Avoiding financial instability: essays on bank performance and riskiness
Bibliographic record
Abstract
Financial stability is the ability of capital markets to perform their essential function, which is to channel funds to entities that have productive investments.Different issues regarding bank performance and riskiness cause friction in the financial intermediation process, shattering financial stability and increasing the chance of a financial crisis.As the maintenance of a sound financial system is important for economic development, we developed three essays covering gaps in the literature on bank riskiness and performance evaluation, whose correct understanding is important for a sound financial system.Firstly, we focus on bank opacity and evaluate whether macroeconomic variables can improve the forecast of the financial performance of banks by using accruals-based measures of banking performance (net-interest income, non-interest income, and loan loss provision) and the novel cash flow-based measures that act as a proxy of financial intermediation (credit and liability cash flow).The results from out-of-sample forecasts indicate that the macro variables can be used to forecast financial performance only when the cash flow-based measures are used to measure banking performance, reinforcing the importance of cash flow, which has been neglected by the banking literature for bank evaluation.The second essay analyses what is at stake with the banking system as banks are on the brink of losing non-interest income due to an increase in competition from fintechs.We show the relevance of non-interest income for banking profitability and if there is a compensatory effect to financial intermediation earnings in relation to bank profitability, which smooths earnings in economic downside, helping, thus, financial stability.Our findings suggest that non-interest income positively impacts bank profitability, decreases bank riskiness, and presents a compensatory effect to financial intermediation earnings in relation to bank profitability.Lastly, we find that non-interest income is more relevant to profitability than financial intermediation earnings for large banks.For the small banks, financial intermediation earnings are more relevant, which shows that larger banks shall be, at first, the most affected by the potential loss of non-interest income.The third essay evaluates whether banks act in a forward-looking way by increasing expected loss provision when there is contemporaneous loan growth.As accounting regulations around the world changed in later years to account for foreseeable credit risk; thus, it is crucial to assess whether the increase in bank riskiness with new loans is softened by a concomitant increase in expected loss provision.The results indicate that contemporaneous loan growth increases bank riskiness, but banks increase expected loss provisions respectively, which shows they act prudently regarding provisioning, benefiting, thus, financial stability.In addition, it was found that when loan growth occurs during higher financial uncertainty times, banks allocate more expected loss provisions to account for an increase in credit risk.Lastly, as the Brazilian banking industry is heterogeneous, we find that small banks set higher expected loss provisions than larger banks for a given increase in the loan portfolio.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".