Matching Algorithms for
Resettlement & Relocation

Limits to Traditional Resettlement & Relocation

Typical resettlement & relocation processes rely on human decisions. This can often mean inconsistent matches, bias, and wasted resources.

Traditional
Refugee
Matching

Human Bias

Matching based on assumed preferences and subjective opinions.

Inflexible, Individuals Only

Traditional systems are challenged by complex populations and needs, and often prioritise one household member.

Limited Scalability

Labour-intensive processes are difficult to scale and error-prone.

Single-Dimensional
and One-Sided

Typically consider receiving community preferences and narrow refugee attributes.

Opaque

Decisions lack clarity and explainability, with lower efficacy and equity.

Resource Misallocation

Not accounting for population-level matching can waste scarce resources.

Pairity’s Solution: Flexible, Scalable Preference-Matching

Preferences & Capacities: Participant data as matching variables centres refugee & receiving community agency. 

Data-Driven Efficiency: Calculates millions of possible combinations across dozens of matching variables.

Transparent Records: Data-driven matching creates transparent records for accountability and real-time monitoring. 

Optimized Resource Use: Optimises use of resources like shelter beds, sponsor capacity, and settlement services.

Adaptable: Accounts for diverse types of households, receiving communities, and pathways.  

Population-Level Matching: Optimally distribute matching outcomes for entire cohorts. 

Pairity’s data-driven preference-matching accounts for the aspirations, needs, and capacities of all parties. We incorporate a vast range of data, including from refugees, communities, and governments. Our data-driven, human-centred solutions are designed for complex, fast-paced environments. Population-level algorithms optimize for everyone. 

Matching works across use-cases including complementary pathways, asylum seeker housing, and community sponsorship initiatives. We deliver improved integration and social cohesion, more efficient use, and objective evidence.

Our Process

  • 1. Define


    Whether you’re trying to match refugees to communities or law students to articling positions, our team will work with you to clearly define the problem and solution.

  • 2. Gather


    We plug into your existing systems to capture data you already have. We create new data capture solutions for any data you might be missing.

  • 3. Match


    Our team of experts will customize our matching algorithm to solve your problem, taking into account any specific requirements you have.

  • 4. Monitor


    We will provide you with advanced analytics to evaluate the outcome of the matching and continuously improve the process.

Contact Us