Data: A Differentiating Factor in Private Banking
Alex, a private banker, has just finished a meeting with a client and leaves for lunch with his friend Ben, who is head of business development at the same bank. During lunch, Alex asks Ben, “When will I finally get more detailed analysis results on my clients from you guys? I still don’t have a clue about my clients’ profitability.” Ben’s answer does not surprise Alex, he has heard it before: “We are trying to get a budget for this kind of data analysis. The problem is that the data are stored in different systems. Accessing the data, getting all the details, and then finding the resources with the right skills to analyse them is a big challenge. But if we were able to do it, the results will definitely help you to improve your service.”
Many private banks and wealth management firms are struggling to manage and analyse their data. The obligation to collect additional data due to regulatory requirements and the liability if some of these data cannot be accessed in time to answer a compliance request, aggravate the problem. In addition, projects that would help improve data management and data analysis capabilities compete against regulatory projects like FATCA, Client Suitability, and Basel III.
If a budget is available for a data analysis project, who should drive it? Business and IT departments are typically not well aligned on this topic. The business professionals do not know what the IT department can do with the bank’s existing data, and the IT professionals do not really understand what analyses the different business department need to better service their clients. Here is where your data analyst team can help. Typically buried somewhere in the lower echelons of the IT hierarchy, they are the most suitable individuals to communicate between business and IT departments. Empower them to assume three roles: mediator, data engineer and data scientist.
The mediator works closely with the various business departments to understand priorities and most urgent pain points. He or she knows what data are available at the bank and at what cost they can be accessed. He or she is also familiar with the origins of the data and the principles that govern their use. With this knowledge, the mediator can reconcile differences between business and IT departments. The main focus of this role is on bridging the cultural gap. Ideally, mediators have a direct reporting line to one of the business departments.
In the role of data engineer, the data analyst solves traditional data problems like the one mentioned in the dialogue between Alex and Ben. The role requires detailed private banking knowledge to understand, for example, how profitability of a client is calculated or how historical performance data of a product can be extracted. The data engineer is also proficient in database technology and traditional data analysis. As long as most analysis-related tasks tasks centre around organizing, cleaning, extracting, transforming, and moving data, the role of the data engineer remains important. Over time and with a shift towards dynamic data analytics, data engineers may gradually be outnumbered by data scientists.
With the increase of data and the perception that data are becoming the new differentiator for banks, private banks will move deeper into data mining and data exploration. Attracting new clients and increasing the ‘share of wallet’ are high-level objectives that need to be broken down into sizable and operable analysis steps. That’s where the data scientist comes in. In this role, the data analyst helps the bank turn data into information and information into insights. Despite this potential, however, the role of data scientist may not be valued by everybody in the private banking world. Smaller banks in particular still count on the quality of their client advisors and do not believe that data analytics can reveal anything about their clients that the client advisor does not already know. Naturally, the achievements of a data scientist will be scrutinized.
Private banks possess valuable data about their clients and products, but many of them cannot leverage the full potential of these data. While technology can help to improve the situation, the real problem is not technical in nature. It is the three roles of mediator, data engineer, and data scientist that together embody the necessary capabilities to allow private banks to make the most out of their data. Candidates for these roles are best found in a bank’s data analyst team because these individuals know what data are available and how to access them. If data is to become a differentiating factor, reassess whether your data analyst resources are able to take on these three crucial roles.