How hyperautomation for capital markets drives efficiencies and insights for hedge funds, crypto investors, asset managers, and more.
In capital market investing, numerous options lead to vast opportunities. The ability to trade a wide variety of securities opens doors to new wealth creation for asset managers, hedge funds, and crypto investors with the insight and skill to make the right decisions. But, with each new investment, portfolio managers gain more information about the specific security and the market to which it belongs. So, while more choices create opportunities, they also naturally bring complexity. The companies that truly succeed in capturing the potential of these opportunities are those that can swiftly manage this increasing complexity.
This is the exact challenge hyperautomation has been created to solve. This guide: Hyperautomation for Capital Markets has been written specifically to address the challenges, opportunities, and benefits of this emerging technology.
What is hyperautomation?
Gartner defines hyperautomation as “a business-driven, disciplined approach that organizations use to rapidly identify, vet and automate as many business and IT processes as possible. Hyperautomation involves the orchestrated use of multiple technologies, tools or platforms, including: artificial intelligence (AI), machine learning, event-driven software architecture, robotic process automation (RPA), business process management (BPM) and intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, and other types of decision, process and task automation tools.”
At Everysk, we define hyperautomation for capital markets as technologies that provide two key benefits to our clients:
- Increased efficiencies through the reduction or elimination of spreadsheets, custom software development, and other technologies that do not scale as needs and complexities increase.
- Increased insights by introducing complex calculations that provide greater visibility into potential investment outcomes.
The insights derived from Everysk distinguish hyperautomation from mere robotic process automation (RPA). Though RPA alone enhances the efficiency and compliance of capital market investors, integrating complex calculations enables the same firms to outperform their peers by providing superior insights. Thus, hyperautomation gives firms the advantages of RPA, and much more.
To capitalize on hyperautomation, firms need a platform that facilitates data ingestion, transformation, validation, and delivery across multiple systems, with applications in portfolio management, trading, risk analysis, reporting, and regulatory compliance.
In this article, we will dive into the advantages of hyperautomation for capital markets and examine how investment firms can tackle these challenges and harness the power of automation to unlock valuable insights and secure a competitive edge.
Capital Market Investors Have Access to More Data Than Ever
Today, investment firms have access to an unprecedented amount of data. Information fuels investment, as each piece contributes valuable insights into market trends, opportunities, and risks. However, investment firms need an automated way to process and analyze all this information to keep up with the rapidly evolving data landscape. Automation also plays a key role in rapidly testing portfolio metrics with prescribed limits and proposing remediation plans.
However, data online exists everywhere in limitless formats, which compounds the challenge of making it accessible and actionable. Portfolio data comes from diverse sources, such as market data providers, prime brokers, custodians, portfolio management systems, accounting systems, and proprietary models. Often, these platforms lack native integrations with one another. However, API integrations – which enable data sharing between multiple platforms – are quickly becoming the standard. Unlocking data from one platform allows providers to synthesize information on their own platforms, although this process can also be complex. With Everysk’s deep understanding of technology and commitment to personalized solutions, we guide clients in navigating these challenges and maximizing their data.
Ultimately, even if firms acknowledge the value of the data they desire to use and possess the technical means to do so, they must act on these insights within the boundaries of compliance. Regulatory bodies enforce stringent rules and standards on how firms handle their data, risk, and reporting. Non-compliance can lead to fines, reputational harm, and a loss of trust from clients and stakeholders. Consequently, firms can leverage more information than ever before, but they must also shoulder the responsibility of doing so in a manner that adheres to all relevant regulatory requirements.
Essential Elements of Hyperautomation for Capital Markets
Hyperautomation refers to solutions encompassing multiple types of technologies, such as:
Robotic Process Automation (RPA):
RPA enables robots or “bots” to perform repetitive, structured tasks in digital systems. Its benefits are restricted to speed and efficiency. RPA does not provide analysis or insight but executes predefined processes more swiftly. Its goal is not to make better decisions than humans but to do so in a faster, structured manner with fewer errors.
With RPA, organizations may utilize unattended bots, which handle all of the necessary automation, or attended bots, whereby the technology assists with repetitive or time-consuming tasks, with pauses for human interaction.
Artificial Intelligence (AI):
AI is a branch of computer science that allows machines to perform tasks typically requiring human intelligence, such as perception, learning, decision-making, and natural language processing. In capital markets, AI helps analyze vast amounts of data, identify patterns, and make predictions, enabling financial institutions to make more informed decisions. AI techniques like machine learning, natural language processing, and cognitive computing automate processes, manage risks, and boost profitability in capital markets. AI is expected to transform capital markets operations through faster, more accurate decision-making, cost reduction, and improved customer experiences.
A subset of AI, machine learning uses algorithms and statistical models to analyze data and identify patterns, empowering financial institutions to make more accurate predictions and informed decisions in capital markets. Techniques like regression analysis, neural networks, and decision trees help learn from historical data and enhance accuracy over time. Machine learning can improve efficiencies, manage risks, and increase profitability by automating processes and reducing manual intervention. For capital market investors, Everysk’s robust calculation engine utilizes powerful formulas proven valuable to asset managers and finance professionals.
The list of technologies comprising hyperautomation grows daily and includes intelligent business process management suites (iBPMS), process mining, natural language processing (NLP), and more. Likewise, the Everysk platform is designed to leverage emerging technologies that present opportunities for capital market investors to gain an advantage. With our deep understanding of technology and commitment to personalized solutions, we guide clients through the complexities of hyperautomation, helping them unlock its full potential.
Key Benefits of Hyerautomation for Capital Markets
The technologies mentioned earlier offer capital market companies powerful benefits over their competitors. These advantages can be broadly categorized into efficiency automations and insight automations.
Efficiency Automations Save Time
Efficiency automations help investment firms save time by streamlining data ingestion, transformation, validation, and delivery across multiple systems. These automations ensure data is entered accurately and consistently into different systems, reducing the risk of errors and ensuring the information is readily available when needed.
Efficiency automations also decrease the need for manual data entry, allowing staff to focus on other critical tasks. In cases where firms aim for rapid growth, efficiency automations provide a shortcut by reducing the need to hire as many professionals in a short timeframe.
As mentioned earlier, robotic process automation (RPA) benefits align with efficiency automations. Unattended bots autonomously complete established tasks, while attended bots perform simple tasks and pause for required human intervention. The advantages of efficiency automations lie in the speed of task completion and the reduced errors resulting from automation.
Insight Automations Inform Better Decision Making
Insight automations enable investment firms to gain a competitive edge by generating actionable insights from user-defined criteria. With these automations, firms quickly identify market trends, risks, and opportunities and respond promptly. Insight automations also help firms monitor key performance indicators, identify patterns in data, and create customized reports that provide valuable insights into their investment operations.
While insight automations are undoubtedly faster through hyperautomation, they are also distinct in that they aim to provide information that would be overwhelming to calculate without automation.
The Challenges of Automation Within the Capital Market Sector
Although technology is advancing rapidly and the benefits of hyperautomation are evident, capital market companies have been slow to adopt these technologies. Below are some challenges that investment firms face when considering hyperautomation.
Closed and siloed capital market systems:
Historically, capital market systems have not integrated with other platforms or processes. Many data providers and investment platforms are hesitant to open up their systems to third-party integrations or customizations, creating information silos that are difficult to integrate.
Compliance concerns with automations:
Though compliance is undeniably ripe for automation, noncompliance penalties are severe. Consequently, firms with inherent concerns about technology can still be reticent to turn over responsibilities to software that people have traditionally shouldered. While technology laggards represent an ever-shrinking percentage of firms, roadblocks preventing automation are likely to appear wherever they exist.
Time and resource investments for automations:
Adopting automation technologies may require significant investments in time and resources, including technology development, staff retraining, and potential shifts in organizational culture. These factors can make firms hesitant to adopt these technologies.
Lack of industry standards in capital markets
The investment industry often involves complex financial products and services that require customized solutions, making it difficult to find ready-made automation technologies that meet unique needs. Firms may need to invest in customized solutions or develop proprietary technologies, which can be time-consuming and costly.
Automation companies don’t understand the investment industry
One primary challenge of automation is finding a company that understands the intricacies of the investment management industry. Many technology companies offer generic solutions that do not cater to the specific needs and nuances of investment management. Everysk, founded by investment professionals, offers a platform designed to address the specific pain points and opportunities of investment managers.
Capital markets are not inherently a technology-rich category
Capital market companies may not have a readily available supply of developers capable of writing the code required for robust automations. This logistical challenge highlights the need for no-code or low-code solutions. These modern software development approaches use visual interfaces and drag-and-drop tools, allowing users to create and deploy applications quickly, with reduced costs and development time.
Less than 1% of the working force globally knows how to write code. No-code and low-code solutions enable non-technical users to participate in the development process, making it more accessible and collaborative. While these development methods are gaining popularity, the trend is strongest in industries that need to adapt quickly and lack large-scale development teams, such as capital markets.
Despite the Challenges, the Benefits of Hyperautomation for Capital Markets are Too Great to Ignore
Though the challenges above represent concerns in the marketplace, they’re swiftly being overcome as investment firms recognize the potential for better results through automation.
In fact, a study by Deloitte revealed that while fewer than 4% of respondents had deployed RPA in 2019, more than 23% planned to do so in the near future. Similar figures were reported for machine learning and AI.
In this the data are clear. Capital markets are rapidly embracing hyperautomation and all of its possibilities.
Everysk: a Hyperautomation Platform Engineered for Capital Markets
Recognizing both the challenges and opportunities for hyperautomation in capital markets, Everysk was developed with the specific intent to deliver automations and insights to the highly regulated capital markets industry. The following reflect how Everysk is overcoming the key challenges identified above.
Designed Exclusively for Capital Market Managers by Capital Market Managers
Everysk, from its inception, has been dedicated solely to the capital markets industry, unlike industry-agnostic automation solutions.
Our founder, Dr. Allan Brik, earned his PhD in Computer Aided Engineering from MIT but spent his career managing risk for large firms like Merrill Lynch and Goldman Sachs and as a CRO for Arden, a $ 14 billion institutional fund of hedge funds. This experience enabled Dr. Brik to understand the intricate workings of the capital markets while keeping an eye on emerging automation technologies.
While at Arden Asset Management, and as part of his group’s mandate, he evaluated the infrastructure of hundreds of investment firms to realize that despite good alpha ideas, many of those firms lacked proper infrastructure to command institutional investments. While their investment strategies may have been sound, determining how, when, and how much to invest required the management of cumbersome spreadsheets that struggled to keep up with dynamic, disparate datasets.
Everysk’s platform, at launch, showcased cutting-edge automation and analytics capabilities tailored for capital markets, including:
- Compliance as a core component, not an afterthought
- A fully open architecture for seamless integrations, both present and future
- An industry-leading calculation engine providing unprecedented insights for portfolio managers on market, liquidity, credit and counterparty risks
Yet Dr. Brik’s vision went beyond mere features; he aimed to make them accessible through a no-code, low-code approach, allowing widespread adoption by market-savvy professionals, regardless of programming knowledge.
Today, Everysk is a comprehensive platform addressing investment firms’ unique needs and complexities while overcoming automation challenges. Its flexibility enables customization and seamless integration through a powerful API, enabling a vast amount of connections to third parties. As a result, firms can automate workflows, streamline operations, save time, and reduce manual intervention.
Advanced analytics capabilities on Everysk’s platform fuel deeper insights and informed decision-making. Data visualization, trend analysis, and predictive risk modeling tools are readily available.
In summary, Everysk equips investment firms with the tools and support to automate workflows, achieve significant efficiencies, and gain valuable insights. By eliminating manual work and streamlining data processing and analysis, investment firms can focus on delivering better client value and attaining improved business outcomes.
Hyperautomation for Capital Markets: A Simplified Technical Guide
Everysk’s powerful automations and analysis are possible through a multi-step process that prepares data for calculation, regardless of source or format. This section details how Everysk captures and processes data.
Within Everysk, a portfolio is a collection of investments in individual securities to achieve specific goals, such as uncorrelated market returns, index outperformance, capitalizing on temporary mispricings (relative value), fundamental investing, and more.
Portfolios are assembled by an asset management company’s portfolio manager or customized for clients within the company’s wealth management division. Portfolios also play a significant role for administrators, custodians, OMS platforms, and other stakeholders responsible for managing client assets or executing trades that need to be added to existing portfolios.
Everysk portfolio data goes through five distinct phases, as detailed below.
Phase 1: Data Ingestion
Data ingestion is the starting point for automated workflows, where positions from various sources come together into a comprehensive portfolio view. The process involves six key steps: connectivity, parsing, mapping, consolidation, look-through, and error handling.
Connecting to different data sources, such as banks, custodians, administrators, prime brokers, and other platforms, is essential for creating a unified portfolio. Everysk’s intuitive interface enables users to receive files from sources like sFTP, API, or email attachments, simplifying the process.
Successful integrations through connectivity set the stage for the powerful workflows that come next.
This step involves extracting and transforming data from different sources and formats. For example, a date format like 12/31/2022 might need to be changed to 20221231, or an options ticker on Microsoft stock (MSFT211008) may need its underlying security ticker extracted for proper mapping.
Mapping aligns the parsed information with appropriate fields, allowing the platform to effectively understand and use the data. For example, providing an ISIN helps the platform access valuable information about a security, such as sector, market capitalization, recent news, and earnings data.
This step combines data from different sources into a single view. For instance, if a user allocates new trades to a loaded portfolio, somebody must map these trades to their correct portfolio. Likewise, multiple trade lots of Apple shares from various traders must be consolidated into a single exposure of Apple at the portfolio level, for instance.
Look-through allows managers to drill down into multiple levels of portfolio data for analysis. For example, if a portfolio contains an ETF, the ability to view the holdings of the ETF as individual securities while recognizing they are part of the ETF position in the portfolio enables a holistic analysis of all securities held.
The final step involves identifying and, if possible, rectifying errors. Automated reconciliation measures can resolve errors individually and automatically without re-running the entire process, streamlining the process and reducing manual work.
Bringing the elements of data ingestion together for hyperautomation
Potent hyperautomation platforms must be capable of handling each element of ingestion and providing a robust alert mechanism for when ingestion fails.
For example, a user may hold corporate bonds with a Swiss bank that provides data in a CSV file via sFTP and liquid derivatives with a US broker offering full API capabilities. Everysk addresses these differences in connectivity and format to generate a holistic portfolio, considering important factors like cash merging and margin accounting, while tracking unsuccessful parsing with bots for integrity checking and error handling.
Phase 2: Data Preparation & Calculation
After completing data ingestion, the focus shifts to data preparation, which requires deep domain expertise and goes beyond the capabilities of off-the-shelf RPA solutions. In this phase, Everysk’s platform comes into play, utilizing bots that act as wrappers for integrated APIs.
These bots take a complex portfolio and various calculation settings (confidence level, horizon days, decay, etc.), call an integrated API, and return results at the individual security level. These results are then aggregated in a structured data matrix called a datastore. Within an Everysk datastore, each column represents a property, while each row corresponds to a security. This streamlined approach to data preparation enhances the platform’s efficiency and effectiveness in handling complex calculations for alerts and reports.
Columns are customizable according to required parameters but typically include:
A unique set of characters assigned to a particular security for trading purposes.
- Security Name:
The name of the security being traded.
- Market Price:
The current price of the individual security in the market.
- Market Value:
The total value of a position or portfolio.
- Net Exposure:
The difference between long and short positions in a portfolio.
The number of shares of a security held in a portfolio.
The physical or virtual marketplace where securities are traded.
The type of currency used to buy or sell a security.
- FX Rate:
The exchange rate between two currencies.
- Asset Class:
A group of securities with similar characteristics.
- GICS Sector:
A way of categorizing companies based on their primary business activity.
- Portfolio Date:
The date when the portfolio was evaluated.
- Portfolio Name:
The name given to a specific portfolio.
A tag used to categorize or identify a specific security or portfolio.
- Unrealized P&L:
The profit or loss on a security that has not yet been sold.
- Liquidity Bucket:
A grouping of securities based on their level of liquidity.
- Market Capitalization:
The total value of a company’s outstanding shares.
- ESG Rating:
A rating system that evaluates a company’s environmental, social, and governance practices.
A measure of a security’s volatility in relation to the market.
- VaR (%):
Value at Risk, a statistical measure of the maximum loss a portfolio may suffer in a given period.
- Historical Volatility (%):
The past fluctuation of a security’s price.
- S&P 500 Stress (-5%):
A simulated pricing scenario where the S&P 500 index drops by 5%.
- Compliance Test:
A check to ensure that a portfolio or trade complies with regulatory requirements or internal policies.
The platform should generate new datastores daily to achieve the best possible insights. Properties must be additive, and bots should be designed to add rules-based columns. These bots are combined into automated workflows, all without requiring database or coding knowledge.
Naturally, more comprehensive insights demand additional bots and workflows. During data preparation, consider using bots that add rules-based columns, which will become crucial in the data exploration phase.
For instance, required columns indicating specific future or cash security categorizations can be employed for in-depth analytics and automations.
In this stage, properly ingested portfolio information is merged with third-party and calculated data through the automated workflows and integrated API.
With portfolio positions now connected to Everysk’s powerful calculation engine and third-party data, the foundation is laid for an impressive data exploration experience.
Phase 3: Data Exploration
With the help of powerful tools, exploring properly aggregated and prepared portfolio data can lead to valuable insights and automated reports and alerts at scale. Data that uses the robust datastores from Phase Two is now dynamically bound into reports and alerts through manipulation techniques such as filters, aggregations, and transformations.
With relevant, accurate datastores, asset managers can now envision powerful “what if” scenarios that go far beyond the capabilities of Excel or other more robust analytics tools. Capital market managers use Everysk to build powerful reports like these:
Historical Scenario Analysis Report:
Analyzes how your portfolio would have performed if specific historical events or market conditions had been applied. Benefit: Helps evaluate your portfolio’s resilience to past crises and market changes.
Sector Rotation Strategy Report:
Explores the potential impact of reallocating investments among different GICS sectors based on market trends and economic indicators. Benefit: Identifies optimal sector allocation for maximizing returns and minimizing risks.
Currency Hedging Impact Report:
Evaluates the effect of implementing a currency hedging strategy on your portfolio’s performance, considering historical and projected currency movements. Benefit: Assesses the potential benefits of hedging currency risk.
ESG Rebalancing Report:
Analyzes the potential impact on portfolio performance and ESG ratings if specific investments were replaced with more sustainable alternatives. Benefit: Supports transition to a more responsible and sustainable investment strategy.
Backtest Benchmark Report:
Compares the hypothetical performance of your portfolio versus a passive index-tracking strategy. Benefit: Evaluates potential trades in terms of potential returns and risk mitigation.
Interest Rate Sensitivity Report:
Assesses the potential impact on your portfolio if interest rates were to rise or fall in the future. Benefit: Helps prepare for changes in the interest rate environment and identify potential risks or opportunities.
Pre-trade Compliance Report:
Adds intra-day trades to portfolios in order to verify if the new trades will breach any investment policy guideline and/or regulatory limit.
Margin Optimization Report:
Estimates next day required margin.
Phase 4: Alerts
As we’ve seen, Everysk hyperautomation for capital markets allows a tremendous amount of data to be normalized and analyzed according to the rules determined by the user. While such data is inherently valuable, the ability to respond to predetermined market conditions when appropriate is where true capital market managers can gain significant advantage from the platform. Everysk users maintain constant vigilance through our automated alert system.
As customizable as the workflows themselves, we suggest customizing your alert criteria according to the following criteria:
Type of Alert:
The specific events that trigger an alert, such as price changes, compliance breaches, risk metrics crossing thresholds, or trading conditions.
Manner of Alert:
The format and medium through which the alert is delivered, such as email, push notifications, or in-app messages such as Microsoft Teams.
Role of User:
The specific user roles that receive alerts, allowing for data governance and tailored notifications based on the responsibilities and interests of different users.
Frequency of Alert:
The intervals at which alerts are generated, such as real-time, daily, weekly, or based on custom timeframes.
Severity of Alert:
The level of importance or urgency of an alert, allowing users to prioritize actions based on the criticality of the situation.
The ability to configure and personalize alert settings, including the criteria, thresholds, and preferences for each user or role.
The inclusion of relevant information, recommendations, or suggested actions within the alert to help users make informed decisions in response to the triggered event. For example, the alert could include data from downstream in the workflow.
The capability to track and analyze the effectiveness and impact of alerts, such as the number of alerts generated, response rates, and any resulting actions taken by users.
A system for escalating unresolved alerts or issues to higher authority levels or additional team members to ensure timely resolution.
Within Everysk, clients customize all alerts according to their specific requirements. Doing so ensures that the vital insights uncovered by the platform are timely, relevant, and highly contextual.
Phase 5: Distribution
Everysk’s powerful alert system provides real-time notifications of time-sensitive information. However, the system can also be leveraged for the distribution of reports compiled in Phase Three (Data Exploration).
In addition to the content itself, asset managers can customize many elements of the report, including:
Choose from various formats specific to your use case. Likewise, build summary reports with immediate high-level information or data-rich reports that provide more granularity.
Choose from email, push notifications, or in-app messages like Microsoft Teams. Be sure your reports reach you where you are so you never miss them.
Security & Confidentiality:
Protect vital data. Ensure only intended recipients can view the reports with custom permissions designed for data integrity.
Determine when reports are sent. Customize timing so your data is at its most relevant when it needs to be.
Custom views of reports according to pre-established criteria.
Maintain audit trail of reports for future reference.
Hyperautomation for Capital Markets: the Final Word
The capital markets industry has long been characterized by many repetitive tasks, making it a prime candidate for automation. However, the true opportunity lies in embracing hyperautomation, which transcends mere efficiency and elevates performance to new heights.
As the industry recognizes the immense potential of hyperautomation, Everysk emerges as the obvious choice for capital market managers. With its robust platform, Everysk seamlessly combines domain expertise, advanced technology, and adaptable workflows, enabling stakeholders to tap into many benefits beyond streamlining processes.
The journey towards hyperautomation for capital markets with Everysk begins with robust data ingestion and preparation, followed by strategic exploration and analysis. Capital market managers can use Everysk’s intuitive platform to empower themselves with the tools and insights necessary for superior decision-making and performance.
In the era of hyperautomation, stakeholders can look forward to an environment where efficiency, intelligence, and performance align to forge a new, transformative path for capital markets. It is time for capital market managers seeking the benefits of hyperautomation to explore the opportunities that Everysk offers and elevate their operations to the next level of success.