FSA Modernization RFI_071125_V4R.docx

CUI//SP-PROCURE/FED ONLY

Request for Information: Federal Student Aid (FSA) Technology Modernization Initiative Federal Student Aid July 21, 2025

Controlled By: U.S. Department of Education, Federal Student Aid, Kaegy Pabulos

Summary

Federal Student Aid (FSA), an office of the United States Department of Education (ED) provides more than $120.8 billion in grant, work-study, and loan funds each year to more than 9.9 million students attending approximately 5,378 postsecondary institutions. We ensure students and their families can benefit from these programs by

· informing students and families about the availability of the federal student aid programs and the process for applying for and receiving aid from those programs;

· developing the Free Application for Federal Student Aid (FAFSA®) form and processing more than 17.6 million FAFSA forms each year;

· accurately disbursing, reconciling, and accounting for all federal student aid funds that are delivered to students through colleges and career schools;

· managing the outstanding federal student loan portfolio and securing repayment from federal student loan borrowers;

· offering free assistance to students, parents, and borrowers throughout the entire financial aid process; and

· providing oversight and monitoring of all program participants—schools, financial entities, and students—to ensure compliance with the laws, regulations, and policies governing the federal student aid programs.

On July 4, 2025, President Trump signed the One Big Beautiful Bill Act into law, which introduces transformational changes to federal student aid programs and drives FSA to be agile in delivering innovative solutions for students, parents, borrowers, and our partners.

As a result, FSA’s technology must evolve into a customer-centric set of unified services that are readily available, secure, and always focused on continuous improvement. As technology continues to become more complex and interwoven, FSA seeks to modernize the way we deliver these core programs through modernizing our enterprise cloud hosting, applications, data integration, tools, and services. Additionally, FSA embraces purposeful innovation and strives to deliver exceptional services while practicing good stewardship of our limited resources. Hence, emerging technologies provide FSA with opportunities to reimagine our service delivery and technical capabilities.

The purpose of this Request for Information (RFI) is to gain a better understanding of—and potentially leverage—current and emerging industry capabilities to modernize FSA’s technology while enabling the successful implementation of the One Big Beautiful Bill Act. FSA is issuing this RFI solely for information and planning purposes, and it does not constitute a Request for Proposal (RFP) or a promise to issue an RFP in the future. This RFI does not commit the government to contract for any supply or service whatsoever. Further, FSA is not at this time seeking proposals and will not accept unsolicited proposals. Responders are advised the U.S. Government will not pay for any information or administrative costs incurred in response to this RFI. All costs associated with responding to this RFI will be solely at the interested party’s expense. Not responding to this RFI does not preclude participation in any future RFP, if any is issued.

Purpose The purpose of this Request for Information (RFI) is to gain a better understanding of—and potentially leverage—current and emerging industry capabilities to modernize FSA’s technology while enabling the successful implementation of the One Big Beautiful Bill Act. More specifically, FSA aims to gather insights from industry on solutions to achieve a modern, integrated, and secure FSA systems ecosystem that addresses the shortcomings of our current state of technology. To this end, FSA is seeking innovative approaches to

· modernize or replace FSA’s legacy systems;

· integrate siloed data across multiple systems;

· consolidate or coordinate disparate vendor solutions; and

· improve services to students and borrowers.

Additionally, FSA seeks input on whether a “greenfield” rebuild (i.e., developing a new system landscape from scratch); incremental improvements to existing systems; or a hybrid of both approaches will effectively meet the evolving demands and needs of students, parents, borrowers, and our partners.

It is important to note that lessons learned from past efforts and audit findings including the need for comprehensive planning, realistic cost/schedule estimates, robust testing, and strong oversight should inform FSA’s approaches. Hence, FSA encourages Respondents to reference these findings and propose solutions that address the documented weaknesses in FSA’s current technology environment.

FSA’s Technology Goals FSA will leverage the insights from this market research to inform and enable the following strategic objectives:

1. Streamline and integrate data infrastructure by creating a unified data architecture that breaks down siloes and provides a single source of truth across the student aid lifecycle. The modernized ecosystem should improve data flow between application processing, grant/loan origination, servicing, and analytics systems. FSA seeks to efficiently integrate new and existing data assets to support real-time data sharing and minimize batch file transfers that cause latency or downtime. By establishing enterprise data standards and governance, FSA aims to improve data quality and consistency across all systems and vendor-partners. In time, FSA plans to strengthen its enterprise-wide data platform by consolidating key information (e.g., student, borrower, program, and institutional data) and improve operational needs.

2. Improve system reliability and stability by enhancing the resiliency and scalability of FSA’s technology solutions. Modernized systems must provide robust performance during peak processing times (e.g., annual FAFSA cycles or loan servicing peaks) without failures or excessive user wait times. FSA aims to reduce unplanned downtime, errors, and instability that have affected legacy systems and recent rollouts. This strategic goal includes building resilience (e.g., cloud scalability, redundancy, and fault tolerance) so that critical services remain available to FSA customers. Additionally, FSA’s systems should be easier to maintain and update without introducing defects. Hence, a stable technology foundation supported by modern DevSecOps and testing practices will enable FSA to increase customer satisfaction and prevent disruptions for students, parents, schools, and lenders. FSA systems should also utilize Artificial Intelligence (AI) to streamline internal processes and automate repetitive tasks associated with student loan processing, servicing, and data management. AI supports the broader modernization by increasing speed and efficiency of FSA operations.

3. Enhance customer—including students, parents, borrowers, and partner institutions—experience and self-service by leveraging modern, agile, and user-centric technology. FSA aims to provide a seamless, one-stop digital platform centered around StudentAid.gov (or its successor) where users can accomplish all necessary tasks with a single login and unified interface. More specifically, this goal integrates functions that are currently spread across multiple systems or contractor portals. For example, a borrower should be able to view and manage all their federal student loans in one place even if those loans are managed by different servicers. Likewise, financial aid administrators at schools should have a single integrated partner portal for all program interactions. The modernized solutions should make the financial aid process simpler, faster, and more transparent—from completing the FAFSA form to making loan payments or adjusting repayment plans—by introducing intuitive web and mobile interfaces that provides personalized tools, faster response times, fewer errors (e.g., incorrect eligibility calculations), and proactive communication while leveraging artificial intelligence to improve the customer experience.

4. Liberate data analytics for decision-making and empower FSA leadership with timely, accurate, and comprehensive data to inform policy and operational decisions. Currently, fragmented data makes it challenging to perform oversight or glean insights across programs. FSA seeks to modernize its data architecture and engineering to enable advanced analytics—including predictive modeling and trend analysis—that can intelligently conduct proactive analysis and evidence-based policymaking. The solution should liberate data for analytics by consolidating data stores and providing modern business intelligence, reporting, and analysis tools. Additionally, the solution should support generating real-time or near-real-time dashboards and reports for program managers and external stakeholders; enhance oversight of contractors and partners through data transparency; and enable slicing and dicing of data for research and program evaluation. The solution should also use AI (e.g., machine learning predictive models) to analyze large student aid datasets for actionable insights including detecting and preventing fraud in financial aid processes. FSA aims to enable evidence-based policymaking and proactive program oversight by uncovering patterns or risks not readily apparent through traditional analysis.

5. Strengthen cybersecurity and data privacy by modernizing FSA’s information security posture and protecting sensitive data. FSA’s systems hold personally identifiable information (PII) for millions of individuals—including financial data and federal tax information—that are integral to government financial functions, which makes them high-value targets for cyber threats. FSA aims to continuously embed strong cybersecurity controls and privacy protections by design. This goal includes compliance with federal security requirements (e.g., Federal Information Security Modernization Act (FISMA), National Institute of Standards and Technology Special Publication (NIST SP) 800-53 controls) and privacy laws; robust identity and access management for users and administrators; data encryption at rest and in transit; continuous monitoring; and incident detection and response capabilities. FSA’s modernization objective is to protect the integrity, availability, and confidentiality of student aid data to the highest standards. The future state should allow FSA to more rapidly address vulnerabilities and adapt to emerging threats. Additionally, strengthening cybersecurity means safeguarding data privacy by ensuring that student and borrower data is used and shared in accordance with consents and regulations. Any third-party access (e.g., partners and contractors) should also be properly controlled and audited.

FSA’s Current State and Associated Challenges Summary FSA’s mission-critical operations rely on a complex suite of information systems that manage the student aid lifecycle from application through loan repayment. Several technology solutions are aging legacy systems, which were developed in silos for specific programs or functions. Over time, this has led to a fragmented technology environment with multiple databases and vendor-managed subsystems that are not fully integrated. While these legacy systems continue to function as the backbone of FSA’s delivery, these solutions introduce the following challenges that slow the delivery and increase complexity for FSA:

· Data Silos and Fragmentation: FSA’s current information architecture is fragmented across multiple platforms and databases. Each major business function (e.g., student aid application processing, loan origination and disbursement, loan servicing, and data reporting) has traditionally operated on separate systems with their own data stores. While FSA has made efforts to centralize portions of its data through an Enterprise Data Management and Analytics Platform (EDMAPS), its solutions do not yet cover the full student aid lifecycle or all data instantiations. Many critical data sets remain isolated in legacy systems or contractor-operated environments, which limits FSA’s ability to obtain a single, comprehensive view of a student or program. Additionally, these silos oftentimes create inconsistent or duplicative data; complications with data reconciliation; and challenges in performing enterprise-wide reporting and analysis.

· Multiple Vendor Platforms: Over the years, FSA’s incremental procurements have resulted in a technology ecosystem that is powered by multiple vendor-provided systems and services. For example, FSA currently contracts with multiple loan servicers that operate independent platforms (e.g., separate websites, separate servicing platforms, login credentials, customer service centers, and cybersecurity controls). The vendor fragmentation creates a complex and “matrixed” technology environment where integration across platforms requires extensive coordination and interface development. Additionally, managing changes or data exchanges in FSA’s current state involves numerous internal systems, partner systems, vendor-operated cloud environments, and batch file transfers that are resource-intensive and error-prone.

· Stability and Customer Impact: The limitations of FSA’s technology portfolio have directly affected stakeholders who are managing the day-to-day work that enables FSA to carry out its mission. Additionally, students, parents, borrowers, and partners often encounter a disjointed experience because data and functions are spread across different platforms. For example, a single borrower with multiple loans might need to interact with several interfaces including redundant accounts and inconsistent information across platforms.

· Business Continuity: FSA’s ability to undertake critical system upgrades introduces significant challenges in maintaining business continuity as FSA aims to minimize disruptions (e.g., downtime and technical issues) to critical student aid services such as application processing, loan disbursements, and loan servicing on which millions of students and borrowers rely. Additionally, FSA must ensure data integrity by safeguarding its vast, sensitive datasets through enabling robust data migration and validation processes to prevent any loss of historical records or corruption of student information during cutovers. Given the complexity of FSA’s current environment and the high risks associated with system failures during upgrades, these priorities demand meticulous planning, strong oversight, and contingency strategies to modernize FSA’s systems without sacrificing service reliability or data accuracy. For example, FSA must manage stakeholder expectations through proactive communication and change management including phased rollouts to maintain trust, reduce confusion, and iteratively deliver improvements and services.

· Partner Integration Challenges: Institutions of higher education (IHEs) have faced significant challenges when integrating with FSA’s digital ecosystem, which are especially acute for smaller institutions. These institutions often operate with minimal technical staff and may rely on legacy student information systems (SIS) that cannot easily interface with a new FSA platform, making integration efforts resource-intensive and dependent on manual workarounds.

FSA’s Current and Legacy Systems Overview FSA’s core business processes are supported by multiple information systems that was initially built for a specific purpose. These major systems manage the student aid lifecycle from application through loan repayment:

· Common Origination and Disbursement (COD) System: The COD system manages the origination and disbursement of all Title IV federal student aid funds (e.g., grants, loans, and work-study) to students and institutions. This system also operates as a backend database for tens of millions of annual applicant/borrower submissions on StudentAid.gov and a pass-through vehicle for loan servicing actions. COD was implemented in the early 2000s and centralizes many student aid transactions. COD interfaces with numerous external systems (e.g., school financial systems) and other FSA systems, often via batch data submissions. The COD system is complex so maintaining and enhancing COD under its current architecture presents challenges where some processes remain partially manual or require workarounds from FSA staff or our partners (e.g., institutions).

· Digital and Customer Care (DCC): The Digital Customer Care (DCC) solution provides infrastructure, application, and customer care technologies that support FSA’s services to over 17 million FAFSA applicants, 40 million borrowers, and 5,700 schools. A core component of the DCC contract is a cloud infrastructure and suite of statutorily required solutions (e.g., digital platform, marketing and communications platform, customer care tools including a customer relationship management tool, and design services) that enable over 40 million borrowers to access repayment programs. Additionally, the DCC solution also powers the Specialty Processing Subsystem (SPS), which applies programmatic rules governing programs including the Public Service Loan Forgiveness (PSLF) or Temporary Expanded PSLF (TEPSLF) programs, the TEACH Grant Program, and the Total and Permanent Disability (TPD) Discharge Program.

· Enterprise Data Warehouse and Analytics (EDWA) / Enterprise Data Management and Analytics Platform Services (EDMAPS) System: FSA has an Enterprise Data Warehouse and Analytics (EDWA) solution that pulls data from various sources for reporting. In recent years, FSA deployed a new Enterprise Data Management and Analytics Platform Services (EDMAPS) system under Next Gen. EDMAPS brings together data from many of FSA’s largest platforms into a more accessible environment for analysis. However, EDMAPS currently co-exists with legacy data stores and reporting tools. The integration is not seamless; and certain analytics or reports still require gathering data from multiple systems or rely on overnight batch updates. Additionally, data latency and quality issues persist, partly due to the lack of a single integrated data architecture.

· FAFSA Processing System (FPS): The FAFSA Processing System was deployed in late 2023 and replaced the legacy system, Central Process Systems (CPS). The FPS system processes FAFSA applications and determines initial student aid eligibility. Additionally, FPS handles around 17 million applications every year.

· Next Generation Data Center (NGDC): The NGDC hybrid (i.e., cloud and on-prem) ecosystem hosts and manages 28 FISMA systems including mission-critical systems like the Financial Management System, FSA’s Security Operations Center, and roughly a third of ED’s high-value assets.

· National Student Loan Data System (NSLDS®): NSLDS is a federal database that stores information on student loans and grants, including loan statuses, balances, and reports for oversight. NSLDS (the legacy version) was introduced in the 1990s and has grown to accumulate data on over 100 million student aid recipients and over 52 terabytes of data. It is a critical reporting system for schools, lenders, and policymakers. NSLDS’s initial technology is dated; FSA developed a modernized “loan data system” as part of Next Gen Initiative to replace the legacy NSLDS on prem instance and migrated the application to the cloud.

· Partner Connect: Partner Connect is a centralized portal for school partners, financial institution partners, FSA staff, and contractors involved in the administration of Title IV financial aid for postsecondary education. This system interfaces with partner institutions (e.g., colleges, guaranty agencies, and state agencies); and houses eligibility and oversight information about Title IV program participants including the FSA Participation Management system which controls user access for institutional partners. The Partner Connect tools are currently hosted through—and provisioned by—the Digital and Customer Care (DCC) solution.

· Servicing Systems (Loan Servicer Platforms including the Debt Management and Collections System (DMCS)): Student loan servicing is managed by multiple vendors that track borrowers’ loan balances, billing, and repayment statuses. Each servicing data structures and functionalities vary because they were developed by different vendors. FSA currently aggregates some servicer data for oversight through data feeds (e.g., to NSLDS or EDWA); but there is a lack of a unified and real-time servicing system. Additionally, the current servicing solution contains multiple data stores of borrower records, which introduces challenges for FSA and student loan borrowers including the accuracy of transferring borrowers from one loan servicing platform to another loan servicer platform in a timely manner.

FSA’s Cybersecurity Infrastructure Overview FSA uses an internal identity management system through Person Authentication System (PAS) and Access and Identity Management System (AIMS) for user authentication. Additionally, FSA maintains both security operations for its systems and coordination with vendors on their internal security operations. Hence, enforcing uniform security policies and monitoring introduces challenges especially with systems spread across various contractors and data centers. While improvements are in progress (e.g., enterprise-wide security architecture planning via FSA Zero Trust efforts), FSA’s legacy system constraints mean some older systems have security limitations, such as older encryption standards or access control models that don’t easily extend to modern identity federation.

Challenges With FSA’s Current State FSA’s current state leads to several pain points that this RFI and subsequent modernization efforts seek to address:

· Gaps in Integration: Because each FSA system was originally built to operate on its own, the integration among them is imperfect. Data must often be transformed and transferred between systems (e.g., moving FAFSA applicant data from FPS into COD for award origination; and then into servicer systems for student loan repayment). These interfaces are frequently batch-oriented, which makes it challenging to trace a single student’s journey in real-time across systems. Additionally, it is challenging to fully integrate all data in FSA’s current architecture, which means that some data discrepancies can occur if updates in one system are not immediately reflected in another. Industry best practices, like master data management, are also hard to implement because no single system governs core entities (e.g., student data, loan data, etc.) across FSA. Ultimately, these integration gaps result in feature release cycles that could take months to coordinate because of complex integrations, higher operational costs, and increase in staff effort for coordinating changes across platforms and software.

· Operational Complexity and Vendor Coordination: The multi-vendor environment means that FSA must coordinate changes across numerous vendors. For example, a policy change might require updates to the student aid application system, origination system, servicer systems, and data warehouse. This coordination is complex and introduces risks to implementation; hence, any modernization will need to either contend with this multi-vendor coordination or seek to simplify it by consolidating platforms.

· User Experience Fragmentation: Despite efforts to present a more unified front-end through StudentAid.gov, users still experience fragmentation behind the scenes. For example, a student applying for aid interacts with different systems when managing their loans; and these systems may not share the same interface or data in real-time. As a result, students and schools sometimes face confusion or delays because one part of FSA’s system does not have the latest information from another system. Additionally, improving self-service is difficult when information is spread out across FSA systems. For example, borrowers cannot currently see their full history of non-defaulted and defaulted loans together easily because defaulted loans reside in a separate system.

· Recent Challenges Highlight Existing Gaps: FSA’s current state introduces inherent risks that result in issues for the public. For example, the 2024–25 FAFSA solution was delivered late due to system complexity and integration with other systems. Additionally, the challenges with this implementation indicate that modernization in an environment as complex as FSA requires not just only new technology, but improved processes, governance, and possibly a fresh architectural approach to avoid simply replicating old problems in new forms.

Guiding Questions for FSA’s Future State Needs FSA invites interested vendors, technology integrators, and other experts to provide information, ideas, and recommendations on how to modernize FSA’s technology environment to address the current challenges and meet the objectives described in this RFI. Respondents should feel free to propose innovative solutions, architectures, and approaches. FSA is particularly interested in understanding from Respondents how a solution-based approach would handle the inherent complexity of FSA’s technology environment and whether such an approach envisions a complete rebuild (i.e., greenfield approach), an incremental modernization of existing components, or a hybrid approach. Please base your responses on the information noted in this RFI and your knowledge of best practices and successful case studies in modernizing large-scale government or financial systems while ensuring business continuity for millions of customers. FSA is also interested in gaining insights even if Respondents are not experts in addressing all of the challenges and areas stated in this RFI but have a novel idea or strategy on how we could integrate or fix a certain component of the problems. Specifically, FSA is seeking input on the following noted challenges and areas:

1. Overall Modernization Strategy and Architecture

a. Approach (Greenfield vs. Leverage Existing): Given the legacy challenges outlined, to what extent would you recommend a greenfield development (i.e., building a new system environment from the ground up, with minimal reliance on existing systems) approach, an incremental modernization approach (i.e., upgrading and integrating the current systems in phases), or a hybrid approach? Please explain your recommended strategy in detail. For example, if you are proposing a greenfield approach, how would you decommission or transition away from the legacy systems and migrate data with minimal disruption? If you are proposing to build on existing solutions, how would you overcome the current fragmentation and technical debt? Outline the high-level target architecture you envision (e.g., a unified platform vs. modular interoperable services) and why it suits FSA’s needs.

b. Integration of Multiple Systems and Vendors: Describe how your approach would manage or reduce the complexity of coordinating across multiple systems and vendor teams. To what extent would you consolidate platforms to reduce fragmentation? If multiple vendors or technologies are involved, how would you ensure all components work together as a unified solution (e.g., governance structure and use of open standards/APIs)? Provide any examples where you have integrated large-scale systems or achieved successful collaboration in a multi-vendor environment. Please also describe how your proposed AI solution(s) will integrate with FSA’s systems and vendors.

c. Risk Mitigation and Program Management: Large modernization projects are prone to cost overruns, delays, and performance issues. How would you mitigate these risks in your proposed approach? Discuss any methodologies or best practices that you would apply for project governance, requirements management, and schedule control. For instance, to what extent would you leverage agile development with iterative deliveries? What mechanisms would you put in place to ensure robust testing and quality assurance to prevent critical defects in production? How would you incorporate independent reviews or oversight to keep the effort on track? If possible, relate these strategies to the specific context of FSA (e.g., dealing with federal acquisition requirements and stakeholder review processes).

d. AI Technologies: Provide details on the AI approaches and tools in your solution including the types of machine learning models or algorithms (e.g., supervised/unsupervised learning, neural networks, deep learning), natural language processing tools, or other AI methodologies (such as large language models, computer vision, etc.) that can address FSA’s challenges. Indicate whether you would recommend leveraging any off-the-shelf AI platforms or custom models; and highlight the AI solution’s capabilities like predictive analytics, anomaly detection, or conversational AI. This technical depth will help FSA understand the sophistication and suitability of the AI solution for our needs.

2. Streamlining and Integrating Data Infrastructure

a. Data Architecture and Integration Plan: How would your solution break down the data silos in FSA’s environment and create an integrated data infrastructure? Outline your approach to enterprise data architecture for FSA. To what extent would you implement a centralized data lake that aggregates data from all FSA business processes or use a federated approach with interoperability standards? Describe how data would flow across FSA systems (e.g., application, origination, and servicing) in your design. For example, how will FAFSA applicant data seamlessly propagate to loan servicing and oversight systems in near real-time and eliminate the current reliance on overnight batch file transfers that lead to blackout periods?

b. Master Data Management (MDM) and Data Quality: With millions of student and borrower records spread across FSA systems, maintaining consistent and accurate data is a challenge. How would your solution establish master data management for key entities (e.g., persons, loans, schools)? Explain any tools or frameworks you would use to ensure that all systems reference the same core data and to reconcile existing duplicate or inconsistent records (e.g., borrower data appearing in multiple servicer databases). How will data changes be synchronized? Discuss how you would improve overall data quality, integrity, and timeliness.

c. Data Standards and Governance: How would you introduce or enforce data standards (e.g., data formats, taxonomies, and exchange protocols) across FSA and its partners? Please include any relevant experience in establishing enterprise data governance in a federated environment or examples storing, retrieving and utilizing significant quantities of unstructured data (e.g., loan payment histories in various formats).

d. Leveraging Modern Data Technologies: What technologies or architectural patterns would you utilize for FSA’s data layer? To what extent would you consider cloud-based data platforms, streaming data pipelines, and APIs? For example, to what extent would you employ a streaming integration platform to push updates in real-time between systems or a common data model that all components adhere to? How would you approach the integration of external partner data (e.g., data from schools, guaranty agencies, and federal agencies such as the Internal Revenue Service) in a secure and efficient manner?

e. AI Integration: Describe how AI solution(s) will integrate with FSA’s systems and data. Explain your recommended integration methods (e.g., APIs, data pipelines, middleware, etc.) and how you would ensure compatibility with FSA’s modernization approach since the AI solution should be capable of consuming and processing FSA’s data.

3. Improving Reliability and Stability of Systems

a. Architecture for High Availability: Describe how your proposed solution will ensure high reliability and system uptime even during peak usage or unexpected surges. How will you design FSA’s systems using a cloud-native and scalable architecture (e.g., microservices that can auto-scale and load-balance web services)? Explain any redundancy or failover mechanisms that will be built in to ensure that there are no single points of failure for critical transactions like application submissions or loan servicing. If a component does fail, how will the system gracefully degrade or recover without major interruption to users?

b. System Performance and Scalability: FSA systems must handle large volumes (e.g., processing millions of FAFSA forms within tight timeframes and servicing 40+ million borrowers). How will you ensure the modernized systems meet performance requirements with room for growth? Discuss any performance engineering practices such as stress testing, capacity planning, using content delivery networks, or caching strategies for frequently accessed data. If applicable, provide metrics or case studies from similar-scale systems that your team has implemented.

c. Change Management and Minimized Downtime: When rolling out updates or migrating from old systems to new, how will your approach minimize downtime or instability? For example, to what extent would you use a phased rollout with parallel operations so that legacy systems are only retired once the new ones are fully proven? Describe your strategy for data migration and cutover that ensures data integrity and completeness while avoiding extended outages. If you are proposing an incremental modernization, how will you de-couple components so that parts of the system can be updated without bringing down the entire environment? Additionally, outline how you would set up rigorous testing (unit, integration, user acceptance, and load testing) and a staging environment to catch issues early. How would your plan prevent a new system from going live with significant unresolved defects?

d. Standards, Maintainability, and Support: Clarify any technical standards or frameworks that your AI solution follows including use of open standards for data exchange, common data models, or AI ethics frameworks like the NIST AI Risk Management Framework. Additionally, provide your recommended maintenance and support model including will the AI models be updated or retrained over time to remain effective as policies or data evolve. Describe the vendor support available to assist FSA in operating the AI solution including knowledge training so FSA’s workforce can work confidently with any new AI solutions.

e. Operational Monitoring and Support: Once deployed, what is your approach to ensuring ongoing reliability? Discuss the tools or practices for monitoring system health (e.g., applications and infrastructure), alerting, and rapid incident response. To what extent would you implement a centralized operations center or dashboard for FSA to oversee all systems’ status? How would you use techniques like chaos engineering or automated recovery scripts to bolster resilience? Include how you would measure and continuously improve key uptime and responsiveness metrics (e.g., target service level agreements for system availability).

4. Enhancing Customer Experience and Self-Service Capabilities

a. Unified User Interface and Portal: Explain how your solution would unify the customer-facing experience for students, borrowers, and partners. What would the end-user interaction look like under your design? For example, to what extent can all services be accessed via a single secure portal or mobile app with a common look-and-feel? How will you integrate services (e.g., FAFSA application, loan counseling, checking loan balances, making payments, seeking help) that are currently separate into one cohesive interface? Provide any ideas for a streamlined navigation and workflow that covers the entire student aid journey.

b. Personalization and Self-Service Tools: Describe the self-service features you recommend implementing to improve user empowerment and satisfaction, including through the greater use of artificial intelligence. This could include interactive wizards or tools that enable the ability for borrowers to schedule payments or adjust repayment plans online; view their aid history and upcoming deadlines in a dashboard; update personal information; or upload required documents. How will your design make these features intuitive and accessible (e.g., mobile-responsive design and compliance with accessibility standards)? If possible, tie specific features to FSA’s goals including enabling borrowers to manage everything through StudentAid.gov without needing to log in to multiple servicer websites.

c. Integrating Support Services: A good customer experience relies on support when users have issues. How would your solution integrate customer support channels (e.g., phone helpdesk, chat, email, and knowledge base) into the user experience? For example, to what extent would you embed a chatbot or live chat that can help contextually as the user navigates the aid process? If a user transitions from self-service to assisted service (i.e., calling in), how will the system ensure continuity so the support agent seeing what the user was trying to do? Discuss how your approach can reduce the need for manual intervention by making the self-service functions robust while ensuring that human assistance is more effective when needed (e.g., through enabling unified customer records for support agents).

d. Experience for Partner Institutions: In addition to student/borrower-facing improvements, address the needs of FSA’s partners (schools, servicers, guarantors, etc.). How will your solution simplify interactions for financial aid administrators and other partner users? For example, to what extent do you propose enhancing our consolidated partner portal to simplify IHE’s administrative burden of compliance and reporting associated with Title IV program management? How would you streamline the onboarding of institutions especially those with limited to no technical staff? Outline any self-service analytics or dashboards that could be offered to partners to enhance transparency (e.g., see the status of all their students’ aid or compliance metrics).

e. Examples and Best Practices: Provide examples of user experience improvements that have been delivered for comparable large-scale public-facing systems (e.g. banking, insurance, or other government services). How did those improvements impact customer satisfaction or efficiency? How could those lessons be applied to FSA’s context?

5. Liberating Data Analytics for Decision-Making

a. Analytics Platform and Tools: Describe the components of your solution that will support business intelligence, reporting, and advanced analytics. For example, to what extent would you include a cloud-based analytics platform or data lake that consolidates data from all operational systems for analysis? What tools or technologies do you suggest for data analysis and visualization (e.g., an enterprise analytics software, artificial intelligence/machine learning tools for predictive analytics)? Emphasize how these choices will enable FSA to easily generate required reports (e.g., portfolio reports, compliance reports, and performance metrics) and to perform ad-hoc queries across the full data spectrum. Explain how your design makes data readily accessible to authorized analysts and decision-makers in FSA.

b. Real-Time and Proactive Analytics: In the future state, FSA wants to conduct proactive analyses and support evidence-based policymaking. How will your solution facilitate more real-time analytics or alerts? For example, to what extent can the system support dashboards that update daily (or intra-day) with key statistics (e.g., application volumes, call center metrics, and loan delinquency rates)? To what extent would you implement any analytics capabilities that allow FSA to detect issues early (e.g., spotting a spike in FAFSA submission errors or identifying trends in borrower behavior that might signal a need for intervention)? Discuss how data science or machine learning could be incorporated including developing models to predict which borrowers are at risk of default and which students need additional outreach. What platforms should FSA leverage for these activities?

c. Data Democratization and Governance for Analytics: Outline how different stakeholders would securely access data in your solution. FSA encompasses users from executives to program managers to analysts, each with different data needs. How will your approach allow authorized staff to get the data they need without heavy technology involvement (e.g., self-service querying or a semantic data layer)? Conversely, how will you ensure security and privacy in analytics including enforcement of role-based access so that sensitive personal data is protected? Address how you would maintain data lineage and quality for analytics to ensure that reports and decisions are based on accurate, consistent data (e.g., a robust data governance and tools to track data provenance).

d. Improved Oversight and Policy Outcomes: Provide suggestions on specific analytics or reporting improvements that would directly help FSA’s leadership and program oversight. For example, how could your modernized data solution improve oversight of contractors? How could your modernized data solution support policymakers (e.g., the ability to quickly simulate the impact of a policy change on program costs)? The intent is to show how liberated data can yield actionable insights. Please describe how novel analytics capabilities (e.g., natural language query of data or artificial intelligence-driven insights) can be applied to FSA’s goals.

6. Strengthening Cybersecurity and Data Privacy

a. Security Architecture: Explain how your solution will build a robust security foundation for FSA. Describe the security architecture you propose including any frameworks or models (e.g., Zero Trust Architecture). How will security be integrated into every layer—from network security and cloud infrastructure to application security—of the modernized systems? Provide details on identity and access management improvements including how to unify identity management across all FSA services with a single sign-on and multi-factor authentication for users. How will you manage privileged access for administrators? Include thoughts on whether FSA should migrate to a FedRAMP-authorized cloud environment or remain on-premises for certain sensitive data including how either option will be secured.

b. Data Protection and Privacy Compliance: FSA handles extremely sensitive data (e.g., financial information, Social Security numbers, federal tax information). How will your solution ensure that data is protected both at rest and in transit using strong encryption and key management? Discuss compliance with privacy and data protection regulations including how you would incorporate Privacy Act requirements, consent for data sharing, and data minimization principles. If your solution involves large-scale data integration, how will you prevent unauthorized access or use of data across systems? Address whether you propose techniques like tokenization or anonymization for certain data sets when used in non-production contexts (e.g., testing or analytics).

c. Security Operations and Monitoring: Describe the capabilities you would put in place for continuous monitoring, threat detection, and incident response. For example, to what extent would you recommend establishing a dedicated Security Operations Center for FSA’s environment if it is not in place? What security information and event management tools or services would you leverage to gain visibility into potential threats across all systems including vendor-operated components? Outline how monitoring would uniformly cover cloud services, on-prem systems, and third-party integrations. In case of a security incident or data breach, what incident response processes and technologies would you suggest to quickly contain and remediate issues?

d. Cybersecurity Best Practices and Certification: Provide insight into how you will incorporate government and industry best practices such as NIST cybersecurity framework adherence, regular vulnerability scanning and penetration testing, code security reviews (i.e., DevSecOps pipeline integration), and compliance audits. If your solution leverages cloud, discuss how you would ensure compliance with FedRAMP and ongoing authorization. FSA will require that any new systems meet at least the same level of security controls as our existing systems. Describe how you will rapidly achieve authority to operate (ATO) for new components without compromising thorough security reviews.

e. Resilience Against Evolving Threats: Cyber threats continuously evolve. How will your design enable FSA to adapt over time? For example, how would you quickly apply security patches across all components? To what extent will the architecture support modular upgrades or integration of new security tools (i.e., if a new identity verification technology is desired to counter fraud)? Describe any forward-looking security features such as advanced fraud detection for student aid transactions or monitoring for insider threats that FSA should consider.

f. Data Security and Privacy: Given the sensitive nature of federal student financial aid data, how would you enable security measures and compliance features of your proposed AI solutions? Consider how you would protect personally identifiable information and financial data in AI workflows (e.g., encryption in transit and at rest, secure APIs, access controls, etc.), and how you would ensure compliance with federal laws such as the Privacy Act and FISMA. If your AI solution involves cloud services or external platforms, specify adherence to FedRAMP security requirements and relevant accreditation levels for government data. FSA also values responsible AI practices. Please indicate how your AI solutions address ethical considerations such as bias mitigation and transparency in automated decisions, especially if algorithms will influence customer outcomes (e.g., eligibility flagging or personalized aid offers).

RFI Response Guidelines This is a Request for Information (RFI) to determine available sources and their capability to provide the products or services described within this RFI. This request for information does not constitute a solicitation and is not an indication that the government will contract for any of the items and services discussed in this notice. Submission of a response to this RFI is entirely voluntary. The voluntary submissions of answers to this RFI shall not obligate FSA to pay or entitle the submitter of information to claim any direct or indirect costs, charges, or other compensation whatsoever.

Any information considered proprietary should be noted via appropriate markings. The government will use such information only to inform and support any potential solicitation and contract or for such other purposes as described within this RFI.

A complete response to the RFI should include answers to all the questions below. Additionally, responses should demonstrate capability not merely affirm the respondent's capability (i.e., the response must go beyond the statement that, "XYZ company can provide O&M support").

Additionally, interested parties responding to this RFI should adhere to the following instructions to facilitate FSA’s structured review:

· Response Format: Please begin with a brief “Executive Summary” of your overall approach (no more than one to two pages). Thereafter, organize your response to correspond to the numbered topic areas listed in the “Information Requested” section above. You do not have to repeat the questions, but please label each section of your response with the corresponding topic name/number (e.g., 1. Overall Modernization Strategy and Architecture, 2. Data Architecture and Integration, 3. Improving Reliability and Stability of Systems, 4. Enhancing Customer Experience and Self-Service Capabilities, 5. Analytics Platforms and Tools, 6. Strengthening Cybersecurity and Data Privacy, and any additional recommendations). This structure will help ensure all key objectives are addressed. Supporting diagrams or tables are welcome where they enhance clarity; they will count toward the page limit, except for an optional appendix as noted below.

· Capability Statement and Company Information: Please provide a capability statement and the following information about your company (no more than one page):

· Company Name

· Your Company’s Primary Business Product or Service Line

· Commercial and Government Entity (CAGE) Code

· Address Including Telephone Number and Email Address

· Points of Contact

· Size of Business Pursuant to North American Industry Classification System (NAICS) Codes

· If applicable, state whether your company is Small Business; Woman Owned Small Business; Small Disadvantaged Business; 8(a) Certified; HUBZone Certified; Veteran Owned Small Business; or Service-Disabled Veteran Small Business; or a Large Business

· Capability Statement

· Page Limit: The response should be concise and focused, not exceeding 40 pages in total length (i.e., Letter Size: 8.5 by 11 inches, Font Size: 11 point and Font Type: Arial or Times New Roman). This limit does not include a cover page if you choose to include one or an optional appendix of up to 10 additional pages for supplemental material such as architectural diagrams, references, or case studies. FSA values quality of insight over quantity so please ensure all content is directly relevant to the RFI topics. The responses should provide specific and actionable information about your proposed solution.

· Inquiries: Provide your questions about the RFI and associated…