Bank Artificial Intelligence–Governance–Risk Panel (BAIGRiP) Dataset.

The dataset consists of a balanced panel of 10 commercial banks observed over a five-year period (2020–2024), yielding 50 firm-year observations structured in long panel format with bank and year identifiers. It includes two constructed composite indices: an Artificial Intelligence (AI) intensity index capturing the extent of institutional AI adoption and deployment, and an Algorithmic Governance Structure (AGS) index measuring formal oversight mechanisms, model risk governance, and board-level technology supervision. In addition, the dataset contains a consolidated Panel_Dataset_Final sheet which serves as the master analytical file containing the structured, ready-to-use panel dataset for replication, econometric modeling, and governance–risk analysis.detailed financial control variables such as bank size (log of total assets), capital adequacy ratios, liquidity indicators, and profitability measures (e.g., return on assets), alongside credit risk proxies including non-performing loan ratios and related risk indicators. Income structure variables such as non-interest income ratios and diversification measures are also provided to capture revenue composition dynamics.  The dataset integrates raw financial information and processed index variables, allowing for replication, econometric modeling, and governance-risk analytics within a compact, balanced panel framework.