Asset and Wealth Management Trends to Unfold in 2021
Asset and wealth management encompasses programs that are used to maximize its productivity. This industry suffered a major setback in 2020, with mega-industry players recording minimal annual turnover profits due to the Covid-19 pandemic. According to a survey conducted by the BankingHub, in March of 2020 the industry recorded the greatest upsurge in the withdrawals from mutual funds and other investment schemes.
Despite the short-term drastic effect of the pandemic, the market posted a timely recovery with some sectors, like information technology and healthcare, peaking their earnings in under three months. The IT sector is at the forefront of ensuring business operations stay afloat online. This introduced the adoption of such measures as remote working to enforce the prophylactic social distancing regulations. This change requires tones of data and fast internet connectivity, turning the world into a global IT marketplace.
The health sector accrued much wealth with the sudden influx of patients and premise expansion to accommodate more and save lives. The pandemic has negative and positive effects on the asset and wealth management trends. But, more importantly, it pointed out the areas of improvement to ensure the business is sustained amidst its presence and the disruption of the normal order.
The investment management trends expected to take over in 2021 include data management, processing, and analytics, integration of platforms for easy assets monitoring, ML and AI. These trends, coupled with the digitization of regulations in the financial sector and the curtailment of cybersecurity, will yield an effective, secure, streamlined, and cost-efficient mode of operation.
Data Transformation — A Vital Tool Post-Pandemic for Asset and Wealth Managers
With the recent move of digitizing operations by the asset and wealth management industry, data transformation is the requisite starting point for all web digital analytics. In this process, the gathered data is cleaned, sorted, and interconverted between data types that are comprehensible by the different analytical models. This is done by on-premise or cloud ETL tools or scripting.
Data transformation implementation in the asset and wealth management industry has been stalled for a while but is now being hastily embraced. The pandemic accelerated the adoption of these techniques via the introduction of unprecedented, unique, volatile, ambiguous, and complex challenges. To circumvent them and streamline operations, asset managers have sought the aid of data transformation services as a first of a series of analyses that inform better decision making, which translates to profitability.
The digitization of the industry is imperative to maintain a competitive advantage among other players. Full digital integration of the business architectural models and operations has the potential of ascertaining a secure, convenient, reliable, and scalable working environment. Novel data trends have turned asset management firms into tech-savvy — as a way to keep up with the trend. By 2021, it is estimated that almost, if not all, wealth management firms will have their technological infrastructure hosted in the cloud.
Cloud computing integrated with machine learning will offer a myriad of services to the asset and wealth management companies for utilization in enhancing their services. Web analytics and sentiment analysis will be at the core of every decision-making analysis. Other smart tools like artificial intelligence, blockchain, and web collaboration also have game-changing potential from data processing to decision-making.
Data Management — A Strong Investment Management Trend
Data is gold. Therefore, its management is imperative in realizing its value. The asset and wealth management industry oscillates around and is dependent on data to make smart, fact-oriented, and profitable investment decisions. Multiple sources, including the internet and social media, generate financial and non-financial data. For proper utilization, this data has to be managed and analyzed to provide insights into the current market trends.
Data management is not a new concept in the asset and wealth management industry. However, with the advancement in technology, it is also facing a revolution. Data management tools are now ubiquitous with the availability of cloud services. Microsoft is one of the pioneers of cloud services, with its brand Azure, which houses the Azure data explorer. This is a cloud-based service that provides cloud computing power with data management tools that are scalable to fit your demand, reliable, traceable, secure, and highly accountable.
Cloud computing is an enabler of big data handling as it gives the provision of utilizing multiple virtual machines for data management tasks. This service has enabled asset managers to invest across a wider asset range such as blockchain for guaranteed asset security. Azure data explorer has continually improved to accommodate analytic resource integration, which can be deployed remotely. It also allows resources gathering via APIs to provide a large data set for analysis, hence eliminating the barriers to data acquisition.
Cloud computing is a must-have fundamental tool for asset and wealth management firms in 2021. It facilitates accurate data manipulation using resilient, secure, flexible, and scalable resources — only pay for what you use. It is the guide to making informed investment decisions from a sea of data.
Additionally, the cloud reduces operational costs by eliminating the cost of constructing and maintaining data centers while delivering enhanced efficiency — a sound strategy for maximizing profits. In a survey conducted by Refinitiv, it was found that asset management firms are embracing cloud solutions with approximately 90% already subscribed to different cloud providers showing a positive trend.
Data Analytics and AI — The Future of Asset and Wealth Management Trends
Artificial intelligence, machine learning, and data analytics are already shaping the asset and wealth management industry indicated by their dominance. Though these are not new technologies in this arena, their usage has experienced an upsurge in recent years due to their unmatched capabilities.
Machine learning and data analytics work synergistically to produce the best result, which is artificial intelligence. The accuracy of machine learning models solely depends on the quality of the data used to train it. Data analytics techniques ensure that the data is thoroughly processed before being fed into a machine learning model. Asset managers have leveraged the power of accurate analytics to guarantee even more accurate predictions by their ML models.
The wealth management industry has managed to propel AI and ML from the C-suite and Boardroom conversations to deployment. However, its full integration into the entire industry is yet to be realized as it currently records limited usage in various sectors. Forbes indicates that Robo advisory is the most initiated form of AI serving as bait to millennial investors. In more advanced status, companies have AI integrated into enhancing lead conversion, processing of unstructured data via optical character recognition, and algorithmic high-frequency trading.
Data scientists continue to explore more capabilities of AI and its integration. For this, it is speculated that asset management firms will soon commence implementing AI in recommending the next best action, ranking and analysis of the stocks (which is under development), real-time chatbots, investment decision making, and generating alpha. Even as the industry embraces this fourth industrial revolution centered around data, the main challenge to maximizing the utilization of AI remains to be data quality.
ML will serve as the enabler of competitive advantage in the asset management industry through the provision of unlimited operation resources. ML has seen the invention of natural language processing, hence enabling voice command applications, machine translations, and image processing for classification and clustering models. In conjunction with the cloud, their operations can be deployed economically, hence reducing the cost of entry for al firms — big and small.
ML, AI, and advanced data analytics are at the core of asset management streamlining and reducing the cost of operation as well as securing the data. They enable managers to utilize data and hasten client engagement, portfolio management, and the invincible back-end operations.
Cybersecurity and Regulatory Pressure — A Strong Asset Management Trend
The biggest challenge facing big data management is cybersecurity. Data safety is a vital component of asset management as it cements the trust of investors in the company. Clients are more attracted to an asset management company based on their technological partnerships that ascertains secure platforms than its financial performance in the market.
Cybersecurity continues to threaten the privacy of clients, assets, and institutional strategies of assetmanagement companies. Firms have implemented multiple security protocols to ensure their firewalls are impenetrable to data breaches, but only one has proven its excellence — the cloud. The cloud offers an excellent solution to cybersecurity as it delegates the duty of data protection to the cloud provider. Additionally, it offers advanced security protocols like privileged access management, cyber risk analysis, and predictions, and network monitoring.
These strategies help companies to stay ahead of their game and seal any loopholes in their security framework that make them susceptible to a data breach. AI and ML are also at the forefront in preventing cybersecurity by presenting solutions that detect and counter cyber-attacks, detect and correct false positive alerts among others. Cybersecurity is deeply embedded and dependent on AI systems. In 2021, it is forecasted that over 50% of the financial players will have migrated to AI and cloud-based solutions to combat cybersecurity and data breach issues.
The advancement of technology is happening at an accelerated rate introducing regulatory shortcomings with each new product that is developed. The asset and management industry is not exempted from these regulations and must therefore ensure that it complies. The digital space has created room to accommodate the automation of regulatory compliance by incorporating it into their systems as they constantly improve.
Asset managers should incorporate the following strategies to revamp their regulation adherence capacity with aid of technology: build compliance awareness, incorporate external tools, overhaul cybersecurity strategies, build enterprise-wide compliance programs, increase stress testing, automate compliance controls, develop robust systems, and build compliance into client onboarding. The regulations covering data protection are extensive, and the regulators are working overtime to ensure they are adhered to transparently. The only way to ensure this is done is by incorporating technology.
Application Management and Platform Integration — Underlying Asset Management Trends
Computers paved the way for the integration of technology into the workspace, but now it is the age of smartphones. In this light, most industries are striving to avail services to their consumers from the comfort and convenience of their homes and offices. Asset management has followed suit to this trend via the utilization of cloud services, the internet of things, and excellent software engineering partners like DataArt to develop customizable mobile applications with a friendly user interface.
OpenFin has been the go-to desktop operating system for financial services, but the shift is changing to accommodate other software development industry players. Asset and wealth management companies and their clients require a simple, powerful, customizable, and efficient management system to keep an inventory of their assets. The change is favoring developers investing in mobile apps, which can be integrated with the cloud to offer accurate and real time tracking to the investors on the current location and status of their assets.
Platform integration is the first step towards achieving an integrated asset management system. This is a must-have for managers in asset-intensive companies. Integration consolidates multiple systems and draws information on the individual assets available in the systems. This is a data-based approach to monitor the lifecycle of an asset across a multidimensional system. To achieve platform integration, different systems need to be regularly updated to provide current and accurate information about the assets. This enables the asset managers to access real-time information on any asset of interest.
Since platform integration aggregates all the business applications, managers can obtain data from various individual applications and subject it to data processing and analytics to obtain insights. These insights aid in making strategic business decisions and the development of novel business strategies. The vast amount of data obtained from integrated platforms can be coupled with ML and AI to enable predictive asset management solutions, which enhances exploration efficiency and reduces risk-affiliated costs.
Application management and platform integration are great steps towards achieving improved asset efficiencies and streamlining processes. This trend is highly adopted by wealth management firms as it enables them to track the performance of an asset amidst others and deduce valuable information that aids the decision-making process. Platform integration is accelerating the asset management systems market which is projected to grow at a CAGR of 10.3% from 2020 to 2025.
The asset and wealth management industry is enabled by different trends that ensure all operations run smoothly to optimize operational cost and monitor asset performance. Data transformation ensures all the vast amount of data collected by managers is converted into machine-interpretable form to be used to gain insight into the asset performance. It is requisite in the utilization of machine-based analytics.
Data management continues to be on the upsurge as new regulations on data protection, and handling continue to be enforced. Excellent management of data prevents data breaches and ensures that the identity and business strategy of wealth management companies are kept discrete. Data analytics and artificial intelligence are game-changers in asset management. They are responsible for generating crucial information for decision-making.
Regulations are mandatory in this ever-developing field, they are meant to ensure a healthy competition is maintained and rules about data management and processing are adhered to strictly. Cybersecurity is a major threat to the data and institutional strategies, measures to counter it are also evolving with artificial intelligence proving to be the perfect remedy to this unethical menace.
Application management has decentralized accessibility to assets down to the mobile phone level ensuring 24-hour access and close monitoring of assets for both managers and investors. Integration of the asset management systems has also enabled multidimensional asset data acquisition used to train predictive models. The asset and wealth management industry trends in 2021 are technology-oriented by harnessing the power of big data analytics, machine learning, and artificial intelligence to streamline the operation and enhance the security of data and assets.
What Changes Are Expected in the Asset and Wealth Management in 2021?
Much improvement is expected in the second half of 2021. The winners will be denied by their flexibility in the adoption of novel technology to improve their operational efficiency and client experience. Regulation and process automation are also in the initial stages, the paperwork associated with the onboarding process is likely to be replaced by a more streamlined digital process that includes online personal information authentication. This will hasten the onboarding experience and improve operational efficiency.
What Is the Impact of Technology in Asset and Wealth Management Beyond 2021?
Asset and wealth management trends in the last decade have been devoid of technology. However, technology is now a fundamental part of the industry, and it cannot be overlooked lest the company loses to its tech-savvy counterparts. The contemporary impact of technology in improving both the client’s and company’s experience is significant. This is an indication of better technological infrastructure to come should the same trend be maintained. Beyond 2021, the deal is simple for asset managers, either you are on the technocrats’ side or you lag behind!
Will the Regulatory Pressure Ease in 2021?
Not at all. The regulators are developing more regulations as the advancement in technology is rendering some of the previously existing regulations obsolete. Asset managers should concentrate more on regulations around: know your customer, anti-money laundering, data privacy, and Investor protection. To realize this, companies are revamping capacity in compliance, risk, and governance professionals. IT experts are also being hired to implement the technological solutions to regulations. The regulation pressure is bound to increase as they are being improved.
What Is the Importance of Data Management and Analytics in Asset and Wealth Management?
The asset and wealth management industry is both a generator and consumer of huge data. The systems used are integrated with applications through APIs to mine useful data that is used to formulate strategies and evaluate the performance of the assets. This data needs to undergo rigorous processing before it is utilized. In this case, data management plays a vital role in ensuring the data acquired is processed in line with the data protection and privacy protection regulations. Data transformation is responsible for converting the data into a form that can be understood by machines.
The data is then used to train and determine the accuracy of machine learning models. The models are later used to make accurate predictions that inform better decision-making by the managers. The cleaned data can also be subjected to data analytics to gain insights into the performance and economic state of the asset.