Banking on Analytics

Raghuraman explores the relevance of implementing analytics for shaping up a bank’s business and the various critical factors for its success

Raghuraman

It’s a given that banks need to be accurate with their reporting and be compliant with regulatory requirements. In today’s context, it is just as much a given that they need to be sensitive to changing market dimensions and customer requirements. They have to be sure about what they sell (products), whom they sell to (customer segments), where they sell (delivery channels) and whether it will be profitable or not.

With 20% of customers accounting for 80% of their profits, banks are still working their way out to focus on cost management, diversification into multiple fee-based income streams and optimizing capital utilization. They are finding new ways to steer and overcome challenges through a relationship driven model to engage and endure customers. Customers do not want pre-configured products, they want products that are differentiated and meet their specific needs. The key lies in a bank’s ability to segment and profile its customers to gain a better understanding of their potential worth. What is required is for banks to achieve a 360 degree view of their customers from the existing silos of Lines of Business (LOB) that would include credit cards, insurance, investment banking, trading, retail banking etc.. Going beyond would be analysis-specific areas such as channel usage and optimization, treasury, trade finance, derivatives etc.

Core groups of subject matter experts (SMEs) have been constituted to ensure the data accuracy and integrity of data flowing from a bank’s core applications to the RBI. Such initiatives make it clear that the banking system is going through a rather vigorous exercise of enhancing data quality with stress on information management for both risk as well as productivity. The challenge is in real-time co-relation of the large volumes of data to derive meaningful information or patterns for what it means. While there can be no single method to deal with the cleansing process, banks have realized this and are working towards completing this humongous task. A clean, accurate historical data repository in the form of a data warehouse would help banks to not only expand their business, but to prevent/mitigate losses as well. Although the RBI’s Committee on Technology Upgradation had advised Indian banks to put an EDW strategy in place by January 2001 and banks with a large number of computerized branches to start their pilot projects by April 2001, progress has been slow. Of late banks have been investing in Enterprise Data Warehousing (EDW) that can provide logical linkages to various sets of information available across a bank for better analysis and for obtaining a holistic picture of their business.

Banking analytics (business intelligence derived from the EDW--data available from all LOBs) can provide metrics to quantify customer value and deliver capabilities to provide a competitive edge. Such analysis will be critical in driving performance as well as managing cost and revenue in the banking industry. Bankers will be able to track various metrics across LOBs including NPA movement, recovery analysis, deposit renewal analysis, deposit overdue analysis, deposit pre-closure analysis, customer acquisition and attrition analysis, bills growth analysis, bills exposure analysis, cash flow, profitability analysis and much more.

Banks have the choice to build their own BI capabilities or to buy off-the-shelf solutions that are specific to their LOB’s needs—say, for loans, deposits, profitability, customers etc. Once BI is available bank-wide, users should be able to access and analyze reports based upon their roles and priorities. This eliminates a user’s dependence on MIS or the IT department for his or her effort to churn out varied reports. While CXOs get an executive view of dashboards that are specific to their interests, the business users (based on their access privileges) can download reports in the format of their choice (Excel, Word, PDF etc.). They get access to a multitude of analytical reports from the integrated data repository. The reports can be through preconfigured graphs or charts that you can drill down into for multiple levels. Coupled with the power of collaborative tools (such as portals and messaging), bankers would be able to meet and resolve issues via secure, online discussions, thereby saving on cost and time. In a nutshell, business departments can employ their time to analyze their performance in real-time rather than wait for days for the same.

• Adoption: The success of a self-service analytics and reporting technology lies in its adoption. The implementation of banking analytics should be considered to be a strategic business initiative and not as an IT initiative to decentralize reporting. This requires executive sponsorship and participation from all of the departments in a bank.
• Plan and Rollout: It will be critical for banks to plan the rollout and choose the best path for adoption. A phased department-wise rollout is a good idea. Milestones need to be set and the involvement of all stakeholders who need to be aware of project risks and outcomes is required. Project deficits with respect to functionality or access will impact adoption.
• Barriers of age and culture: The ability of bankers to adapt to a new environment and acquire skills to take proactive decisions assumes great importance here. Traditionally, especially in the public sector, there has been dependence on MIS departments for data and reports. With the advent of business analytics, this dependency has to come to an end. Moreover, there will be challenges with respect to age (the average age of a PSU banker is over 45, Source: RBI) which may act as a barrier and prevent them from getting hands on with the solution.
• Training & knowledge transfer: Banking analytics is a cross-organizational initiative and this will impact every department and hence all business managers and senior executives must be trained and encouraged to use this tool. Even if we were to assume that the number of employees to be trained will be around 1,200 (around 10% of the employee average across all banks, Source: RBI 2008-09), the magnitude of the activity becomes clearer. Perhaps, the bank may want to use e-learning as an effective tool.

Raghuraman is a Senior Business Technology Professional with a primary focus on enterprise solutions for the Banking and Financial Services sector. He can be reached at raghuraaman@gmail.com