Re-imagining Financial Market Analysis and Forecasts With Alternative Data

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Published on
February 13, 2023

               In recent years, there has been a lot of discussion about alternative data in the finance sector, and there is an excellent reason for it. By bringing unforeseen insights into investment opportunities via real-time signals and alternate points of view, this type of data is favourably influencing the financial sector and giving hedge funds a competitive edge in the market. Additionally, it has become a crucial tool for investment companies looking for alpha, or market out performance.        

   What is alternative data?  


   Alternative data contrasts with conventional data sources including press releases and macro statistics as well as those from businesses (cash flows, financial statements, and press releases). While financial statements and reports, management and investor presentations are sources of traditional data, alternative data is unstructured and unprocessed data that must be cleaned, translated, and analysed before it can be used.  


   The usefulness of this data is in providing more thorough, detailed, and timely visibility into the variables that influence strategic choices. Alt-data can make it possible to analyse pertinent aspects through original and unusual lenses during this process.  


   The financial sector is already flooded with alternative data, the majority of which is generated by the proliferation of devices. But one key question that remains is how can it be harvested and organised into data that can provide actionable insights.  


   Types of alternative data  


   Alternative data sets come in a wide variety of forms. In their effort to produce alpha, investors use pretty much anything, from email receipts to profile picture information.  


   Some prominent categories of alternative data are listed below:      

  • Geolocators
  • Satellite Images
  • Shipping Data
  • Social Listening Tools
  • People and company data
  • Credit card data


   Benefits of alternative data  


   Whether an information edge is gained through on-the-ground assessments of company fundamentals, supply chain dynamics, or structural themes—or, in fact, through the systematisation of insights gathered from diverse alternative data—the foundation of effective alternative data serves to develop a detailed overview of a company's long-term prospects.  



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   Let’s take a look at the benefits of using alternative data:        

   1) Increased information  


   The first benefit is a common one: enhanced data implies more data. This indicates that you can learn more by enhancing your data. Additionally, it makes the information you already have more informative, so it does not merely add to the knowledge.  


   2) Increased data quality  


   Both quantity and quality are important to enrichment. In order to improve the quality of the data generally, incorrect, inaccurate, or missing data fields must be added to or eliminated.  


   3) Cost and workflow efficiency  


   An investment in data enrichment will undoubtedly pay off. Costs from errors and ineffective handling are significantly less likely to accumulate with enriched data. Richer data can be processed more quickly and easily, facilitating smoother operations and reducing unneeded annoyance for data workers.  


   4) Boosted lead generation  


   More leads are generated by enriched customer data because the contact details are more precise. Additionally, given that more information leads to a greater comprehension of the leads, those are also better leads.  


   5) Stronger sales intelligence  


   Better sales intelligence is also a result of the leads' having higher-quality data. With the help of this information, salespeople can learn more about potential clients and create better sales presentations.  


   6) Improved targeted marketing  


   Businesses can run more precise marketing efforts by enhancing alternative data. Such initiatives have a considerably higher chance of succeeding if the leads have more details and are more accurate.  


   7) Better customer care  


   Data enrichment can also aid in improving the accuracy of the customer information already available. And this makes it possible for businesses to offer better services, which leads to increased rates of client retention.  


   8) Personalized services  


   In a similar vein, after the data has been enriched, it is simpler to offer the clients individualised services. Giving your customers what they want before they ever consider asking for it involves getting to know them better.  


   Alt Data Use Cases - Harnessing the power of data in the market  


   Alternative data offers investors and financial professionals a higher degree of information. There are numerous uses for alternative data collection such as:  


   Find and evaluate potential new business partners  


   Alternative Data reveals itself to be a priceless asset for enhancing any corporation CRM. Users can enhance the assessment of future B2B customers and partners by utilising new data and datasets.  


   Utilizing these fresh datasets, you may easily pinpoint the locations of competitors or sites of interest in any chosen region where services or goods are not offered.  


   Alternative data analyses and compiles reputation and feedback information from social media sites and online channels to build a more thorough and trustworthy profile of operators and potential clients.  


   The outcome? a CRM that has been enhanced with unique insights and performance KPIs for assessing new business possibilities strategically.  


   Enhanced Client Services  


   Companies can utilise the information published online to track the effectiveness of their customer service efforts and make the required modifications with the use of alternative data.  


   For instance, a business keeping an eye on social media platforms might notice that one of its products is missing a feature and change it to satisfy client demand, or they might reply with a PR campaign that highlights the product's advantages.  


   Historical information for predictive algorithms  


   Alternative data not only offers a thorough and precise perspective of the current business environment, but banks and other financial organisations may also accurately estimate future possibilities by analysing historical data about an organisation.  


   For instance, a new hotel is asking a nearby bank for a loan. Financial statements and reputation data over a two-year period show a grim picture. One with little visitors, online reviews, earnings, and revenues. However, the bank was able to identify a great performance with thousands of consistently positive evaluations and online feedback by reviewing historical data going back up to four years.  


   Semantic Analysis and Introduction of novel solutions  


   Banks and other financial organisations all have their own reputations in addition to the corporate clients they serve. Understanding how one bank branch or the entire brand is perceived is crucial.  


   For example, a bank gathers and monitors all customer reviews and conversations on its rehional branches as well as those for a significant rival in the same region.  According to a semantic analysis, the majority of complaints made against the rival are in reference to how unhelpful the telephone operators in the various branches were. Therefore, with the help of this analysis, banks can concentrate on their strong points, emphasise them more in their marketing and communication, and encourage their staff to continue their good work in this way.  


   Opting for Alternative Data to Gain Strategic Value  


   Business executives must continue to be the strategic drivers, but data scientists are crucial in assisting in the access to and transformation of alternative data into insightful information. These consist of:    

  • Describing the most practical and effective method for the business to obtain the data from the data source (via APIs, cloud storage or file transfer protocols)
  • Transforming unstructured data into organised data using machine learning
  • Normalising the data, which includes removing duplicates and establishing links



   Bottom Line - What’s Next?  


   The world will witness the widespread adoption of alternative data prediction models and alternative data-driven revenue streams as businesses recognise the value that alternative data has to offer the economy in general and the financial industry in particular. Companies will learn to see impact when businesses learn to gather alternative data that is - Accurate, User-generated and Organised.  


   Trustworthy and dependable alternative data sources can be a crucial tool for financial institutions. To know more, get in touch with Fornax today!  


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