Data and analytics

Your challenge

Data steers decisions that can directly affect risk. Unfortunately, even financial services institutions that are aware of data’s value are not necessarily able to capture or handle it to their best advantage. They struggle with perspective, sequence, prioritising and execution, as well as board-level ownership and connections. They’re missing effective data-management systems and skills that would help them understand and support the information demands of regulators and cross-functional stakeholders. And they lack quality data.

Financial services organisations need fundamental data and analytics capabilities to facilitate both financial and non-financial risk-management processes. In Deloitte’s Global Risk Management 2021 survey, we found that most institutions struggle in two broad areas: maintaining reliable data to quantify non-financial risk and inform risk-based decisions, and being able to use and source alternative data, such as unstructured data. We can help with both challenges, and many more.

Why Deloitte?

Recognised as a Leader of the 2022 Gartner Magic Quadrant for Data and Analytics Service Providers, Deloitte enables AI-powered transformations through end-to-end data and analytics solutions. In the Netherlands, Deloitte Risk Advisory has a dedicated pool of around 300 talented data professionals. We help clients find meaning in data, enabling you to maintain a model that facilitates responsible pricing and risk management in your products and balance sheet.

We have also assisted many clients shifting to data-driven regulatory processes. For a Dutch bank, we helped implement automation software that cut data processing time by 80 per cent, freeing up reporting specialists to analyse trends and interpret regulations. Our integrated, comprehensive approach can enable you to save resources, and turn compliance risk management into a strategic advantage by making it more data and technology driven.

Our capabilties

With years of experience behind us, we can show you how to gain insight into your data management maturity. Then we’ll provide you with best-practice blueprints, frameworks and timely, practical solutions that can include the following.

• Data management: An effective data strategy is hard to achieve if the data governance structure is not well defined or not properly implemented. It can also suffer when there is insufficient knowledge of the data’s origin and lineage, or unreliable or inconsistent metadata and master data. We can offer a data management maturity scan, data governance map and data management tooling, as well as set up a chief data officer function.
  
• Data quality management: On-site inspections by national and European regulators have revealed a struggle to ensure data quality in reporting. With our Data Quality Framework, we help define data governance structures, source critical data elements, design and implement quality rules, and create dashboards to continuously monitor quality.
  
• Data engineering: Data is often scattered throughout an organisation, belonging to various owners and suffering from inconsistent data definitions or erratic use of tools. Our data engineering methodology enables an incremental build of a centralised data hub. Our experienced implementation teams bridge the business perspective with the technical perspective. And with a data pipeline, you’ll see improved operational efficiency, from data source to consumption.
  
• Remediation and rapid response: Data remediation is associated with strict deadlines and high volumes. Challenges faced in every remediation programme relate to scalability and the flexibility to remediate various gaps. Deloitte’s Data Remediation Factory is configured to each precise use case. User groups are trained to prepare and pick up remediation items, and technology smooths workflow functionality and data collection, gathering and auditing.
  
• Data insights: Becoming an insight-driven organisation requires more than just data and technology. We guide you to ask the right business questions, which will lead to the right analysis, and actionable insights that guide the redesign of processes and optimise operational effectiveness. To this end, we offer an insight-driven organisation framework, and knowledge-graph data insights monitoring.
  
• Advanced analytics: Financial organisations can gain a competitive advantage by extracting maximum value from the huge volumes of data produced by advanced analytics and algorithms. For example, with our lending process optimisation, we help incorporate state-of-the-art methodologies, data sources and approaches to enable more digital lending processes within banks’ front offices. We also help financial institutions optimise back-office processes by introducing more data-driven decisions within their FR&R and other risk-management processes.