Fund administrators are adapting to an age of digital transformation, investing to meet the needs of their asset management clients and the investors they serve. But how well is the asset servicing community prepared for these challenges? Which technology should they invest in? And what adjustments to their business culture does this require? Funds Europe, in partnership with Temenos, surveyed the industry to evaluate how it is managing this change agenda.
Technology and operational requirements
• 93% say that investment in operational systems is essential for asset managers to improve efficiency and reduce cost.
• 54% say that legacy technology remains a problem for the funds industry.
• 83% say third-party technology providers will play an important role in driving innovation in investment operations.
• 68% say it is important to have one strategic service provider that can support a client’s full outsourcing requirements.
• 35% say that they will increase the number of third-party providers that they employ.
• 38% of respondents say that digital transformation will be their company’s major focus over the year ahead.
• 23% say that improvements in data analytics will be the most important development in the next three years.
• 40% say that developments in artificial intelligence will be the most important development in the next ten years.
FOCUSING ON THE FUTURE
Over the past 15 years, we have seen a transformation in the role that technology plays in the global economy. In 2006, the top ten global corporations by market capitalisation included four energy companies (ExxonMobil, BP, Royal Dutch Shell and Gazprom), along with firms from the financial services (Citigroup, Bank of America), auto (Toyota Motor Corporation), retail (Walmart) and industrial (General Electric) sectors. Microsoft was the only global technology company at this corporate high table.
Fast-forward to 2019 and seven out of the top ten global corporations by market cap are digital technology companies – Microsoft, Apple, Amazon, Alphabet, Facebook, Alibaba Group and Tencent Holdings. This illustrates the power that digital innovation can have in driving the corporate expansion of a group of technology players that were little-known at the start of the millennium. But it has also heralded new approaches to product development and service delivery made possible by digital technologies – through the use of cloud computing, mobile applications and analytics driven by rapid advances in data science and artificial intelligence.
The digital transformation age
The World Economic Forum (WEF) highlights in its Digital Transformation Initiative how cheaper and better technology has changed the way people communicate with each other and how this has revolutionised the way they access information, goods and services: 8 billion devices are now connected to the internet and the WEF expects that figure to reach 1 trillion by 2030 (World Economic Forum, ‘Digital Transformation Initiative: Executive Summary’, 2018, page 6).
To survive in this fast-moving digital era, the WEF suggests that “companies will need to become digital enterprises, rethinking every aspect of their businesses”. This will involve automating and streamlining business processes. It may involve investing in artificial intelligence and machine learning. It will also demand efficient management of key data, preventing mission-critical information from drowning in the data lakes that companies are creating to manage data at enterprise level.
The digital transformation challenge
These present new opportunities, but also challenges for long-established firms that need to adapt to a digital age. Decision-makers in the financial services industry are confronted with uncertainties around how to replace their legacy technologies, which new technology applications they should invest in, and how to ensure their firm has the skills to make this digital transformation work. There has been massive growth in the data available to financial services firms – a golden resource that may be employed to support advances in investment analytics, operational risk benchmarking, analysis of distribution and marketing trends, and for a host of other uses. However, this is useful only if the firm has a well-designed infrastructure to manage its data flows and the analytical skills required to interrogate this data effectively.
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