Abstract

Capital Markets are one of the most important pillars of worldwide economy. They gather skilled finance and IT professionals as well as economists in order to take the best investment decisions and choose the most suitable funding solutions every time. Data analytics projects in Capital Markets can definitely be very beneficial as all optimizations and innovations would have a financial impact, but can also be very challenging as the field itself has always incorporated a research component, thus finding out what could really be of an added value might be a tricky task. Based on a comprehensive literature review, this paper aims to structure the thoughts around data analytics in investment banks, and puts forward a classification of relevant data analytics use cases. Lastly, it also discusses how transforming to a data-driven enterprise is the real change investment banks should aim to achieve, and discusses some of the challenges that they might encounter when engaging in this transformation process.

Highlights

  • Capital markets are one of the most important and complex fields in worldwide economy that involves multiple stakeholders, among which investment banks are the main actor

  • This paper aims to provide a classification of relevant data analytics use cases for investment banks, and discusses the importance of engaging in a data-driven transformation and some of the challenges that could be faced in this process

  • This paper describes why, more than ever, launching analytics initiatives is important in investment banks

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Summary

INTRODUCTION

Out of all the activities performed in capital markets, portfolio management is one of the most important ones It focuses on decision making with regards to investments for individuals or institutions, taking into account the investment policy, objectives, asset allocation, risk and performance [4]. Based on the financial challenges of each, investment banks advise their clients on the best approaches to raise capital taking into account the current investment climate as well as the client’s needs [6] This applies to mergers and acquisitions’ scenarios where businesses are often looking to restructure by purchasing their competitors. In addition to the risk management, internal controls, accounting and IT functions among others Given their very diverse missions, investment banks’ departments often have opposite views on market trends, look for different opportunities, offer various services to the same clients, and collect distinct data inputs as well as analyze and process them differently

DATA ANALYTICS IN INVESTMENT BANKS
Prediction of Financial Market Patterns
Detection of Crisis Situations
Client Risk Profiling
Product Recommendation for Clients and Prospects
Simulation and Recommendation of Market Trades and Investment Strategies
Optimization of Internal and Support Processes
Use Case Prioritization
Cloud Integration
Data Architecture
Event Sourcing
Findings
CONCLUSION AND FUTURE WORK

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