Technology

Data Visualization & Finance – The Way Forward

Data Visualization
Written by prodigitalweb

Data visualization with machine learning is the next big thing in Fiance sector. It has equipped finance professionals with a deeper insight into the inner workings of any organization or market, and map growth and make forecasts about financial performance. This in turn allows decision makers to take the right step forward in terms of strategy, armed with actionable financial intelligence.

Real time nature of data is the net fuel for growth of companies. Instant data availability means that companies need to be ready to consume and interpret the data for decisions. Technological interaction like Social Media plays an important role in decision making. Along with this, Data overload is key issue that financial institurions have to face. Missing out on a key data point could spell catastrophe in the long run.

The problem arises when financial experts have to explain their findings to their audience, be it the board of directors or the CEO of a company for that matter. Data visualization steps in to translate financial data and findings into actionable insights.

Data visualization allows financial experts to present their findings in a storyboard-format, allowing the audience or the decision makers to gain actionable insights at a glance and delve deep into the data to get the numbers they want, to fuel their decisions.

The visualization tools available at their disposal allow for a comprehensive review of the data, complete with interactive elements like heat maps and drill-down features, that allow for a great story-telling with the data. Also, data visualization enables financial experts to present complex data in a simplified manner, allowing decision makers to interpret the data correctly, charting out trends and patterns.

If you are a financial expert or part of a financial institution, taking the plunge into data visualization, here is a primer on best practices that you need to follow:

  1. Know your audience: Before getting started on data visualization, find out who is your audience. Who will be the final consumer of the visualization that you will be preparing? Is it your boss, is it the CEO of your company or is it a mid-level manager? Knowing who the data is for will allow you to tailor the visualization for your audience. Your audience will define your data visualization strategy. Also, make sure you know their expectations from the data, as it will help you refine your strategy even further.
  2. Be Simple: Don’t go showing off your data visualization skills! The aim here is to present the data to the audience in the simplest manner possible, as it will help them get to the insight faster. This in turn will make the decision making process faster as the output time will reduce. A simple visualization layout will allow the audience to focus on the key information presented in the dataand not get distracted.
  3. Design responsibly: While visualizing the data, make sure you pay heed to the visual elements of the visualization. By visual elements we mean the color, text font, font size and the grid layout. All of these factors could make or break your visualization. The visualization should be pleasing to the eye and not make the audience confused as to what is where. Keep the labels prominent so that the audience knows what it is looking at.
  4. Feedback is the key: You are bound to get feedbacks on your visualization. Evaluate the feedbacks careful and incorporate the important points into your visualization in order to make it better and more productive for your audience. Feedback is an important aspect of data visualization as it would tell you whether your visualization approach is right or not.

Most financial institutions struggle with the influx of data, not knowing how to make the most of it. Thinklayer offers industry leading data visualization solutions that allows clients to get the insight they need, when they need it, through custom-made data dashboards created using pre-defined industry KPIs.

 

 

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