Digital Transformation for Sustainable Public Finance in Africa

Africa’s economies traditionally relied heavily on external finance. In recent decades foreign aid has poured into the continent (about US$1.2 trillion over 30 years), with 23 countries (43%) classified as “aid-dependent”stias.ac.za. In some poor states aid inflows even exceed government spending. For example, Burundi’s aid received was about 145% of its central government budget in 2021ceicdata.com. By contrast, Africa attracts only a small share of global private investment: in 2022 FDI inflows were just $45 billion (≈3.5% of global FDI)unctad.org. Nevertheless, a few countries are extreme outliers (e.g. Namibia draws ~18.6% of GDP in FDItheglobaleconomy.com). Overall, many African governments remain vulnerable to volatile donor and FDI inflows. This underscores the urgent need to diversify finance: boosting domestic revenues and innovative instruments to fund SDGs in a sustainable waystias.ac.zaundp.org.

Aid, FDI and ODA Dependence in Selected Countries

Aid/ODA dependence: Numerous African states still depend on official development assistance for basic budgets and projectsstias.ac.za. For example, war-torn or low-income countries (e.g. Burundi, Central African Republic, Liberia, Somalia etc.) receive aid equal to large fractions of GDP. In Burundi’s case, ODA was 145% of government expenditure in 2021ceicdata.com. Overall, donor flows remain sizable: aid to Africa reached nearly US$60 billion in 2023stias.ac.za. Such dependency leaves governments exposed when aid shifts, as current global ODA is stagnating or declining.

FDI dependence: Private investment flows are growing but uneven. Africa-wide, FDI flows (~$45 bn in 2022) are modest (only ~3.5% of world FDIunctad.org). Moreover, a handful of countries capture most of it. Namibia (18.6% of GDP) and Liberia (17.2%) have the highest FDI/GDP ratios in 2023theglobaleconomy.com, reflecting large mining and oil projects. Others like Mozambique (13.0%) and Seychelles (11.2%) are also FDI-hightheglobaleconomy.com. In contrast, large economies such as Nigeria and South Africa attract big absolute FDI volumes but low FDI/GDP shares. High FDI is double-edged: it brings capital but can crowd out local industry and is prone to commodity cycles.

Composite profiles: Countries like Ghana and Kenya receive moderate amounts of ODA and FDI, whereas others (e.g. Ethiopia, Uganda) rely on concessional debt and donors for infrastructure. As an example, Ghana’s tax-to-GDP ratio is only ~14% (2021)undp.org, below regional targets, meaning it still leans on external finance for social programs. In sum, Africa’s financing mix varies: some states are aid-heavy (Burundi, Mozambique, Rwanda at times); others attract investment (Egypt, South Africa, Namibia); but all face pressure to boost domestic resource mobilization for SDGs.

Case Study: Kenya

Kenya, a lower-middle-income country, provides an illustrative case of pursuing self-reliance via digitalization. Though Kenya still receives donor grants (in health, education, infrastructure), it has invested heavily in tech-driven finance reforms. The Kenya Revenue Authority (KRA) has digitized tax collection (the iTax e-filing system) and automated customs, with the aim of increasing the tax-to-GDP ratio from its previous ~13% toward the 20% benchmark. Importantly, Kenya is now piloting AI and data analytics for tax enforcement. As reported in 2024, KRA plans to use AI/ML “to analyze vast data sets to identify tax evasion patterns, optimize allocation, and predict future revenue streams”peopleofcolorintech.com. The Commissioner General notes this will boost tax collection and transparencypeopleofcolorintech.com. Similarly, Kenya’s Cabinet Secretary has highlighted that “AI and data analytics can help tax authorities boost compliance, improve risk profiling, and forecast revenues more accurately”peopleofcolorintech.com. These steps, along with electronic invoicing and faster customs clearance, aim to broaden the tax base (including Kenya’s large informal sector) and cut leakages.

Beyond revenue, Kenya aligns planning with SDGs through its Vision 2030. Budgets follow a medium-term strategy linked to development goals (similar to results-based management approaches). Digital platforms (e.g. integrated financial management systems, open-budget portals, e-procurement) are being strengthened to track spending efficiency. For instance, Kenya’s adoption of the Government Integrated Financial Management Information System (IFMIS) and e-procurement has improved budget execution transparency. While Kenya still leverages external finance (e.g. World Bank loans, P4R grants), its case shows how innovation can reduce aid dependence.

Digitalization and AI for Revenue & Expenditure

Figure: Finance practitioners from across Africa gather at a CABRI conference on digital public financial management, underscoring the continent’s commitment to tech-enabled PFM reformcabri-sbo.org.

African countries are increasingly applying digital public financial management (PFM) innovations. Foundations such as e-tax, e-procurement, digital ID, and interoperable databases are being built out to improve revenue and expenditure efficiency. A recent CABRI/ODI conference emphasized that governments are leveraging Digital Public Infrastructure (DPI) – integrated systems like payment platforms and data registries – to modernize PFMcabri-sbo.org. For example, South Africa’s digitized social grant payments and Zambia’s new electronic tax platform were cited as leading innovationscabri-sbo.org. In general, digital finance reforms across Africa include:

• Modernizing revenue administration: Many treasuries are upgrading tax systems with automation and mobile technologies. UNDP notes that “modernization of tax administration systems” and adoption of digital payment platforms are core reformsundp.org. Kenya’s AI initiatives (above) are one example. Others include (a) linking national ID to taxpayer registration (Ghana TIN-Ghana Card integration) and (b) enabling e-invoicing and mobile-money transaction monitoring. These tools help capture revenues from digital economies and informal sectors.

• Enhancing transparency and controls: Expenditures are being made more transparent via online budgets and audit systems. According to the 2023 Open Budget Survey, African countries have improved average transparency scores (to 38/100) by publishing citizen budgets and fiscal reports, though still below world averagesundp.org. Complementing this, many governments are deploying e-procurement portals and payroll audits. For instance, blockchain pilots are used to track spending: Guinea-Bissau in 2024 launched a blockchain ledger to manage its public wage bill in near-real timeimf.orgimf.org, making salaries and pensions fully auditable. Ghana has similarly announced plans for a blockchain-based government system to secure all public datatechpoint.africa. These platforms help catch fraud (no more “ghost workers”) and ensure funds reach intended targets.

• Strategic planning and fiscal data systems: Digital dashboards and integrated fiscal databases enable better policy planning. Countries are linking Ministries of Finance and Planning through common data systems. Aligning with Results-Based Management and SDG trackers, governments use ICT to tie budget allocations to outcomes. For example, systems for SDG budget tagging are emerging: researchers demonstrate that AI/NLP can automatically label spending against SDG categories to speed up SDG-aligned budgetingcambridge.org (though with caveats about local customization). Data-sharing across revenue, debt, and development ministries is improving through national portals and e-governance platforms, enabling cohesive SDG monitoring.

Digital PFM Tools & AI Models

Practical digital tools can accelerate this transformation:

• AI-powered tax systems: Tax authorities can integrate machine learning for fraud detection and forecasting. Kenya’s KRA examplepeopleofcolorintech.compeopleofcolorintech.com shows how AI can flag evaders and predict collections. Similarly, experimental models (e.g. deep learning forecasting) have proven effective at projecting quarterly tax revenues. Such systems reduce manual audits and improve compliance.

• Blockchain tracking: Secure ledgers are being tested for public finance. Ghana’s commitment to a blockchain governmenttechpoint.africa and Guinea-Bissau’s wage blockchainimf.org illustrate how distributed ledgers can make all fiscal transactions transparent and tamper-proof. A conceptual diagram of a blockchain network is shown below, highlighting how each change in the public record is cryptographically linked and visible across nodes.

Figure: Conceptual blockchain ledger for government finance. Each transaction or record (represented by blocks) is securely connected. This ensures immutable audit trails for budgets, salaries and procurementsimf.orgtechpoint.africa.

• Open budget dashboards: Mobile-friendly portals and open-data apps (like Nigeria’s OpenTreasury or Kenya’s integrated budget site) empower citizens and analysts to monitor public spending. These dashboards can be built on GIS or mobile apps to visualize budget execution and SDG performance in real-time.

• Anomaly detection in procurement: AI models can flag irregularities in large contracting datasets. For example, algorithms using pattern analysis can identify overpricing or suspicious bid clustering. Studies note that “AI-powered supplier scorecards” and blockchain procurement systems help track performance and share information across agencieszawya.com, reducing corruption.

• SDG budget tagging (NLP): Machine learning can automatically classify budget lines by SDG relevance. Research shows AI achieves high accuracy at labeling expenditures to SDGscambridge.org. This speeds up assessment of SDG spending commitments in finance ministries. Nevertheless, caution is needed: pure AI needs local input, as one study warns governments “cannot rely solely on AI tools and off-the-shelf taxonomies”cambridge.org. The best practice is a hybrid: initial NLP tagging followed by expert review.

• Predictive fiscal analytics: Governments can apply predictive modeling to forecast revenues and expenditures. As Kenya’s tax official noted, AI “will analyze vast data sets… and predict future revenue streams”peopleofcolorintech.com. Techniques like time-series forecasting and causal modeling (using data on prices, trade, remittances) allow ministries to produce more accurate budgets and early warning of shortfalls.

Integration with RBM and SDG Frameworks

These digital PFM innovations must align with existing management systems. Many African countries already employ Results-Based Management (RBM) and national SDG tracking platforms to evaluate outcomes. For example, Kenya and Ghana have Performance Agreements and budget-program links to sectoral results. Digital tools should feed into these frameworks, not operate in silos. Integrating e-procurement and e-tax data with SDG dashboards and medium-term plan monitoring platforms is key. Likewise, fiscal transparency initiatives like Open Government Partnerships or the African Peer Review Mechanism complement digital PFM by requiring accessible data on development spending. In practice, this means linking databases (tax records, treasury, social programs) so that an SDG indicator (say, school enrollment) is automatically updated when the corresponding budget is spent. AI systems should be embedded into planning ministries: for instance, automated SDG tagging cambridge.org outputs could populate national SDG reporting tools, while anomaly alerts could be incorporated into audit committees.

In sum, digital public finance solutions must interoperate with overall public administration platforms – from statistical offices (for SDG data) to donor coordination systems. To succeed, governments and partners should adopt interoperability standards (e.g. APIs between e-tax and budget systems) and coordinate through frameworks like National Financing Commitments and Integrated National Financing Frameworks (INFF). This ensures that enhancing PFM with technology reinforces – rather than bypasses – planning and accountability processes.

Measuring Systems Change

To track progress, the following indicators can be monitored:

• Governments adopting AI/digital PFM tools: Count how many African countries formally deploy AI-enabled tax systems, blockchain in PFM, e-procurement platforms, or open-budget dashboards. For example, a useful milestone is the number of UNDP/World Bank CoEs (Centers of Excellence) or GIFT (Global Initiative for Fiscal Transparency) signatories.

• Integrated data systems: Track the number of interoperable fiscal data platforms (e.g. national financial management systems that interface with tax/customs/regional data systems). Another metric is the number of ministries/agencies sharing centralized databases (for instance, joint revenue-authority–finance ministry platforms).

• Digital transaction share: Measure the percentage of government payments and revenues processed electronically. This includes share of public procurement using e-tendering, share of VAT filings done online, and proportion of social transfers disbursed via digital payments. A rising trend (e.g. >80% digital transactions) would signal deep PFM reform.

• Revenue mobilization outcome: While longer-term, improvements in tax/GDP ratios or reduction in ODA share of budgets can gauge fiscal impact. IMF analysis suggests that better admin could yield an additional 3–5% of GDP in revenuesundp.org; monitoring actual tax performance against this benchmark is informative.

Collectively, these metrics form a dashboard of system change. They can be integrated into UNDP’s Sustainable Finance Hub reporting: for instance, counting UNDP-supported digital finance projects in countries, or tracking adoption of its recommended tools. Over time, such indicators will show whether African PFM is truly transitioning from fragmented, manual processes to a data-driven, integrated digital architecture that underpins self-reliant SDG financing.

Key Findings

• High external dependence: Many African states are heavily dependent on external finance. For example, roughly 23 countries are “aid-dependent” (ODA financing a large share of budgets)stias.ac.za. In extreme cases (e.g. Burundi), ODA exceeds government spendingceicdata.com. Private investment flows are also uneven: Namibia’s FDI is ~18.6% of GDPtheglobaleconomy.com while the regional average is under 4%. Such reliance poses risks as donors reorient and global shocks (pandemics, rate hikes, commodity swings) hit.

• Shift to domestic and innovative sources: To achieve the SDGs, African countries must mobilize domestic resources. Digital technology is a key enabler. For revenue, smart tax systems (e-tax, e-invoicing, integration with digital IDs) can raise compliance. For example, Kenya is using AI/ML in its tax authority to detect evasion and forecast revenuespeopleofcolorintech.compeopleofcolorintech.com. Countries are also exploring innovative finance (diaspora bonds, local capital markets) to complement digital tax gains.

• Digital PFM successes and examples: Concrete innovations already show promise. South Africa’s digital social-grant platform and Ghana’s growing use of biometric/payroll systems have reduced leakages. African governments are piloting blockchain for finance: Guinea-Bissau’s new public wage ledgerimf.org and Ghana’s announced blockchain government initiativetechpoint.africa aim to secure spending data. Open-budget dashboards are expanding citizen oversight of finance. A recent CABRI dialogue highlighted these trends, urging more adoption of DPI tools across the continentcabri-sbo.org.

• AI models for governance: AI and data analytics can tackle public finance challenges. Anomaly-detection algorithms can flag corrupt procurement bids, as seen in e-procurement analyticszawya.com. Machine-learning classifiers can automatically tag budget items by SDG alignmentcambridge.org. Predictive models enable more accurate fiscal forecasting (e.g. projecting tax revenue trends). However, experts caution that AI must be adapted to local contexts – governments “cannot rely solely on AI” without human expertisecambridge.org.

• Integration with SDG/RBM frameworks: Digital tools should complement existing planning systems. Governments should link new PFM platforms to results-based budgeting and SDG-tracking mechanisms. For example, automated SDG budget tagging feeds directly into national SDG monitoring. By aligning AI/IT platforms with their development plans (e.g. through Integrated National Financing Frameworks), countries ensure technology strengthens rather than bypasses accountability.

• Proposed measurement framework: Progress can be gauged by indicators such as the number of countries deploying AI-enabled tax/custom systems, the number of integrated fiscal data platforms, and the share of government transactions done electronically. These metrics (alongside fiscal outcomes like rising tax/GDP ratios) provide a transparent way to monitor the system-change envisioned by the UNDP Sustainable Finance Hub in Africa.