A new wave of Fintech solutions is emerging with innovative offerings targeting both banks and their customers. Many successful "fintech" companies rely on innovative usage of analytics as a core aspect of their offerings. Banks can benefit from such innovation to enhance their products and services. In this session, we will cover: What is the current state of Fintech? How is analytics used in Fintech companies? How should financial institutions use analytics in their Fintech initiatives?
As data and analytics become pervasive in all aspects of financial services, the ability to communicate in this language — that is, being data literate — is a new organizational readiness factor. Whether translating to the board how data and analytics manifest in compliance and fraud use cases, explaining how to creatively blend internal and external datasets to better evaluate risk, or describing advanced analytics techniques that improve customer experience, the data and analytics discipline is the new language digital finance. While business partners conceptually agree on the importance of data quality, consistency, and access, they push back on taking direct ownership of data decisions. Without effective data governance, data remains trapped in vertical silos preventing data and analytics leaders from leveraging enterprise data as a true information asset for digital initiatives. Join our panel to learn how successful financial firms are using collaborative, factually oriented dialog and data governance to achieve a clarity of purpose that drives real transformation.
This roundtable is a forum to discuss how organizations are exploiting analytics technologies to create customer intimacy. We will discuss topics that cover how analytics and related technologies are being used to achieve business goals, the challenges that organizations encounter and successful approaches in overcoming them. PLEASE NOTE: Reserved for end-users only. Pre-registration required.
Analytics and its derivations are critical for banking and securities firms to succeed in the future. Firms look to apply analytics, in conjunction with other technologies such as AI, across most of the business functions to compete better and operate efficiently. In this session, we will explore what the specific new trends, emerging technologies and how both incumbents and their fintech challengers are applying analytics in their business.
The Australian Prudential Regulation Authority (APRA) released the final version of its new cybersecurity requirements in December 2018. Banks, insurers and superannuation funds are expected to meet the new requirements by July 2019. Data and analytic leaders need to be prepared to discuss how third-party providers access and secure data and be able to articulate the business value created by taking on additional risk. This session provides an opportunity to ask questions and learn what steps your organization needs to take now to prepare. PLEASE NOTE: Reserved for end-users only. Pre-registration required.
Increased transparency is a major force driving open-data initiatives but many government organizations struggle to show how data also increases accountability. This session will provide government data and analytics leaders with the techniques needed to establish a sustainable performance management program that tracks progress on organizational priorities and goals.
From policy planning to service delivery optimization, this session will explore opportunities and frameworks for using data and advanced analytics to improve government service delivery. What are the patterns of successful data leaders in finding balance between data governance and innovation?
Sharing data information among government organizations and its partners remains an obstacle to transforming public services and improving outcomes. This session offers guidance to develop successful and sustainable data sharing practices in government so that data and analytics leaders can increase data sharing in their jurisdictions.
This session will describe the foundational concepts for the discipline of master data management and the technology solutions that support it. What is master data and why is it important? What are the most common business benefits of successful MDM programs? What are the discipline and technology components of a successful MDM program?
Analytics should be a key enabler of organizations’ goals but that is seldom the case. Most initiatives tend to focus on tools deployment and user support with little connection to business objectives. In this session, we describe a step-by-step methodology to design a business-outcome-driven analytics evolution roadmap with a strong commitment to users and a shift from technology to business impact.
Organizations increasingly need to connect things that share data — disparate data and analytics programs, MDM and master data stores, applications, processes, teams and external partners. But without a well-planned strategy based on requirements for mediation and governance, it's hard to enjoy a smooth flow of trusted data. What are data hubs and how do they support data sharing and governance? What are the most effective starting points for a data hub strategy? What are the best approaches to architect and deploy data hubs?
Fresh hot roles for the information-savvy organization are emerging to help organizations become more data-driven. New skills and competencies are required for existing roles to adapt to the changing role of data and analytics. This session will highlight the key roles and responsibilities in data and analytics to be ready for the digital business and the impact on the organization model. Key issues: What's happening in data and analytics forcing change? What's the impact on the organization? What's the impact on roles and skills?
Finding, integrating, cataloging and curating data for analytics, data science or further data integration (and data engineering) by business users is consistently rated by data and analytics leaders as one of the top three challenges in data management. 1. How can organizations incorporate augmented and stand-alone machine-learning-enabled data preparation tools for analytics/BI and data science use cases? 2. What are the market segments and popular offerings in the rapidly competitive and popular data preparation space and what should be your evaluation criteria to select the best offering? 3. How must you plan your data management and analytics architecture to ensure the right balance between self-service and IT oriented data preparation to avoid a governance chaos?
Join your peers for an informal discussion on data and analytics trends specific to government. To kick off the table conversation, attendees will be presented with some of the key findings from the government results of the 2019 CIO Agenda survey.
Traditional data and analytics governance that focuses only on policy, compliance and enforcement, is now obsolete for digital business. Adaptive governance practices that are contextual and elastic are urgently needed for successful digital business initiatives. This session discusses why current practices are now inadequate and how adaptive governance practices can be adopted to enable better outcomes.