The race to implement artificial intelligence at scale within financial institutions’ technology stacks has made it imperative that they ensure their data foundations are solid. Without trusted data, AI is a potential minefield of erroneous outputs, hallucinated responses and inaccurate analyses.
This compromises leaders’ ability to make well-informed decisions and poses the risk they’ll make errors that will compound as that output data is reused. Actions taken based on poor-data outputs also lengthen the time it takes an organisation to see a return on its AI investment – a factor that could have an impact on the C-suite’s approach to future technology project funding.
However, numerous surveys of financial firms show that while they have faith in their models, many are not so sure about the quality of their data.
It’s a matter that is taking on greater urgency as autonomous AI agents are deployed to carry out data-driven tasks with less human input. With reduced overview of data as it enters models, data managers are left to ensure that data is clean, accurate and complete earlier in the pipeline.
With observability tools offering monitoring capabilities to identify anomalies in data, it will fall upon specific technologies to intervene and shape data into a form that’s suitable for model ingestion.
In the first Data Management Insight webinar of the summer – entitled The ROI of Data Trust: Quantifying the Business Value of Data Observability – leading voices in the data industry will examine this vital aspect of AI deployment and scaling.
On the panel of experts, Jay Reilly, senior vice-president, sales – Global Centre of Excellence at Precisely will be joined by Christina Schack, head of data operations and strategy at Vontobel and Paul Barker, chief control officer – cross controls enterprise technology – at HSBC.
The discussion will be moderated by Data Management Insight editor Mark McCord.
The importance of sniffing out anomalies in data is apparent in the number of technology vendors now offering observability tools.
They include Acceldata, which won the the Best Data Observability Provider Award at Data Management Insight Awards USA in 2024, start-up Bigeye and established platforms like Snowflake and Ataccama, which took the Best Data Observability Provider Award at Data Management Insight Awards for Europe 2024.
Armed with the knowledge of where data errors exist, engineers can intervene with sophisticated pipeline tools to attend of integration, cleansing and metadata issues.
In the discussion, panellists will take on a range of topics, including:
- How the ROI of observability tools and initiatives should be measured
- The benefits and potential complications of leveraging AI to ensure data trust
- The core KPIs that data teams should monitor across their pipelines, what signals matter most and the reduction of false positives and alert fatigue
- The processes and challenges of fitting data observability practices into broader data management frameworks.
The ROI of Data Trust: Quantifying the Business Value of Data Observability webinar will be held on July 8 at 10:00am ET / 3:00pm London / 4:00pm CET. There is still time to register to join what promises to be a fascinating webinar.
Subscribe to our newsletter
