Student Loans Company: Advanced Learning Loans Assessment Rules
Automatic evaluation of a student's advanced learner loan application to determine eligibility and entitlement.
Tier 1 Information
1 - Name
Advanced Learner Loan Assessment Rules
2 - Description
The Advanced Learner Loan assessment rules engine can perform an automatic assessment of applications from applicants wishing to obtain tuition fees for further education.
The system uses the information provided by applicants and course information from further education learning providers/ESFA/DfE to automatically determine eligibility and entitlement to funds in accordance with government policy on any given supported academic year.
The system allows the SLC to provide the service to the public at scale in a logical and consistent manner.
3 - Website URL
https://www.gov.uk/advanced-learner-loan
4 - Contact email
Tier 2 - Owner and Responsibility
1.1 - Organisation or department
Student Loans Company, Technology Group
1.2 - Team
Assess FE
1.3 - Senior responsible owner
Chief Information Officer Head of Software Delivery
1.4 - External supplier involvement
Yes
1.4.1 - External supplier
Syntel Europe Limited
1.4.2 - Companies House Number
Syntel Europe Limited - Company number 03227061
1.4.3 - External supplier role
Delivery of Advance Learner Loan product began in 2013 since then SLC has engaged multiple third-party partner organisations to help develop, evolve and maintain the Advance Learner Loan rules engine.
Syntel Europe Ltd (a company currently operating under Atos), Edge & Sopra Steria were involved through early inception of the service, providing the SLC with additional software development staff to develop the initial core functions of the service to deliver the Advanced Learner Loan products.
Syntel Europe Ltd replaced all the previous partners and provided continued involvement alongside SLC development staff implementing annual changes from updated government policy.
1.4.4 - Procurement procedure type
SLC - Awarded via Framework - Technology Services 3 Framework Agreement RM6100
1.4.5 - Data access terms
The terms of access to (Government) data granted to the supplier are provided within the Framework Terms and Conditions of the Technology Service 3 Framework Agreement RM6100. The license granted by the Customer to the Supplier as follows: The Customer hereby grants to the Supplier a royalty-free, non- exclusive, non-transferable licence during the Call Off Contract Period to use the Customer Software, the Customer Background IPR and the Customer Data solely to the extent necessary for providing the Services in accordance with this Call Off Contract.
Tier 2 - Description and Rationale
2.1 - Detailed description
Advanced Learner Loan Rules make automated decisions considering the information provided by students (e.g. identity and residency information) DfE (e.g. course information) and other government sources (e.g. HMPO for identify verification, Home Office). It determines any outstanding information and/or evidence needed to help guide students towards successful completion of their applications, as well as automatically deciding eligibility and entitlement amounts if possible. The tool supports manual assessment and manual overrides which allows student finance officers to manually validate and update evidence and eligibility information, this takes place when there is missing information or evidence e.g. proof of residency history for eligibility. The rules involved are individually straightforward but collectively complex. This complexity is tackled partly using a third party open source business rules management system named Drools. This is not an AI tool - there is no “scoring” or analysis of data using complex statistical or machine learning algorithms - it is instead a forward-inferencing rules engine (based on the RETE algorithm). Its usefulness derives from its support for order-independent authoring, composition and application of the large and overlapping rulesets required by the Department for Education each academic year.
2.2 - Scope
The Advanced Learner Loan assessment tool and its rules are used solely for assessing student finance applications for Advanced Learner Loan funding for England. This process can be initiated in two ways: either by submitting an application via the SLC customer portal, or via a paper based application which, when received, is data entered by SLC operational staff into the Advanced Learner Loan operations portal. Both routes result in automated processing of the application via the rules engine
2.3 - Benefit
The Student Loan Company receives a large volume of applications each year, with varying policy rules applied based on the cohort, domicile, product and academic year. The volumes received across the business cannot be manually processed in a timely, consistent, or cost effective manner. The automated processing of applications supports the large volumes of applications and results in the rules for each application being applied in a consistent manner. Where exceptions occur the system updates the application state accordingly to indicate to student finance officers that manual intervention is required. The automation of the majority of applications allows operational staff have the capability to deal with each case and provide more care and attention to individual customers with specific needs.
2.4 - Previous process
Prior to the introduction of this assessment functionality, SLC provided no financial support for further education in England. The introduction of government policy to provide student finance to further education students necessitated the need to introduce a solution to assess all the extra tens of thousands of applications on top of the volume of applications SLC already received for other SLC services. A project was instigated to build a new system, with a decision made at senior levels of the organisation to implement the solution using modern development standards, tools, technologies and processes.
2.5 - Alternatives considered
SLC considered other implementation options, including using existing assessment systems, to deliver the Advanced Learner Loan assessment rules. The decision was taken to use more modern technologies and technical architecture to deliver the further education service with Advanced Learner Loan.
Tier 2 - Decision making Process
3.1 - Process integration
Advanced Learner Loan Rules provide decision making for the Advanced Learner Loan platform handling processing of student finance applications. Applications are either entered online or submitted on paper, when these applications are received by the Advanced Learner Loan platform they are automatically and immediately assessed to determine their status. The Advanced Learner Loan rules engine is the sole decision making tool for Advanced Learner Loan finance application for England. The platform gathers and persists the information used by, and calculated by, the rules and presents it where needed to customer, assessor and advisor portals. If the rules determine that insufficient information or evidence has been provided that will be the outcome of the assessment flagged to student finance officers for manual intervention. The platform also orchestrates automated correspondence to students, including chasers, and instructs SLC’s downstream processes to set up payments to learning provider for tuition fees. From there repayment processes are ultimately set up on completion of their course.
3.2 - Provided information
The information considered by Advanced Learner Loan rules includes: • the data provided by the customer on their application for student finance (including their address) • any supporting evidence submitted • other reference government data (e.g. Identity and Residence Status Information, where applicable)
The Advanced Learner Loan assessment rules engine will use this information to return an outcome based on the Advanced Learner Loan assessment rules. The outcome will typically comprise: - • Identified missing information, if any • Identified missing evidence requirements, if any, including a breakdown of validated evidence supplied that may meet these requirements • A list of eligibility criteria and whether they have been met or need manual assessment • Entitlement amount • An overall application status (e.g. missing evidence, missing information, approved, ineligible, etc)
3.3 - Frequency and scale of usage
Over the last 12 years, the algorithm has processed an average of 65,000 applications per annum across England. Approximately 9-10% of applications in England are submitted as paper-based applications. All applications are processed by the same rules engine.
3.4 - Human decisions and review
A typical application for an Advanced Learner Loan is fully automated, adhering to the business rules developed from government policy. Only when there is missing information (paper-based applications only), missing evidence or evidence that fails to meet requirements (online and paper-based), will the rules result in fallback to manual intervention. These exceptions are manually processed by staff trained to deal with these circumstances.
Applications that do not meet the eligibility criteria (e.g. the applicant is over the age limit at the start of the course) will be automatically assessed as ineligible.
3.5 - Required training
Development staff are provided an overview of the entire system and an introduction to the individual services that encapsulate the assessment process. Development staff are provided a checklist of information that they are required to learn about the system and are given reference documentation on the development, deployment, support and maintenance of the system. Staff also work with more experienced members of the team for a period of time to get real world knowledge of the system and companywide processes to support the overall system.
Operational Staff undertake training provided by the Learning and Development team. Full system training will be provided to new recruits with top-up training provided where changes are introduced within the system. Work instructions and Guidance documentation is also produced as a reference tool.
3.6 - Appeals and review
If a customer feels a decision in relation to their student finance application has been made incorrectly, they have the right to appeal. An appeal is a formal request for the decision to be reviewed. Appeals can be submitted by post or email.
When submitting an appeal customers need to provide details of the award they’re appealing and why they consider SLC’s decision to be wrong. They should also enclose any evidence that supports their case.
The appeals process takes on average 40+ days and will be dealt with by the Appeals team with no automated processing. An appeals officer will review the original decision and details alongside any supporting evidence submitted as part of the appeal.
Submitted appeals will be rejected where it is not a genuine appeal, such as disagreeing with policy, or requiring more information regarding their application.
Tier 2 - Tool Specification
4.1.1 - System architecture
All the files and configs that implement the business rules are packaged in a JAR (Java ARchive) file along with the other required models and Java classes. This JAR file is further added as a dependency to the Web Application and Web Service that deal with the paper applications and online applications respectively. The Web Application and Web Service are deployed independently using a combination of automated and manual steps. These are deployed across multiple development and test environments before reaching production; at each stage there is a suite of automated and manual tests increasing in breadth and depth to maintain correctness. The application/service are deployed in production with multiple instances to provide high availability, robustness and scalability. These are updated periodically in production based on the requirements in specified downtime windows and thus not impacting any ongoing user activities.
4.1.2 - Phase
Production
4.1.3 - Maintenance
The services that deliver the assessment process are supported, updated and maintained on a regular schedule: - there are typically annual changes to government policies that necessitate an update of the business rules and processes implemented. - periodically there are projects that take place that may result in changes to the integration of the services with other systems. - there are irregular clarifications of government policy that may result in updates to the rules throughout the year. - any defects that are reported/identified can be rectified on an on-going basis - there are mechanisms in place that monitor the system for any problems and members of staff that regularly inspect the system for problems.
The deployments to the underlying applications are semi-automated and regularly maintained. The underlying infrastructure is scanned and patched on a need basis.
4.1.4 - Models
The core business rules contained within the services are implemented using a business rules management engine named Drools, which in itself is written in the Java programming language. The data models consumed and produced by Advanced Learner Loan Rules are entirely in-house, relatively small, and completely independent per customer apart from shared reference input data such as course details.
Tier 2 - Model Specification
4.2.1 - Model name
Student finance policy for Advanced Learner Loan in England
4.2.2 - Model version
Student finance policy for Advanced Learner Loans in England for each academic year since 2013
4.2.3 - Model task
To determine the Advanced Learner Loan application eligibility and entitlement.
4.2.4 - Model input
Advanced Learner Loan application and course data
4.2.5 - Model output
Advanced Learner Loan finance application eligibility and entitlement based on the information and evidence supplied by the customer on their application and the DfE about their course.
4.2.6 - Model architecture
Forward-inferencing rules engine using the RETE algorithm.
4.2.7 - Model performance
The Advanced Learner Loan assessment rules were tested across the various pre-production environments in a variety of ways:
• in all pre-production environments automated tests created targeted test data in order to ensure that the rules generate the expected outputs • in the test environments example test data is also created by the testing teams in order to ensure that the rules generate the expected outputs.
SLC has a rigorous testing approach which covers all areas of the test pyramid at various levels including unit, system, integration testing. Automated tests run as part of every release, a full and rigorous test phase takes place every year as part of the annual service launch this includes end to end, performance and user acceptance testing. The system has also undergone penetration and code review plus regular security scanning.
Formal sign-off from a disparate set of senior stakeholders is required prior to each annual service launch.
4.2.8 - Datasets
Advanced Learner Loan finance applications and course data provided by student and DFE.
In the pre-production environments test data is created by manual & automated tests in order to ensure that the rules generate the expected outputs.
In the test environments test data is also created by the testing teams in order to ensure that the rules generate the expected outputs.
The SLC operational teams have created a specific dataset of information suitable for their needs in the training environment.
4.2.9 - Dataset purposes
Validation - In the pre-production environments test data is created by manual & automated tests in order to ensure that the rules generate the expected outputs.
Testing - In the test environments test data is also created by the testing teams in order to ensure that the rules generate the expected outputs.
Training - In the training environment the SLC operational teams have created a specific dataset of information suitable for their needs.
Tier 2 - Data Specification
4.3.1 - Source data name
Advanced Learner Loan application and course data
4.3.2 - Data modality
Text
4.3.3 - Data description
Advanced Learner Loan application and course data
4.3.4 - Data quantities
The volumes of data used varies depending on the environment.
Since the launch for the Advanced Learner Loan service in 2013 for England there have been approximately 800,000 applications.
Data in test environments varies across different environments depending on the tests that are carried out there - automated, user and performance testing, etc.
4.3.5 - Sensitive attributes
The dataset contains personal data including personal identifying information about SLC Customers (students and contacts) including but not limited to: Name Date of Birth E-mail address Telephone Address National Insurance Number Passport Number or Identity Document information Bank Details
4.3.6 - Data completeness and representativeness
The production dataset uses information provided by customers as part of their Advanced Learner Loan application and course data provided by Dept. for Education so this data is complete and representative of the target population.
4.3.7 - Source data URL
N/A - Not a public dataset
4.3.8 - Data collection
The data was/is collected when customers apply for student finance, either online or on paper. This is the only purpose of the data.
Customer data (e.g. name, address) may already exist from previous student finance applications (e.g. for further or higher education) and can be updated/reused for subsequent Advanced Learner Loan applications.
4.3.9 - Data cleaning
SLC uses data provided by customers and DfE (Department for Education) without any pre-processing or cleaning.
SLC deletes unapproved applications data periodically to comply with GDPR.
Data in validated at the point of entry for online applications. Any data quality issues will be addressed via communication between student finance officers and customers.
4.3.10 - Data sharing agreements
SLC shares data with other government departments as part of the assessment process where required based on each individual application.
As part of the assessment process this can include: HMPO The Home Office Customers provide their consent to share this data as part of the application process.
4.3.11 - Data access and storage
SLC is responsible for the storage of the data in the Advanced Learner Loan platform.
Data in the Advanced Learner Loan platform is stored in accordance with the principles of the UK General Data Protection Regulation (GDPR).
All the data is encrypted at rest, encrypted when in transit outside SLC network and access is restricted via role-based access control.
Tier 2 - Risks, Mitigations and Impact Assessments
5.1 - Impact assessment
The Advanced Learner Loan platform is subject to annual updates based on changes to government policy. Each update to the rules engine is subject to Data Protection Impact Assessment (DPIA) review.
The latest DPIA assessment for the Advanced Learner Loan assessment platform was approved by the Information Asset Owner (IAO) in June 2025. This covered annual rollover and policy changes requested by government.
5.2 - Risks and mitigations
Information stored and processed by the SLC is valuable to bad actors. To mitigate any risk, all services that store or process information in the post-graduate assessment platform is subject to regular review by the SLC security teams to look for data risks, and systems have robust security protections and security tools regularly scanning for vulnerabilities and intrusion.