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Interpretations of the frequently heard buzz words “Big Data” can mean many things to many individuals. The confusion lies in its ability to provide solutions to long-standing business challenges for companies of all shapes and sizes. Many companies and clients that I come across are still sceptical about their ability to advance their efforts in big data to generate the required return on investment. Perhaps the most promising industry big data can be of assistance is the financial industry. With no physical products to manufacture – data is arguably their most important asset, containing a wealth of information. The question for many financial companies is how to best leverage this information to gain sustainable competitive advantage.
So how can financial companies achieve this? I have summarised 5 key best practices from IBM’s executive report “Analytics: The real-world use of big data in Financial Services” to provide some clarity:
1. Commit initial efforts to customer-centric outcomes: It is vital that organisations focus big data initiatives on areas that can provide the most value for customers. For most firms, this means beginning with customer analytics that enable better service by being able truly to understand customers’ needs and anticipate future behaviours. For example, a major Chinese bank analyses historic customer data from a variety of structured and unstructured sources to determine individual preferences, and how best to leverage these opportunities. This has involved transforming their business objectives from product-centric to customer-centric.
2. Define big data strategy with a business-centric blueprint: An effective blueprint defines the scope of big data within the organization by identifying the key business challenges involved, the order in which those challenges will be addressed, and the business process requirements that illustrate how big data will be used. This blueprint will help the organisation develop and institute its big data solutions in pragmatic ways that create sustainable business value. As an example, a prominent global stock exchange company employs big data analytics to detect new patterns of illegal trading, thereby reducing damage to the company.
3. Start with existing data to achieve near-term results: The most logical and cost-effective place to start looking for new insights is within the organisation’s existing data store, using the skills and tools most often already available. A recent IBM survey identified that over 80% of the financial services firms are focusing on transaction and log data to generate insights. There is still a large amount of untapped value locked away in these internal systems.
4. Build analytics capabilities based on business priorities: The unique priorities of each organisation should guide the development of big data capabilities, especially given the tight margins and other regulatory and cost pressures organisations face today. Here, companies should focus on acquiring the specific skills needed within their own organisations, especially those that will facilitate the ability to analyse the data and represent it in a consumable way to business executives.
5. Create a business case based on measurable outcomes: Developing a comprehensive and viable big data strategy and subsequent roadmap requires a solid, quantifiable business case. It is important to have the active involvement and sponsorship of business executives during this process, in conjunction with an ongoing business and information technology (IT) collaboration.
Referring back to my first point, while the big data movement can mean many things to financial companies it is only of use when implemented with finesse and strategy. Where banks and financial services lag behind their cross-industry peers is in using more varied data types within their pilots and implementations. Financial institutions will realise value by effectively managing and analysing the rapidly increasing volume, velocity and variety of new and existing data, whilst implementing the right skills and tools to better understand their customers and marketplace as a whole.
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