In the age of ‘big data’, both financial institutions and retail investors are facing the challenge of having too much information. With so much data to process and analyse, the challenge for analysts is how to effectively parse, interpret and act on this vast amount of information in a short period of time. Siloed market analysts cannot possibly hope to process the scope and scale of information alone. Markets are so fast-paced, being late to a decision can be as good as being on the wrong side of it. Although institutions have a lot of intellectual content within their firm, they have no real idea what the firm thinks about market factors at any one time. Institutions rightly have to hire well and delegate responsibility to their teams to make good investment decisions but even then money is left on the table. For retail investors, they have never had such incredible access to data and information but they lack the capacity or experience to process it all, in order to make sound investment decisions. This creates a need to leverage technology and analytics to manage the volumes of data and identify actionable insights.
The Data Deluge:
Today, there are more sources of data than ever before - CRAs, market news, 3rd party data providers, alternative data sources, and social media sentiment analysis - it can be difficult for financial institutions or retail investors to wade through it all. Processing it all, and cutting out noise, can be overwhelming and can lead to missed opportunities as well as poor decision-making due to incomplete or inaccurate analysis.
Siloed: Alone or in Small Teams:
Analysts are often siloed within their respective departments which makes it difficult for them to keep up with developing trends outside their scope of expertise. The global financial market however is complex; a ripple effect can develop and impact sectors and regions far from their origination point. As a result, market analysts may find themselves unable to accurately predict future trends or identify opportunities when variabilities change outside of the scope of their area of expertise.
Retail investors face a similar issue when trying to make informed decisions about investment in a timely manner; they are presented with too much information but lack the experience necessary to effectively analyse it all in order to make sound decisions quickly enough before prices change dramatically. Retail investors cannot rely on their team, they are often alone in their analysis or rely on forums and Reddit channels to collaborate together (see @wallstreetbets). Moreover, retail investors may not have access to the same quality of data that financial institutions have access to. This lack of access can make it difficult for retail investors to make informed decisions without potentially missing out on good investment opportunities or suffering losses due to unforeseen risks that were not considered beforehand due to a lack of knowledge about certain markets or securities.
Data Hygiene and Quality Assurance:
When there is too much information, all investors have to ensure that the data is accurate and up-to-date. Data must be consistently monitored and evaluated for its accuracy. If the quality assurance standards are not met then it can lead to incorrect conclusions, decisions or interpretations based on bad information. Additionally, disparate sources from multiple departments must be consolidated into one source making sure that everyone has access to the same version of the truth across all departments in order for effective decision-making processes.
This is the way… Innovating with Technology and Analytics
To address this challenge, organisations need to innovate by leveraging cutting-edge technology and analytics. Technology can help automate processes so that more time can be spent analysing the data instead of collecting it. Additionally, analytics can help analysts identify patterns in large datasets quickly and accurately so that actionable insights can be extracted from them. Automation and analytics can help analysts to spend less time manually searching through news and large datasets looking for relevant trends or correlations, allowing them to focus on interpreting what these trends mean for their organisation or clients.
Go further… with Human-in-the-Loop AI, ML and NLP
Financial Institutions and retail investors should leverage AI-based technologies such as human-in-the-loop AI, machine learning (ML), and natural language processing (NLP) algorithms which can process large amounts of unstructured text quickly and accurately. These AI-based technologies will allow analysts to forecast better market performance. Analysts will gain deeper insights about markets faster than ever before, giving them an edge over their competitors who are still relying on manual processes or traditional methods for analysing data.