11:00, March 23 : Panel Discussion | Collaborating with Regulators for a Proactive Approach to Compliance

The regulatory landscape is evolving rapidly. Financial institutions are faced with increasing reporting and regulatory requirements and new rules are continually being released. How can you work together collaboratively between infrastructure, and regulator? How do you ensure that you’re delivering to regulators what they need to do their jobs? How can increased collaboration better equip you to handle the next wave of regulatory change? How can firms prioritize the commitments made on data to various regulators across the world?

Panelists will discuss:

• What approaches work best for wiser collaborations?
• How do you achieve greater collaboration internally for a more productive relationship with regulators?
• With increased levels of information being required, how can finance institutions and regulators work together to ensure regulators can handle in uptick of information?

12:00, March 23: Panel Discussion | Exploring the Next Evolution of LEI on a Global Scale

Many see LEI as the big great hope for aggregating information and managing counterparty risk, but there is still work to be done. As new rules come out of the Treasury, LEI is broadening use beyond derivatives. What does standardization look like on a global scale in 2016? How will LEI introduce new requirements for financial institutions? How has LEI reduced the problems it was intended to resolve?

Panelists will discuss:

• Determining LEIs for the most important entities
• Translating the natural keys and ways instruments are identified into the LEI
• Ensuring coverage is broad and complete so that it has value inside the bank as an identifier and so that items are tagged appropriately for regulatory reporting

2:00, March 23: Panel Discussion | Analytics Through a Risk Lens, Identifying Potential Risks

Financial institutions are just scratching the surface of accessing the potential of analytics. With non-discretionary data projects reaching a level of maturity, financial institutions are now looking to roll out discretionary data activities to improve profitability and reduce risk. With a centralized data model, there are more data points to analyze, how can this be used to reduce risk? How can data be used as an early indicator of clients in financial distress?

Panelists will discuss how to:

• Achieve more granularity over longer periods of time to meet new risk measures
• Get true leading indicators through inlaying data to determine well in advance if there will be a loss
• Minimize the proliferation of sensitive data to mitigate risk