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Data holds the key to smart decision-making

Data holds the key to smart decision-making

By Nick Felton, SVP, MHR Analytics

The financial services industry faces a myriad of major challenges including navigating digital disruption and economic uncertainty at the very top of the list.

Against the backdrop of complex Brexit negotiations, the future of the UK economy remains unpredictable in the short term. Organisations must be smart with their data innovation to ensure these potential turbulent times are turned into a positive step forward for their business.

In this febrile environment, data can be harnessed to identify and neutralise risk. Whether it’s planning financial resources for the year ahead, managing facilities or IT infrastructure; good decision-making is paramount at all times. Company leaders can improve their confidence in making important decisions with reliable insights from accurate data.

There are however many challenges when it comes to sourcing accurate information. Duplications, erroneous or outdated data resides everywhere, and all too often gets used for making vital choices about the future of the company.

The consequences of failing to address this issue are severe for many reasons. Poor quality data can lead to financial miscalculations, disjointed planning and impact the bottom line if not tackled as a matter of urgency. Additionally, in an era when stricter compliance measures in the form of MiFID II is forcing financial services organisations to operate with a greater degree of transparency, a lack of visibility into data assets could leave companies in breach of strict regulations.

For companies considering solving this problem, the time is now. Recent UK economic data has revealed the UK’s GDP rose just 0.1% in the first three months of 2018. Additionally the Bank of England has recently updated its 2018 economic forecast of a growth of 1.4 per cent, down from the original 1.8 per cent forecast. So, whilst the future remains unclear, these indicators mean now is the time to take an innovative approach to data.

A recent survey by DWF of FTSE 100 companies found that business leaders are now paying close attention to the EU negotiations, knowing that the outcomes of the deal will have a significant impact on the UK economy. If businesses are planning for Brexit, then they should also be planning to better understand the data assets which reside within their organisation that can accurately manage the changes Brexit will bring.

Despite the uncertainty, polling indicates overall morale is strong in the financial services and banking sector. A recent poll from Lloyds Bank has revealed that 88 per cent of over 100 senior business leaders believe that the UK will continue to be one of the most prominent hubs for the financial services sector after the UK leaves the EU. The Leadership Gallery also conducted a survey of C-suite executives to understand their concerns around Brexit and found that 76 per cent have limited concerns about the threat to their revenue.

This confidence is welcome, but it must be backed up by organisations taking a much more proactive approach to data management.

As well as harnessing the power of data to inform financial planning, it is important that organisations use it to effectively manage financial products and services. This is where scenario planning can be particularly beneficial, allowing companies to model potential outcomes, adapt to fluctuating revenue and tailor product offerings accordingly.

Likewise, data can help organisations monitor the performance of products, including the viability and profitability of bonds and derivatives etc, which is essential for companies wishing to maintain the competitive advantage.

The big data conundrum is not going to go away, businesses will continue to be bombarded with growing volumes of information. The make or break factor is how this information is analysed and acted upon.

Big data, managed correctly, is something that can really assist in knowing what assets an organisation has but it’s not the easiest process to navigate through. The sheer scale and complexity of many organisations’ data assets often means companies do not know where to begin.

The market for business intelligence and analytics is on the rise. It has been reported that big data spending is set to reach $58.9 billion by 2020 and nearly half of UK businesses are starting to apply big data insights into their businesses but actually, only 30 per cent of them are extracting enough valuable data to put it to good use and this is where businesses are going wrong. It is therefore vital that organisations extract the data that they can use to help their future forecasting, managing revenue and handling assets else these expensive data projects will not provide the necessary return of investment.

Right now, we are seeing a slow take-up of these new big data projects, which is certainly a positive step forward for organisations mastering data assets. Unfortunately, this apprehensive approach is nothing new; the financial services industry has been cautiously sluggish at implementing new technology and banks in particular have had a difficult time bringing in new innovations like artificial intelligence and data analytics.

So with digital transformation on the rise and customers expecting increasingly personalised experiences, there has never been a better time for financial services organisations to begin a new data journey. It’s time to recognise that poor quality data is a major business threat that could have profound ramifications for the future of the company if not identified and corrected immediately.

Whatever the economic challenges that lie ahead, it is important that financial services organisations address them with accurate information to deliver high quality decision-making. With Brexit on the horizon, contingency planning for new scenarios is not enough, every data asset within the company must be up to date and relevant.

Addressing this issue now will not only help organisations navigate the uncertainty ahead, it will empower accurate decision-making for the long term.

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