Data Quality

The digital transformation in financial services is rapidly redefining how the industry does business. It is changing almost every aspect of the business model from how customers interact with their bank, to the speed with which business managers need to make decisions.

While the core banking transactions have been digitized for many years, the current transformation is digitizing all customer relations, business rules, reference data, descriptive data and how this kind of information is delivered and consumed.
With the higher demand for information the data volume will grow larger and larger. Banks need to be prepared with the right strategy. This includes selecting the right business intelligence tool that is scalable, can cope with growing user and data demands (mobile and social media data will increase the data volume exponentially), is performant and flexible enough to handle quickly changing market conditions.

Another important aspect is data quality. Analysis and reporting of information makes only sense if the data that is used for building the information, can be trusted, is accurate, and can be reconciled with the various data sources. Compliance is key!

In order to manage and control data quality, banks all over the world are establishing data governance as part of a greater BI goverance initiative.

The goals of data governance are obvious. Clearly defined data elements ensure higher data quality and better decision-making because the information can be trusted. It reduces operational friction and protects the needs of the stakeholders by building repeatable processes and standards. The transparency gained through these processes in conjunction with a reduction of costs and an increasing effectiveness help as well.

The key roles of data governance are the following:
Data Governance Council - governing body to coordinate the effort and serve as a committee for resolving issues between the lines of business.
Data Owners - business that understands the data and the sources
Data Stewards - responsible for data/information areas, e.g. marketing, leading the effort within their area of responsibility to control and improve data quality
Data Custodian - IT driven role that udnerstands the technical impact of data, how it is loaded, calculated and modeled.

The problem with such initiatives - at least from my experience - is that a lot of financial institutions believe they can do these kind of initiatives (implementing a BI Competency Center and data governance) without external help. You have to have the experience to implement this. It is a change management process that requires a very good understanding of the subject and an external view/standing. I have supported and led such engagements various times and can say that those that were following external advice and had executive sponsorship, are successful.
Others, that tried it themselves, usually did not achieve the level of adoption necessary.