Recorded Webinar: Improving data integrity to address regulatory requirements6 May 2021
Financial institutions today face a global regulatory landscape characterised by rigorous and varied reporting requirements across their businesses. Reporting challenges include completing more data fields across more lines of business with greater frequency, adding complexity and cost.
At the same time, there is waning tolerance among supervisory bodies for errors, issues or delays – as illustrated by the indignance shown by many regulators during the early days of the global pandemic.
This heightened level of regulatory activity makes it more crucial than ever that financial institutions remain in control of their data. Most have no true golden source of their key data sets, making it difficult to reconcile data either internally or with their counterparties. Large firms are routinely having to deal with millions of exceptions every day. The cost and complexity of meeting regulatory expectations continues to rise, because the underlying data integrity that financial institutions require is just not there. Unable to rely on their own data, they are fighting a losing battle,. The volatility of markets during the pandemic has merely served to raise the visibility of the problem, and with regulators across all jurisdictions demanding more, firm need to act now to avoid an expensive and reputationally damaging regulatory disaster.
With regulators losing patience, firms need to gain control over their data – and demonstrate this to the regulator. This webinar explores how firms can tackle the cost and complexity of regulatory requirements at root source, by achieving data integrity across their organisation.
Key discussion points include:
- Tackling siloed, overloaded legacy systems working with multiple different data sources:
- Quantifying data quality issues and building a business case for addressing them.
- The ‘delusion of control’ – why your teams think they are in control of the data when in fact they are not, and how do you prevent this?
- Establishing a data control framework for new products/trading activity: Ensuring your controls can keep pace with front office innovation
- One single source of truth: How do you actually get to the point where you have a golden source that works?
- Why the last mile matters: What even a 1% error rate can cost your business and how you can reduce it further
Moderator: Andrew Delaney President and Chief Content Officer
More about our speakers:
Head of Data Governance & Analytics
Rockefeller Capital Management
Arvind Joshi is the Head of Data Governance and Analytics at Rockefeller Capital Management. Prior to this, he was the Data Management Lead at Scotia Bank reporting into the CFO and CDO, with responsibility for the Data Governance initiative/program for US Finance. Arvind was also at Deloitte Advisory and managed multiple engagements at BHCs and FBOs. At Credit Suisse Holdings (USA) Inc., Arvind led the CCAR data governance initiative and at Morgan Stanley he was responsible for defining, establishing and implementing data governance/data quality programs for Basel and CCAR compliance. Arvind also represented the CFO office in establishing “Enterprise Data Office” for regulatory compliance (DFAST/CCAR and BASEL).
Arvind has over 25+ years of experience in Fortune-500 companies with diversified and comprehensive understanding of technology, business and operations processes. Arvind has successfully led initiatives to improve data governance and data quality through effective implementation of data management methodologies and technologies.
AVP – Data & Analytics, Office of the General Counsel – Global Operations
Shailesh Mathankar is responsible for executing the Legal & Compliance Data Program at AIG to improve maturity of data management processes and enable shift from reporting to analytics. He has an extensive background in all things data. He started his career as a Database Administrator and grew into other aspects of data management such as Data Warehouse, BI/Analytics, Data Governance, Data Standards, Data Quality Management. Prior to joining AIG, Shailesh worked for 12 years at two Big Four Accounting firms leading and managing several data intensive programs across diverse sets of technologies.
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