Maximising efficiency with leveraged data

Many financial institutions (FIs) today are trying to implement different practices to optimise the efficiency of their business operations while struggling to achieve better performance, while also focusing on how to comply with the different regulatory requirements such as Know Your Customer (KYC), Basel III, Foreign Account Tax Compliance Act (FATCA), Money Market Statistical Reporting (MMSR) and others.

Organisations are 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 5 billion subscribers are surfing, broadcasting or sending data.

The financial industry is one example amongst several industries that are 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 some will lead to significant operational risk and loss of opportunity.

FIs should see 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.

In the next few paragraphs I would like to illustrate the practical ideas on how FI’s can optimise their performance  by leveraging existing data and shifting the focus on improving the quality of data:

Capitalising 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 whilst onboarding new customers, the information is usually well detailed. Some institutions have also started considering collecting more high tech customer unique attributes like voice recognition. While collecting customer information is a mandatory obligation for FIs for regulatory purposes, banks should extend this process because 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 type of clients. The bank can innovate new oriented services per layer and keep their clients informed and engaged through observing client feedback. This will also allow them to evaluate more accurately their client’s needs and respond, thus giving them an edge over the competition.

In this big data era it is very clear to see that data driven banks will succeed and be more able to compete and thrive.

Visualise data

Data by nature is difficult to be digested. “The main goal of data visualisation is to communicate information clearly and effectively”, says Vitaly Friedman, editor-in-chief of 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 to 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. “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”, the head of product and marketing at JP Morgan said.

Enhanced Knowledge Discovery in Database (KDD)

Finding knowledge in data is almost impossible as long as the input data is poor. Today, with the transformative impact of data the value of obtained knowledge can be improved by enhancing the Knowledge Discovery in Database (KDD) process and applying a linked database approach, though this is not enough to achieve the target. FIs should adopt a cascading systems technique by adding another layer of systems which 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) shows that banking and financial sector firms are to increase 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 FI’s 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 FI’s 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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