The Investment Management sector has seen dramatic change in the last six months. M&A activity boomed in the second half of 2020, and the first half of 2021 has seen no slowdown. The rapid digitalisation of not just Fund Management firms but the entire commercial environment has generated new opportunities and challenges.

As Digital Transformation consultants, we’ve worked with a number of firms - from Private Equity to Asset Management - and we’ve seen at first hand how the sector is facing change. We asked a number of industry insiders for their insights into the biggest trends in the UK, including digital transformation, machine learning, regulation, engagement, and more. Here are some of the biggest trends in Investment Management in 2021.

1- Digital Transformation

Technology continues to play an integral role across various Investment management functions as it has for decades. As new tools are developed, computing power has become more affordable, and as the availability of data continues to increase, additional use cases for AI and ML in asset management emerge.

Until recently, the private equity sector has been reluctant to embrace digitisation, out of the belief of its potential to disrupt business and deal flow. Now, however, as deal flow has evolved, many fund managers understand that technology is now critical to maintaining a competitive edge.

Digital Transformation has had far reaching consequences for business processes on the internal and external level. Internally, firms have looked towards streamlining and enhancing internal operations, record keeping, regulatory reporting, financial planning, consolidation, and forecasting. 

Externally, D&A and insights have been leveraged to improve portfolio acquisition decision-making and drive revenue, supporting commercial growth. Everything from conducting due diligence, to client engagement to collaboration with partners, have been executed digitally and in many ways streamlined and improved. 

Firms that have embraced digital have seen improvements in a range of processes. For instance: 

  • The use of D&A prior to due diligence, has been known to increase deal speed and improve accuracy in deal pricing. What-if scenario planning and growth analyses on financials enables firms to develop growth models and plan strategically for future growth and newly acquired portfolio companies. 
  • Partners have access to critical information in real time, allowing for quick and agile reporting and scenario analysis. 
  • Manual operations such as fund accounting, trade and settlement, and CRM can be streamlined and automated, driving higher value activity.
  • Compliance irrespective of jurisdiction is made simpler and more cost effective, streamlining regulatory reporting, and making client onboarding more efficient. 
  • In house digital capabilities allows fund managers to enhance the companies they invest in, selling them for a profit. 
  • Digitisation makes judging market positions, historical performance, cash flows, and capital expenditures easier, making identifying targets that much easier.

Digital Transformation also offers firms a unique opportunity to drive efficiency and profitability. Take Financial Consolidation for example. Traditionally, a Fund Manager would get monthly management reports from their portfolio companies and then decipher manually and with spreadsheets about who is and isn’t performing as they should, as well as where and how performance can be enhanced. This could include:

  • Inventory
  • Production
  • Ordering and purchasing data
  • Sales statistics
  • And much more.

Compiling that information and trying to interpret such a large amount of data is time consuming and challenging for a fund manager ill-equipped for it. Digitising this process means linking all your portfolio company systems together, feeding critical business information into a single system. This allows you to monitor data in real time, and to support quick and agile responses to market conditions, and to act on more accurate forecasts and budgets. 

2- Machine Learning

The growth of computing process power, storage, the cloud, and the proliferation of market  data has had a far reaching impact for Investment Management in many ways. Machine Learning has driven positive change especially in areas such as:

  • User experience and interfaces
  • Operations
  • Investment processes

Each of these functions has benefited from decisive improvement in terms of efficiency, managing risk, and enhancing decision-making. 

User experience

Tools using AI are now available for investors to better gain access to the financial markets and receive digital advice, including planning for retirement. Based on characteristics such as a user’s age, income, risk tolerance, and desired income in retirement, model-based digital tools can help investors select the appropriate asset allocation mix to meet their goals. Low-cost personalised investment advice, tax-loss harvesting, portfolio allocation rebalancing, and digital documentation are now highly accessible, thanks to Machine Learning.

Operational efficiency

In Investment Management, firms must serve clients at a lower cost. Technology has been key to streamlining and managing the processing of internal and external data, as well as the post-trade operational processes from confirmation, trade settlement, position reconciliation, cash balances, and NAVs. 

AI has become integral to quality checks, data cleansing, support functions, monitoring, and exception handling of vast quantities of data on financial instruments that asset managers rely on. Data quality is hugely important and making fewer operational risks to protect clients is one of the key benefits of AI. 

Investment processes

The investment process has been completely transformed. Technology has been leveraged to support data and research functions and to drive alpha signals and models, pre-trade analysis, and improving understandings of risks in a portfolio. For instance:

  • In modelling, large data sets can be analysed to identify patterns and insights to support decision-making
  • Smart beta portfolios use lenses to determine allocation, favouring certain characteristics within an index, whether it be sustainable dividends or low volatility assets. 
  • Index investing and ETFs are made possible by innovations in product structure supported by technology.

After acquiring a portfolio company, analytics capabilities opens the door to mining greater amounts of data to drive productivity and efficiency. Value capture allows you to drill down into the details, showing you exactly what particular processes need improvement. 

Following acquisition, many fund managers are arming their portfolio companies with extensive digital prowess, creating value by improving its processes, expanding and upgrading their product and service lines. This enables them to compete better against other businesses in their sectors. 

Research and Generating higher returns for clients

In Investment Management, there is now a broad range of other information available that can signal a company’s future performance. Asset managers have developed AI and ML tools to compile, cleanse, and analyze the universe of data available, including analyst reports, macroeconomic data (e.g., GDP growth, unemployment) as well as newer “alternative” data sources. 

Alternative data might include GPS, satellite imagery, internet searches, employee satisfaction data, to learn more about individual companies and portfolios. AI is leveraging real-time data to support fund managers generate higher returns for clients as a result.

Minimising transaction costs and market impact

Machine Learning is also improving the flow of trade execution. AI and ML models can assist human traders in selecting the routing destination or execution methodology which optimizes for:

  • Purchasing shares at the lowest price
  • Minimising transaction costs
  • Minimising market impact of the transaction

Trading models are able to interpret inventory, pricing data, and historical transactions to recommend what would lead to an optimal trading execution. These recommendations can then be incorporated using a smart order router, which displays suggestions to traders and sends orders out electronically.

Machine Learning is one of the biggest drivers of change within the Financial services, and we are already seeing it mitigate risk, reduce costs, generate greater returns, and deliver products and services more efficiently for clients. We’re excited to follow this trend in particular.

3- Brexit & Increased Regulatory Scrutiny

From January 2021,  the free trade and cooperation agreement between the UK and EU was enacted. Since then, UK firms have lost their passporting rights that broadly allowed UK-licensed firms to provide their services into the EU and vice versa. 

In the absence of the passporting regime, cross-border work is much more complicated. Firms are re-assessing their business activities, such as how they market their funds, amend their activities, and operational structures. 

As well as this, Brexit has meant that acquisitions involving UK and EU parties will be impacted by dual competition investigations. In the UK, the CMA will begin to take a more prominent role in reviewing international M&A deals. 

This broadly reflects a global trend for the sector. Governments worldwide are playing a growing role in M&A, expanding beyond just assessing the impact of a deal on market power and consumer interest. A number of other factors are now being considered, including national interest, data privacy, impact on future competition. To give some examples:

  • In the UK, the government adjusted a takeover law, allowing for the scrutiny of cross-border deals in sensitive industries, 
  • In Germany, the government vetoed a number of hostile foreign takeover bids in the healthcare sector. 
  • In the US, the Trump administration demanded TikTok’s US subsidiary be sold to a US buyer on the basis of both national security and data privacy.

The rising impact of regulation for the sector demands organisational agility from dealmakers and firms alike - especially as governments become further involved. In the UK, firms are finding they have to be alert to interventions from the CMA - in particular as a result of its expansion across the jurisdiction. The result? An increase in regulatory burden on acquirers, and significantly more red tape.

4- Increased M&A Activity

The M&A market saw significant slowdown at the start of the pandemic, as businesses adapted to the challenging commercial environment. However, the market quickly recovered by the end of the year, with unprecedented activity - especially in technology and healthcare. In Q4, more than 1250 global M&A transactions were announced valued at $1 trillion, exceeding historical averages. In 2021, organisations across sectors are expected to deploy further capital to accelerate growth, digitise their business, and gain scale.

We asked a number of Fund Management employees their thoughts on the biggest developments impacting M&A:

Big data and its use in AI universally

The growth of Big Data and AI is a tale as old as time. However, more recently, their applications have been massive across medicine, finance, health, e-commerce, and this is a catch-all because no part of our lives will be unaffected by this. However, with it comes a large invasion of privacy which firms are increasingly cautious to work with. 


The ability to grow and produce in a more sustainable format and reduce the unavoidable intake of huge amounts of chemicals has generated much interest from firms sector wide. 


The ability to feed our everyday requirements and make our lives more convenient is a massive opportunity - especially as it has been democratized and made increasingly accessible to the consumer.


The ability to set homework and teach a child individually in accordance to their specific needs and not just the needs of the majority in a class and with that more specific focus on specific essential areas of education 


The ability to finance via data and disrupt the traditional banking models of lending by predetermined and inflexible criteria. Being able to iron out manipulation caused by market economies for the benefit of the masses rather than the few.

5- ESG

While ESG investing has been in development since the 70s, the trend has accelerated decisively in recent years, progressing from a niche to a mainstream product offering. This is largely down to an increased demand by investors, to which a number of Investment Management firms have responded to. BlackRock, Goldman Sachs, and Vanguard are such examples who launched ESG products in 2020.

In a Deloitte survey, more than half of respondents across North America, Europe, and Asia Pacific indicated an acceleration of ESG policies, programs and products as a result of COVID-19. We expect the trend to continue with the development of data and analytics tuned to support the variations of specific ESG goals, as well as new capabilities in line with governance and reporting practices.

Current focus on ESG - data management plans have been put in place for investments, built around KPIs and related targets. Robust data strategy can help a manager automate this. D&A helps managers benchmark and monitor ESG issues material to ESG performance

Final thoughts

In 2020, the pandemic presented an enormous challenge for the investment management industry - but the industry adapted. The volatile commercial environment, personal hardship for the workforce, and the commitment to clients will lead to a stronger, more digitally capable Investment industry by the end of the year. 

As 2021 is showing, the recovery of M&A, the digitisation of firms across industries, and increased regulation is transforming Fund Management. We’re excited to see how he sector develops in the second half of the year and beyond.