How M&T Bank ensures data quality as it implements gen AI

Core Insights - The integration of generative AI in banking necessitates a focus on data lineage to ensure data accuracy and trustworthiness [1][11] - Banks face operational, compliance, and reputational risks if data lineage and governance are not properly managed, potentially leading to lawsuits and financial losses [4][5][11] Data Governance and AI Strategy - M&T Bank's Chief Data Officer emphasizes the importance of a robust data strategy alongside AI strategy, highlighting the interdependence of data quality and AI success [2] - The bank has initiated a data lineage initiative and established a data academy to enhance data governance, with 2,000 employees trained so far [12][13] Generative AI Implementation - M&T Bank initially restricted access to large language models to protect sensitive information but later partnered with Microsoft Copilot for generative AI applications [6][7] - Approximately 16,000 of the bank's 22,000 employees utilize generative AI for tasks such as drafting emails and summarizing calls, resulting in increased efficiency [7][9] Data Lineage Tools - M&T Bank employs data lineage software from Solidatus and Monte Carlo to create a comprehensive repository of data, enhancing the bank's ability to interrogate and analyze data [14][15] - Solidatus integrates with various databases and business intelligence tools, facilitating the understanding of data flow and lineage [15][16] Future Directions - The bank aims to integrate data lineage with generative AI models to ensure that the data used is internal and governed, enhancing accountability [18][20] - There is an expectation of increased value from future integrations between data lineage platforms and generative AI providers [18][19]