Many of today’s financial institutions (FIs) are trying to implement different practices to optimise the efficiency of their business operations while struggling to achieve better performance. At the same time, they must focus on how to comply with different regulatory requirements, such as know-your-customer (KYC), Basel III, the US Foreign Account Tax Compliance Act (FATCA), the European Union’s (EU) Money Market Statistical Reporting (MMSR) and other regulations.
Organisations are now more aware than ever before of the challenge Big Data raises and in many cases have taken initiatives to accommodate the growing challenge. Many leading institutions have embarked on plans to manage mobile Big Data, a significant challenge but also an opportunity where five billion subscribers are surfing, broadcasting or sending data.
The financial services industry is one example amongst several industries witnessing a tangible increase of daily volumes of data and a massive number of real-time transactions. Consultants and data management experts are giving guidelines and advice on Big Data. It is important today that FIs pay attention to the Big Data challenge, simply because ignoring this phenomenon will pose significant operational risks and loss of opportunity.
FIs should need to view Big Data as an opportunity. Managing Big Data to extract value can give them an edge in better management, resulting from more informed decision-making and leading to better performance.
The following paragraphs illustrate some practical ideas on how FIs can optimise their performance by leveraging existing data and shifting the focus on improving the quality of data:
Capitalising on customer data: Naturally, banks focus on collecting the right information from their customers to meet regulatory requirements. They do this by either updating their existing database, or when on-boarding new customers. The information is usually well detailed and some institutions have also started considering collecting more hi-tech customer-unique attributes using voice recognition.
While collecting customer information is a mandatory obligation for FIs for regulatory purposes, banks should extend this process to their advantage – since customer information gives them an edge and a possible competitive advantage. This can be achieved by categorising the client’s information on different layers based on several criteria to understand thoroughly the distribution and the types of clients. The bank can innovate new oriented services per each layer to keep their clients informed and engaged through observing their feedback. This will also allow them to evaluate their client’s needs more accurately and be more responsive to their customers.
In this Big Data era it has become clear that data-driven banks will succeed and be able to compete and thrive even more.
Visualise data: “The main goal of data visualisation is to communicate information clearly and effectively,” states Vitaly Friedman, editor-in-chief of the web developers’ and designers’ publication Smashing Magazine. It is critical to know what data you need in order to effectively manage and use your Big Data and not be lost in raw data visualisation that will not add much value for you. The right type of data should be presented in charts without the need to concentrate on the efforts of visualising all raw data or complicated graphs.
To achieve the goal only efficient information should be represented. Carol Waddell, head of product and marketing of JP Morgan says: “While we’ve always used plan data and analytics in working with our clients, the new tool delivers data that allows us to go much deeper and provides a much clearer window into participant behaviour.”
Enhanced knowledge discovery in databases (KDD): As long as the input data is poor, finding knowledge in data is almost impossible. Today, with the transformative impact of data, enhancing the knowledge discovery in database (KDD) process and applying a linked database approach can improve the value of obtained knowledge. Although this is not enough to achieve the target, FIs should adopt a cascading systems technique by adding another layer of systems that has the capability to interconnect with different databases and extract needed fields, which will increase the accuracy of finding patterns of data.
Data deduplication: Be efficient and avoid duplication of data storage. Eliminating the redundant data has its value on the output of the earlier mentioned practices. Recent research conducted by PwC and the Confederation of British Industry (CBI), which issue a quarterly survey, shows that banking and financial sector firms increased investment in IT by around 72% in 2015, this includes a 27% investment allotment for storage and computing fields alone. Data deduplication has a vital role not only in reducing storage cost but also in increasing performance especially for real-time applications that receive a high amount of data and require regular data archives.
FIs cannot ignore Big Data. Now is the best time for FIs to put in action their plan for a proactive performance tuning. Especially with the rise of the Internet of Things (IoT) as it is anticipated in the short term that FIs will be overwhelmed with data. The right strategy for capturing, managing and utilising tremendous amounts and sources of data will give a competitive edge and transform to real growth in revenue for FIs.
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