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“Making data pay”

By Thierry Kremser, Partner and Data & Technology Leader at PwC Luxembourg. The financial industry is flooded with data. The explosion of banking information exchanged by customers and the multiplication of data used in the financial markets, together with an increase in storage capacity and calculations, explain the enthusiasm around data analytics and algorithms.

In the 1980s and 1990s, IT systems transformed virtually every single bank process. Today, banks have that real opportunity to reinvent themselves again—with data and analytics.

If traditional banks adapt and learn to protect customer information in the new setting, big data could be the key to their competitiveness on the long-term. It would allow them to use more data and carry out a much larger and faster algorithmic analysis work. In a context where speed and efficiency are the key words, being able to conserve, manage, process and analyse an incredible mass of data represents a strong competitive advantage.

 

Sharpening risk assessment and driving revenue

Every major decision to drive revenue, to control costs, or to mitigate risks can be managed by data and analytics.

Data analytics give financial services firms a better overview of how their businesses are performing and provide complete and insightful information to support strategic decision making.

Faced with an increasingly volatile clientele, the first challenge for banks is to retain their customers. They can anticipate their needs by analysing their banking behaviours, as well as their shopping habits online or their activity on social networks. Combined with traditional financial data, social and behavioural data could provide a comprehensive picture of future borrowers and a more accurate assessment of their risk profile.

The use of data analytics in banks opens up numerous prospects for profitability. It also raises questions, as much as it fascinates.

For investment banking, big data tools analyse market data in real time to maximise profitability and minimise exposure to risk. They thus favour the optimisation of trading strategies within the front offices, for which the analysis must be dynamic, given the variability of the data.

Data that was previously abandoned due to lack of storage is now easily stored in databases to be analysed. And so, the capital markets industry has become one of the most data-driven industries. Electronic trading generates millions of messages every day. Regulatory and risk management requirements are challenging banks and financial services firms to capture, store, and analyse data that spans multiple years, departments and regions, at ever increasing levels of granularity.

 

Fierce competition around the corner

We know that revenue from selling data will increase exponentially in the next three to five years across capital markets, commercial banking, consumer finance and banking or insurance.

This kind of opportunity is getting more attention and many traditional financial services firms face non-traditional players entering the scene. Google, PayPal and Apple, for instance, are quickly gaining ground in the payments space, proving that non-traditional firms can enter the competition just by having a data advantage. According to numerous studies, leading financial services firms risk losing 10% or more of their potential top-line revenue to non-financial competitors within the next few years if they don’t move quickly to transform their business.

Advanced-analytics opportunity quite simply is an opportunity to redefine the playing field, some banks will seize that opportunity and will be able to truly differentiate themselves using data and analytics. Do you use data and analytics to drive growth in the business, to drive better risk behaviours in the business, and to reduce costs across the business? That can be now a huge differentiator.