FIMA Connect Virtual Event 

For the last 4 years, the CDO and Data Leader’s Private Boardroom has been a highlight of FIMA and we’re delighted to connect the community virtually! This is an exclusive, invitation-only meeting for CDOs from top banks and asset management companies to share solutions and devise strategies to further advance the data agenda. Connect with peers and industry leaders to share ideas and successes along your data journey.

What a way to start your day! Kick off your FIMA Connect Virtual experience by joining your fellow financial services executive peers in an informal speed networking activity. Like speed dating, you’ll have 5 minutes to meet with 1 or 2 executives before rotating to the next session, allowing you to meet many peers in the process. Starter questions will be provided to help break the ice, so what are you waiting for? Don’t miss this chance to expand your network! This session is limited to attendees at financial institutions only.

As the demand for data grows in financial services, firms are leveraging cloud to speed up analytics, turning attention to enabling digital customer journeys and aligning with business priorities to deliver value across the enterprise. Yet challenges remain with a lack of data awareness and a lag in organizations using data to transform their organizations. By creating a data driven culture and increased data awareness, data consumers can further explore data and extract insights to deliver business value and grow revenues.

Panelists will discuss how to engage the business around data, including:

• Methods to increase data awareness and literacy
• What change management approaches motivate people, and what doesn’t work
• Communicating the value of data initiatives, aligned to business priorities
• How to create a storyboard based on business outcomes
• What KPIs are meaningful and how to align KPIs with the business

Data governance is foundational for not only reporting, but also advanced analytics and AI. Unfortunately it’s been an ongoing pain point for this industry, with few wanting to take ownership of the data, complicated by legacy systems and legacies of culture. With the shift to a hybrid cloud and ongoing security concerns, well governed data has never been more critical.

Panelists will discuss how they’re driving their programs forward, including:

• Security and robust governance policies to govern data in a hybrid cloud environment
• Integrating governance with the project lifecycle and connecting basic activities to strategic advantage
• Prioritizing efforts on regional and global levels to drive governance globally
• Keeping up the momentum of data governance programs as a way of life

Self-service is often touted as the holy grail of analytics - allowing users to discover and access data without having to ask IT to create them a data mart or otherwise extract and export the data. The challenge is not just to provide access to the data - there are tools that do this already - but to do this in a managed and governed way so that you can trust the output of the analysis. Without this, we end up with the fabled 'Tower of Babel' with no standards and no governance.

Building self-service capabilities on a trusted foundation is the key to successfully unlocking your data assets and enabling analytics innovation. Data Virtualization provides a data access platform that allows users to access the data that they need, when they need it. A Data Marketplace, built on top of this proven technology and exposing consistent and governed data sets to users, provides the trusted foundation for a successful self-service analytics initiative.

This session will explore:

·        The promise and pitfalls of self-service analytics initiatives

·        How a Data Marketplace, built on top of a Data Virtualization platform, can provide the trust and governance that is needed for these initiatives to succeed

The long awaited solution to the illusive data ROI has arrived. As the demand for analytics continues to increase, there are opportunities for the data organization to be more tied to business outcomes, and in the process create a strong ROI. But in order to capture this value, changes to data management are required. Peter Serenita, SVP & Chief Data Officer, Scotiabank has reengineered the data process to fit with the time to market iteration mentality and reduced tolerance in terms of perfection of the analytics group. Hear how he and his team are aligning with analytics, including:

• Provisioning data for analytics users to have line of site into the provisioning process
• Matching the data process with the consumer demands
• Introducing automation and machine learning to shorten delivery time

Financial services organizations are competing in a time of unprecedented change and must adapt or face consequences. The most innovative businesses are using the existing data in graph format to drive deep-link analytics as a way to increase profits, improve customer satisfaction, and find and stop fraud and financial crimes.

Join us as we share the case studies of how 7 out of the top 10 banks have used TigerGraph and how graph data has impacted Financial Industry use cases.

·        Integrating data across multiple stores, silos, and external data sets using data deduplication, and entity resolutions techniques at massive scale and speed (Billions of entities in short time windows) 

·        Focus on Data privacy and compliance on the interlinked datasets for business intelligence operations, LOBs, and fraud applications.

·        Driving value from data using deep link analytics, pattern detection at scale of terabytes in real-times.

·        Standardize easily to the schemes like FIBO

Across the industry, firms are eliminating on-prem data systems and migrating systems and applications to the cloud to meet the new demands of the future. With decades of legacy architecture, most organizations will have to function in a hybrid state for several years. How can you make this transition as seamless as possible for the organization? Find out how to ease this transition, including:

• Understanding what capabilities you need in-house to migrate to the cloud
• Knowing which cases should and shouldn’t be on the cloud
• Prioritizing applications for migration, including good enough vs. perfect state
• Addressing data retention concerns pre-migration to establish guardrails to cost optimize cloud investments
• Managing global organizational complexity, including different jurisdictional requirements and permissioning
• Embedding data policies in a more automated fashion to processes that control data in the cloud
• Standardizing data that is coming in, including employing master data management and data quality checks

Since the morning was jam-packed with detailed presentations and thought-provoking panel discussions, here’s your opportunity to be part of the discussion! Join a group of your financial services peers to share ideas and new best practices in an intimate virtual environment.

1.      From Chaos to Coordinated: How Advanced Tooling & Automation Improves Data Intelligence

Join this conversation to understand:

• Stages of data chaos
• Challenges to better visibility
• Using automation to centralize and organize
• Flexibility to make a difference regardless of your technology stack

We’ll answer key questions, including:

• Getting started (crawl, walk, run)
• What about data governance?
• What about compliance?
• How long does this all take?

Sam Benedict, VP of Solution Strategy, erwin by Quest

2.      Say Goodbye to the Rising Costs of Poor Data Quality Processes with Data Lineage

Data quality issues cost businesses millions of dollars each year in both lost revenue and direct or indirect costs associated with poor processes. Join the session and learn:

• How a proper data lineage solution optimizes and improves the efficiency of data quality processes
• How to achieve more with your existing data quality budget
• How poor data quality tarnishes your reputation
• How to eliminate the costs of manual processes surrounding data quality and root-cause analyses

Improving data quality processes will help you:

• Keep ahead of the competition
• Achieve full regulatory compliance
• Win customer trust
• Save time, money, and resources by eliminating the manual processes surrounding data quality

Ernie Ostic, SVP, Products, MANTA

3.      A Data Driven Approach for Achieving a Trusted Customer Experience

As organizations are expanding their use and monetization of data, they being held accountable to protect the data in their control and are challenged to establish mechanisms to effectively challenge and sustainably oversee risks associated with the data. These challenges are exacerbated within organizations by unclear lines of authority and overlapping corporate agendas

The session will cover:

• Leading practices on how to define and achieve the “Standard of Care” for information assets that are critical for business decisions.
• A risk-based approach for data protection and compliance that will turn data from a liability to into an enabler for better business decisions
• Address questions like “I need to know where my customer and employee personal data is and how it is being used to comply with various privacy regulations?”

Executive Speaker, KPMG

This is your opportunity to meet fellow women in data peers from financial institutions and create new connections. During this structured meet-up you’ll have the opportunity to outline your business priorities, reveal pain points and share recent success stories. You’ll come away feeling inspired, supported, and ready to take on your next big idea. This session is limited to attendees at financial institutions only.

Space is limited to 15 digital banking executives.

Hosted by: Julia Bardmesser, SVP, Head of Data, Enterprise Architecture and Salesforce Development, Voya Financial 

Executive Speaker, SmartStream

Data permeates every part of the organization, with added security concerns as the industry migrates to the cloud. Data breaches continue to rise, and in the case of a breach, you’re entrusted to govern it. How are you addressing the question of access? How is data governance stepping up to meet evolving requirements?

Find out:

• What combinations of enabling technologies and policies are most effective
• Effective controls for data, including authorization, encryption, tokenization and purging
• Data permissioning to manage data loss prevention to guard against intentional or unintentional leakage of data
• How to strike a balance of protecting client data while supporting innovation
• Which categories of sensitive data need to be protected at a higher standard

The financial services industry is under great pressure to cut costs while maintaining high levels of service and perfect regulatory compliance. Disparate data and systems, as well as paper-intensive processes slow this effort and as a result, teams are unable to focus on other high-value client-facing services. Financial institutions must nurture cost-efficient growth, while competing with Fintechs that don’t have burden of legacy infrastructure, data and systems. This is where Intelligent Automation helps organizations to efficiently manage their data and handle their operational tasks. 

Find out how to capitalize on these new tools, including:

• Leveraging software bots to mimic day-to-day routine tasks
• Advancements in data science that make data ingestion, curating, and normalization, as well as model testing and evaluation simple and efficient
• Understanding how to reduce manual efforts (and associated costs), assure better compliance, increase speed and accuracy of products and services, reduce risks, and improve customer service
• Learn how cognitive automation, artificial intelligence, and machine learning can automate a wide variety of end-to-end processes, including underwriting, loan processing, account set-up, and KYC

Financial institutions have made big investments in the data lake, yet many are now seeing the limitations of running operational data in the lake. There is a need for the next level of architecture evolution in the data lake. This is where data mesh comes in to break down the silo between the lake and operational systems and make data more meaningful. Douglass Stewart, Head of Vanguard Data Office, Vanguard is looking to the future of data management, which is decentralized. Hear how Doug and his team are implementing data mesh to work toward more decentralized data management, including:

• What data mesh means for structuring, controlling and iterating
• Building out microservices architecture, treating data like software
• Leveraging blockchain as a system to govern the data
• Reducing risk by creating standards for metadata and quality around data products 

Interested in demonstrating thought leadership as a keynote presenter? Contact adrienne.bills@wbresearch.com

A recent study by NewVantage Partners found that while investment in AI is high and continues to increase, only 24% of respondents report their organizations as becoming data-driven. This begs the question, where do these technologies work and where is it hype? What analysis can be done to do subsequent tests that you didn’t write the rules for?

Panelists will discuss:

• The current scope of applications for AI and machine learning
• How and when practitioners need to be involved
• Methods to speed up rule creation for data quality
• How to build standard governance, oversight and controls for risk management

Interested in demonstrating thought leadership as a keynote presenter? Contact adrienne.bills@wbresearch.com

It’s been over a year since most of us last saw our colleagues in-person, but the initiatives haven’t stopped. Data management initiatives are frequently multi-year projects with significant investment and measurable KPIs, but how do you keep up the momentum with a diversified, remote workforce? How is data management impacted by the rise in phishing attempts and cyber security threats? Hear how data leaders are keeping up the momentum while remote, including:

• What it means to do data management remotely, and unexpected benefits
• Technologies to fill in the gaps when there is more recorded documentation
• Structuring and librarying information to ensure it doesn’t get lost in an internal wiki
• Transitioning from one technology to another and the implications
• Learning from the challenges of data management while remote

As the demand for data continues to increase, the data organization is under pressure to provide data solutions to meet evolving business demands. Knowledge graphs capture the relationships between different data points to extract maximum value. David Newman, SVP, Head of Enterprise Knowledge Graph Solutions for Wells Fargo has been leading and advancing knowledge graph innovation at Wells Fargo over the last few years. Hear his insights on how to:

• Communicate the value of knowledge graphs to help the business understand a new paradigm of data
• Leverage customer focused knowledge graphs for enhanced customer 360
• Get a clear cut view for basic KYC due diligence to accelerate customer onboarding
• Understand use cases to apply knowledge graphs today
• Train machine learning and AI to gain insights

Since the morning was jam-packed with detailed presentations and thought-provoking panel discussions, here’s your opportunity to be part of the discussion! Join a group of your financial services peers to share ideas and new best practices in an intimate virtual environment.

1.) Leveraging Data Cataloging to Prepare for the Future State of Your Data Program

Andrew Foster, Chief Data Officer, Americas, Deutsche Bank 

2.) Data Quality Control Through Sustainable Data Remediation