How the financial services sector uses big data analytics to predict client behaviour

The financial services sector has gone through unprecedented change in the last few years, writes Paul Garel-Jones. Customers are expecting a more personalised service from their banks. Regulators have reacted to the credit crunch with significant changes to regulation with more intrusive and granular supervision. At the same time, according to the EMC-sponsored IDC Digital Universe study, the world's data is doubling every two years with 1.8 trillion gigabytes expected to be created in 2011. A challenge for the industry is, therefore, how to use the breadth and depth of data available to satisfy more demanding regulators, but also improve services for customers.

The opportunity for the sector is to unlock the potential in the data through analytics and shape the strategy for business through reliable factual insight rather than intuition. Recognising that data is a significant corporate asset, a number of organisations are appointing chief data officers following pressure to police the integrity of the numbers as last year's Economist Special Report, "Data, Data Everywhere", put it. This pressure is driven by business leaders wanting more consistency in information and by regulators becoming increasingly concerned at the quality of data they receive during a time when regulatory demands are growing. This is made clear by the increasing number of references to integrity of data in each new regulatory requirement. For example, Solvency II requires insurers to have "internal processes and procedures in place to ensure the appropriateness, completeness and accuracy of the data". These processes and procedures could (and usually do) involve technology, but should also include data policies, standards, roles and responsibilities to ensure data integrity is appropriately governed.

While it is crucial to ensure the integrity of data provided to executive management and regulators, unlocking the insights in the data to better understand customers, competitors and employees represents a significant opportunity to gain competitive advantage. While regulatory pressure is forcing organisations to improve the integrity of the data, many financial institutions are seeing improved data quality and the use of analytics as an opportunity to fundamentally change the way decisions are made and to use the data for commercial gain.

Much of the current debate around Big Data is locked in technological advancements. This misses the point that the real strategic value in the data is the insight it can give into what will happen in the future. Predicting how customers and competitors' customers will behave and how that behaviour will change is critical to tailoring and pricing products. Big data should be about changing the way you do business to harnesses the real value in your data, re-shape the interaction with the market and increase the lifetime value of your customers. Therefore, which data is required to achieve these objectives, who needs it and how often are key pieces of the big data puzzle.

Big data should also involve using multiple data sources, internally and externally. Geo-spatial data, social media, voice, video and other unstructured data all have their part to play in knowing the customer today and their future behaviours. For example, leading firms are looking at using both internal and external data, both structured and unstructured, to develop personalised banking products. Customers are more likely to be attracted and retained with personalised products - hence, lifetime value goes up. Similarly, analytics have an increasingly important part to play in the recovery of bad debt. Recoveries functions typically target based on the delinquency status of the account. However, a better understanding of customer circumstances can improve targeting and have an immediate impact on recovery rates while also reducing cost.

There is no doubt that harnessing the power of big data can enhance organisational performance. However, it is not a technological question. It is a strategic one about how an organisation derives genuine insight from their data and changes the way they interact with customers, competitors and the market through fact-driven decision-making. Those organisations that master this will set the trend in customer service, improve profitability and respond more rapidly to the evolving regulatory and competitive demands of the industry.

Paul Garel-Jones is the financial services director at Deloitte Analytics