Lack of Sectoral Risk Analysis Emerges as a Major Weakness in Nepal’s Financial Stability Framework

Nepal’s financial system continues to operate with a serious gap in sectoral risk assessment, raising concerns about long-term stability. While central banks in advanced and emerging economies rely on stress testing, forward-looking models, and granular industry data to anticipate systemic risks, Nepal’s regulatory framework remains constrained by limited information and incomplete analysis. This has left policymakers, banks, and investors navigating what experts describe as an “unknown unknown” environment.

Although Nepal Rastra Bank has recently begun publishing sector-wise non-performing loan (NPL) and provisioning data, analysts argue that such disclosures are only a starting point. These figures should inform deeper background research rather than serve as policy endpoints. Without comprehensive sectoral diagnostics, lending and investment decisions continue to be driven more by market imitation than by evidence-based evaluation.

This herd-driven behavior has already produced visible distortions. Excessive investment in garments, sugar, and cement industries—often without realistic assessments of demand, capacity utilization, or export potential—has intensified stress in the banking system. Similarly, housing loans are frequently assessed using uniform risk assumptions, treating prime urban areas such as Baneshwor in Kathmandu and remote districts like Darchula as comparable, despite stark differences in liquidity, resale value, and income profiles.

At the core of the problem lies the absence of independent, reliable sectoral data. Policymakers and lenders lack verified information on hydropower consumption patterns, cement industry utilization rates, or tourism demand split between domestic and international markets. As a result, regulatory decisions are often made in isolation—such as caps on electric vehicle lending—without a holistic understanding of actual demand, substitution effects, or usage intensity.

Directed lending policies further illustrate the challenge. Mandating a fixed share of credit to small and medium enterprises (SMEs) assumes that SMEs constitute a single economic sector. In reality, this category spans retail shops, workshops, transport services, hospitality, and micro-manufacturing. Treating such a heterogeneous group as one sector obscures risk differentiation and complicates meaningful policy evaluation.

The lack of official external data has also weakened credit appraisal practices. Banks remain heavily dependent on borrower-provided spreadsheets and projections when assessing corporate loans. Without authoritative sector benchmarks, even sophisticated financial models rely on assumptions that are difficult to validate, increasing the likelihood of mispricing risk and misallocating capital.

Historical patterns reinforce this concern. Nepal’s industrial expansion has repeatedly followed imitation cycles rather than strategic planning. Garment and carpet industries once expanded rapidly before contracting. Sugar mills multiplied without aligning with sugarcane supply. Cement plants—particularly clinker-based units in the plains—expanded despite rising import dependence. Similar cycles affected edible oil industries and, more recently, segments of tourism and hospitality.

Tourism presents another example of uncoordinated growth. Hotel capacity has increased based on optimistic projections, yet there is limited analysis of airport handling capacity, length of tourist stays, or domestic spending power. Without sector-wide demand assessments, capital continues to flow into projects whose long-term viability remains uncertain.

Despite these gaps, fragments of data do exist. The central bank collects extensive information through supervision, reporting, and site inspections—often exceeding what is available from national statistical agencies. However, limited staffing and institutional capacity have constrained the ability to convert raw data into actionable research. Managing an economy exceeding Rs 80 trillion with just over a thousand staff has stretched analytical resources thin.

This data deficit also undermines Nepal’s ability to attract foreign investment. Beyond investment promotion frameworks and one-stop service centers, investors seek credible sector outlooks. Claims of hydropower potential or tourism growth require annual projections of industrial consumption, export demand, and infrastructure readiness—data that remain fragmented or unavailable.

Experts argue that the solution lies in establishing an independent economic research institution, separate from both the central bank and political structures. Such an entity could consolidate sectoral data, conduct anticipatory analysis, and publish forward-looking assessments. By reducing uncertainty and transforming “unknown unknowns” into measurable risks, it would support better lending decisions, more effective regulation, and informed investment.

Ultimately, financial stability cannot be sustained in a data-poor environment. Without granular, credible, and forward-looking sectoral analysis, Nepal’s banking system will remain vulnerable to cyclical overinvestment and sudden corrections. Bridging the information gap is no longer optional—it is a prerequisite for resilient growth and credible policymaking.