ENTERPRISE CRM: TURNING DATA INTO INSIGHT

By Dr. Ashok Hegde, AVP - Industry Principal and Head of Capital Markets Practice.

Building a CRM application within the context of an investment bank is always challenging. The build complexities arise from the fact that these applications need to use multiple systems to access information and enable businesses to manage client information. In order to have an effective CRM application, processes need to be built to transform data attributes into meaningful information about the client, which would include a complete understanding of clients’ relationships, their value to the bank and provide detailed insight into their future potential.

A lot has been written on the current status of the investment banking industry. Many research reports have indicated a smaller appetite for IT investment expressing concern over their ability to invest further in client facing applications.

A growing business requires sharper insights

With respect to the business, even though the absolute value of trade and transactions has plummeted, the daily volume of business has remained steady. In certain asset classes such as fixed income, the daily volume has even increased. It is in this context that the need for better insights on customer activities and streamlining the processes of information sharing between front, middle and back office is gaining further momentum. While supporting the clearing functions, ensuring error free settlement mechanism, processing corporate actions and sharing required information with regulatory compliance department remains critical, developing an integrated and pan enterprise  approach to managing  client interactions and transactions is the need of the hour.  An enterprise wide CRM application reduces the redundancies, which result from multiplication of CRM systems developed to support individual divisional needs.

However, the ability to conceptualize and build such a system which addresses the above dimensions is hindered by disjointed processes and unavailability of accurate enterprise-wide data. Often, large and medium sized investment banks tend to use the existing systems or applications that were conceptualized and built to address the immediate business needs of the individual division. Such a myopic approach has resulted in the development of disparate systems that address the needs of individual business units or trading desks. This approach has been the single most important reason for the disjointed processes which exist today in the IT landscape of most of the industry players making it difficult to have single view of the investment banking business.

What should IT managers in investment banks focus on?

Over the years, the priorities of an IT manager in investment banks has remained the same. Though, defining the common data strategy, maintaining client contact profiles, client segmentation, lead generation, product and service match, analytics for cross selling and customer profitability analysis continue to remain the most important pillars of  CRM applications, the top priorities include:

a. Improving data confidence: Data quality issues have been discussed in various reference data related literature, available in plenty. The enterprise’s requirement to have cleansed and certified reference data has  always taken the limelight in discussions. However, the quality of the customer reference data can only be measured by the confidence level of the user. There is no better way to validate the quality of data, its integrity and its recency. Old data in the system today, is as good as incorrect data. For example, in an investment bank, the confidence of the research team on the data provided to them, is the final verdict on the quality of the data. User confidence level is the only time-tested method available to validate data accuracy and integrity.

b. Building pan-IB CRM systems: The second priority for an IT manager in an investment bank is the intention to build an enterprise-wide CRM system which cuts across all trading desks. A lot more is yet to be accomplished with respect to supporting the various division’s needs to profile customers. The need to manage the availability and unavailability of information in the real-time calls for building a pan-IB CRM system. Capturing, processing and distributing data elements on need basis as well as on push basis still remain one of the top five priorities of the IT manager of   investment banks.

Hurdles in the path to building an enterprise wide CRM system

Historically, systems and databases were built over time while responding to the growing needs of the business. Often, custom-built applications and standard CRM products are used to create a crisscross of applications, processes and systems on different platforms which are in different formats. Thus, data gets transformed into meaningful information in varied reporting formats and standards but data attribute naming conventions are different in different business units within the same enterprise. Often, these are not in conformation with the best practices of building enterprise-wide CRM systems. Commonly, information architecture with common terminology is hardly linked to the organization’s business architecture.

Building an IT structure on top of business architecture and information architecture remains elusive. Considering the difficulties in common reference of same data attributes, it is difficult to measure the success of many CRM systems developed within banks. Due to the complexities that currently exist; many have stayed away from attempting to migrate these disparate systems into one single pan-IB platform. There are not many who can claim that they have the single-view on customer activities – irrespective of desks or divisions that deal with that particular customer segment.

Meeting the requirements of the sales team is also important for the success of CRM systems in investment banks as optimized sales activities can sharpen the value proposition to the service buyers. Building a well thought through workflow to manage the deal process can significantly reduce effort and cost in the process. Reducing data redundancies, improving data integrity, managing alert and event all can be of help in this process. Since client activities are always referred to within the context of time frame and event, analytical ability of a CRM system needs to be supported by historical time series data attributes in addition to simulated data generation to understand the future in better perspective.