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Time To Modernize The Tech Stack To Support Effective Financial Research In A Post-Pandemic World

Excel, Email, and Evernote. These tools are some of the most used technologies in the investment research process. Ironic that analysts spend their days tracking massively innovative digital companies like Google, Amazon and the like, yet continue to rely on these siloed applications to fuel strategic investment strategies, never mind how they manage to communicate and collaborate with colleagues. The more distributed the information is across these individual tools, the more time it takes to uncover insights, distracting from value added initiatives and increasing the room for error in the analysis process. 

If these obvious shortcomings weren’t enough to raise a red flag, the global pandemic was instrumental in exposing significant gaps in the investment research process. Pile on the continued proliferation of unstructured data, requiring analysts to spend an inordinate amount of time combing through PDFs, social media posts, videos, audio transcripts, email and more, it’s safe to say firms have more than enough justification to modernize the technology stack and gain the competitive advantage necessary to thrive in a post-pandemic world. 

There are clear advantages of AI, machine learning, and cloud to vastly improve the investment research process, enhance analyst productivity, and achieve alpha. And while the industry has come to recognize this need for change - cloud computing was identified as the top digital priority for the financial service industry in response to the pandemic according to a Harvard Business School Analytics Services report - the actual exercise of replacing existing (familiar!) tools can be daunting.  

Organizations should first consider the inefficiencies that result in missed opportunities to focus their tech modernization efforts. For most, there isn’t a standardized way to organize, store and share information, stunting analyst workflow and limiting strategic decision making. Innovations in AI, machine learning and natural language processing are key to ensure better and faster research, organization, efficiency, and results. Meanwhile, cloud is essential to ensuring team members can easily access information – no matter where they are – and effectively share ideas, insights and collaborate. 

But where to start?  Here are three key areas to consider as you begin the tech overhaul needed to modernize your investment research process and gain a competitive edge. 

Shore up Security

The financial industry must juggle a myriad of security priorities – from protecting against savvy cybercriminals and new vulnerabilities, to safeguarding sensitive data from evolving breaches, to ensuring regulatory compliance and auditability. And as much of the workforce continues to work from home, shoring up security to enable seamless and effective collaboration means an increased reliance on cloud-based applications - which carries its own set of security concerns.

At the top of the list, with a huge responsibility for sensitive data and material, firms should bolster access controls and implement best practices to ensure safe data transfer and storage. Meanwhile, automating critical functionalities across the research process to ensure continuous operations and high availability protects internal operations and mitigates risk. Take time to review global security standards for monitoring, testing, and auditing and update accordingly to effectively protect customers.  From daily backups and emergency protocol procedures to ongoing risk management and constant monitoring for malicious activity, delivering world class data security is kingpin when modernizing your technology stack.

AI – Greater insight; faster discovery; winning strategies  

Integrating AI driven tools into the research workflow eliminates the need for context-switching and significantly reduces the time it takes analysts to find the uncharted insights that drive winning investment decisions. Advanced search technology across millions of internal and external document sources helps to surface the most relevant information fast. Meanwhile, categorization and sentiment analysis of earnings call transcripts for example, eliminates time wasted reading and marking up every transcript. Adding in this layer of AI helps analysts effectively and quickly pull out what’s important from terabytes of extraneous information, connect internal and external research and gives teams a clear view of their investment opportunities saving you valuable time and money.

Cloud – Its the new water cooler 

The global pandemic and work from home mandates expedited the need for cloud to ensure teams could effectively do their job from anywhere. To thrive in a post-pandemic world and meet evolving business requirements, organizations must consider the undisputed value of cloud-based systems to foster collaboration and seamless communication. By effectively enabling analysts to access documents, data, structure notes, dashboards and more at any time from any location, along with the ability to collaborate, empowers teams to produce the best investment ideas and recommendations. More than a “nice to have” cloud is essential to thrive in a modern world. 

Make no mistake, technology is not meant to replace the critical decision-making skills of an analyst, but the right tools can effectively augment the human element to deliver winning strategies.  Combined, this ensures research becomes a competitive advantage as opposed to a burden, positioning your firm head and shoulders above the rest.

Swati Tyagi is Vice President, Product, at Sentieo

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