priority.
According to the Federal Court affidavit, when visa officers enter Chinook a message pops up which says, amongst other things, “The Chinook User Interface allows you to view multiple applications for review and initial assessment. It does not replace reviewing documents.. and/or reviewing other information… The refusal notes generator is meant to assist with general bona fide refusals. If the notes do not reflect your refusal reasons, please write an individual note.”
Concerns
There have been many concerns raised about the implementation of automated triaging and Chinook. These include the possibility that it is what has led to increased refusal rates, that individual care is not being given to applications, that applications are not being carefully reviewed and instead quickly bulk refused, that AI flagging a file as high-risk will lead to an officer wanting to simply affirm the AI’s finding, that refusal reasons are increasingly consisting of boiler plate templates which is not helpful for applicants, and that it may perpetuate systemic racism.
Because IRCC has not been transparent about the implementation of these systems and their results it is difficult to confirm if these concerns are founded. Regardless, it is important that those submitting applications understand that Canada’s immigration system is no longer one in which human officers meticulously process individual applications in the order that they are received. It is important for individuals with refused applications to obtain the internal reasons for refusal, or Global Case Management System (“GCMS”) notes. IRCC’s use of artificial intelligence and bulk refusal generators makes this even more important, as a review of the internal reasons or GCMS often indicative of whether such software was used, and whether a refused applicant should either file a reconsideration request or seek judicial review to see if a human may reach a different conclusion.