It has never been a more challenging time to be a Chief Risk Officer at a financial services firm. They must use precise data to measure risk, allocate capital and cover exposure. In addition, they must equip compliance groups to explain these decisions to industry regulators.

So what are the data issues impacting financial services organisations today? What should they consider and invest in if these situations exist? The following will outline three key data challenges and how they can be overcome.

Challenge #1:     I don’t have the right data in my risk applications, models, and analytic applications. It is either incomplete, out of date, or plain incorrect.

Root Causes:

The data required to manage and monitor risk across the business originate from hundreds of systems and applications. Data volumes continue to grow every day with new systems and types of data in today’s digital landscape.

Due to the lack of proper tools to integrate required data, IT developers manually extract data from internal and external systems which can range in the hundreds and comes in various formats. Solutions that can help:

Consider investing in industry proven data integration and data quality software designed to reduce manual extraction, transformation, and validation and streamline the process of identifying and fixing upstream data quality errors. Data integration tools not only reduce the risk of errors, they are designed to help IT professionals streamline these complex steps, reuse transformation and data quality rules across the risk data management process to enable repeatability, consistency, and efficiencies that require less resources to support current and future data needs by risk and other parts of the business.

Challenge #2:  We do not have a comprehensive view of risk to satisfy systemic risk requirements

 Root Causes:

There are too many silos or standalone data marts or data warehouses in the organisation, containing segmented views of risk information.

 Creating a single enterprise risk data warehouse takes too long to build, too complex, too expensive, too much data to process all in one system

 Solutions that can help:

Data virtualisation solutions can tie existing data together to deliver a consolidated view of risk for business users without having to bring that data into an existing data warehouse.

Long term, look at consolidating and simplifying existing data warehouses into an enterprise data warehouse leveraging high performing data processing technologies like Hadoop.

Challenge #3:  I’m unable to identify and measure risk exposures between counterparties and securities instruments

Root Causes:

Existing counterparty/legal entity master data resides in systems across traditional business silos.

External identifiers including the proposed Global Legal Entity Identifier will never replace identifiers across existing systems.

There is a lack of insight into how each legal entity is related to each other both from a legal hierarchy standpoint and their exposure to existing securities instruments.

 Solutions that can help:

Master Data Management for Counterparty and Securities Master Data can help provide a single, connected, and authoritative source of counterparty information including legal hierarchy relationships and rules to identify the role and relationship between counterparties and existing securities instruments. It also eliminates business confusion of having different identifiers for the same legal entity by creating a “master” record and cross reference to existing records and identifiers for the same entity.

In summary, Chief Risk Officers and their organisations are investing to improve existing business processes, people, and business applications to satisfy industry regulations and gain better visibility into their risk conditions. Though these are important investments, it is also critical that you invest in the technologies to ensure IT has what it needs to access and deliver comprehensive, timely, trusted, and authoritative data.