Expand+Requirements
Students seeking admission to the MSc Pathway or its constituent programmes must possess:
• An Honours degree (second class honours grade 2 award or higher)

or
• Admission many also be considered for experienced professionals w...

Hide-Requirements
Students seeking admission to the MSc Pathway or its constituent programmes must possess:
• An Honours degree (second class honours grade 2 award or higher)

or
• Admission many also be considered for experienced professionals who do not meet the admission requirements as set out above, where they can demonstrate knowledge through their work i.e. they have more than 5 years’ experience in a management role (to be considered on a case by case basis).

You must be a current member of IOB, or become a member, to undertake this programme.

Expand+At a glance
This programme is relevant to all areas of the financial services sector, in particular international financial services, fund management and all areas of banking.

Who is it for?
Learners will be at managerial and leadership level o...

Hide-At a glance
This programme is relevant to all areas of the financial services sector, in particular international financial services, fund management and all areas of banking.

Who is it for?
Learners will be at managerial and leadership level or aspiring to a leadership role.

How you will benefit
On successful completion of this programme, you will be able to:
• Describe and explain the challenges and opportunities provided by integrating data and advanced analytics in the provision and management of financial services
• Examine current practice pertaining to data and analytics in a financial services enterprise or unit and recommend enhancements in design and skills base to ensure the unit provides a competitive service
• Analyse the impact of a data driven culture and the business drivers in facilitating effective use of data and analytics tools and processes in financial services
• Identify the key features of and evaluate the procedures / new technologies within an organisation which assists and empowers its personnel / business units as they learn to use data and analytics in their everyday work
• Communicate clearly (using appropriate media) to pertinent stakeholders the impact of data and analytics on financial services and products design and delivery
• Critically reflect on your professional role and contribution to financial organisations in the context of the application of data and analytics technologies and systems in financial services (and related sectors) and the implications arising from such developments.

Continuous Professional Development
If you hold an IOB designation or a designation managed by IOB, CPD hours may be awarded on successful completion of this programme.

Expand+Modules and learning outcomes
Strategy and Culture in a Data and Analytics Environment
(NFQ Level 9, 10 ECTS)

The data and analytics environment
Business and technology trends in data and analytics. The business value of data and analytics toda...

Hide-Modules and learning outcomes
Strategy and Culture in a Data and Analytics Environment
(NFQ Level 9, 10 ECTS)

The data and analytics environment
Business and technology trends in data and analytics. The business value of data and analytics today. Regulatory environment and considerations. Data and analytics leadership.

Building a data and analytics strategy
Aligning data and analytics with enterprise strategies. Vision setting. Strategic frameworks for data and analytics. Opportunity mapping. Use cases in leveraging data and analytics. Aligning enterprise goals through data and analytics.

The data and analytics mindset
Engaging the C-Suite. Analytical acumen. Learning and education for data and analytics. Building data-drive decision making across the enterprise. Data tools and visualisation. Managing day-to-day - integrity, dictionaries and longevity.

Talent and Assets Management
(NFQ Level 9, 10 ECTS)

Best Practices in Data Management
Data management best practice. Data foundations. Data architecture. Data democratisation. Harnessing and filtering big data (structured/unstructured) New and emerging pillars in data management and architecture.

Data and Analytics Architecture and Technologies
Data storage and distribution. Data translation and quality. Data virtualisation. Data integration. Data processing. Data streaming. Knowledge discovery tools. Business Intelligence (BI). Predictive analysis. Cognitive (e.g. deep learning).

Managing Risk - Data & Analytics
Data governance. Data quality. Data longevity. Managing bias in decision making. Evaluating risk in data and analytics. Risk mitigation - software, hardware, data, operations, people, customer, and brand.

Driving Business Outcomes
(NFQ Level 9, 10 ECTS)

Leveraging Data & Analytics – Skills, Methods and Tools
Building the data and analytics team. Data analytics operating model. Interpretation and problem solving. Tooling and workplace. Learning and education for data and analytics.

Driving Business Outcomes
The application of 360 degree data and analytics. Aligning business strategy with data and analytics. Driving data and analytics business results. Framing questions and problem statements. The importance and limitations of data and analytics.

Future developments in Data & Analytics
Technology trends in data and analytics. Technology strategies and how they impact data and analytics. The importance and limitations of data, analytics, and modern technologies.