The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

Our Data Analytics And Cloud Blog Roundup Of 2019

December 12, 2019 at 9:06 AM

As a data analytics company, we write about data analytics frequently: but less so on the cloud. However, as software product experts, one of our blogs on a cloud-related topic was so popular this year, we would feel terrible if you were to miss it, and so have decided to add together our data analytics and cloud topics together in this roundup.

The blogs included here, cover frequently used analytical concepts, helpful list and insightful opinion pieces.

Here are our most popular Data Analytics (and 1 cloud) blogs:

Eight question on the Gini Coefficient

Whether you’ve been involved in introducing models into your business or have had a passing interest in economic affairs, you may have come across the term “Gini-coefficient”. This blog hopes to demystify the concept and give you a good deal of information on the statistical measurement. We answer:

  1. What is the Gini coefficient?
  2. How is it applied in economics?
  3. How did it come about?
  4. What does the Gini mean with reference to a scorecard?
  5. Is it a good measure of a scorecard's strength?
  6. What other scorecard performance measurements are there?
  7. What is a good Gini?
  8. How is a Gini calculated?

Read more

Mathematical optimisation in five phases

For businesses wishing to improve their credit decisions, the adoption of Mathematical Optimisation is an important consideration. Mathematical optimisation is more than a straight data-driven strategy design as it incorporates prescriptive analytics… Read more

Top 5 LinkedIn groups to join on data analytics

With LinkedIn usage growing by two new members every second, you simply can’t afford to not be on the platform. Founded in 2003, LinkedIn has 590 million users with 260 million of those active every month.

We at Principa are very active on LinkedIn, sharing our blogs and industry news. If you’d like to view our LinkedIn page, click here.

This month, we list our top 5 LinkedIn groups on our favourite topic: data analytics… Read more

Amazon Web Services vs Microsoft Azure: Which cloud provider should you host your core business systems on?

Deciding on which cloud service to host your core business systems on can be a daunting task. Amazon Web Services (AWS) and Microsoft Azure are two of the biggest players around, while Google Cloud and IBM Cloud are also gaining market-share.

 

In this blog, we compare the two juggernauts of cloud computing, AWS and Azure, to help you in choosing the provider that’s right for hosting your business systems. A “winner” can’t be selected between the one or the other, rather we highlight the main pros and cons that will help you decide which service will cater to your organisation’s needs… Read more

Why the human mind is flawed at making credit decisions

For a while, we have been running a blog series on cognitive biases and logical fallacies that data scientists should avoid. In philosophy there are a host of informal logical fallacies – essentially errors in thinking – that crop up every day. In this series we have looked at the practice of data science to determine how these same fallacies also occur.

Today we will be looking at fallacies and their manifestation in credit: The Monte-Carlo fallacy and the Hot-hand fallacy with some studies in the credit world.

The first is the Monte-Carlo fallacy (also known as “gambler’s fallacy” or “fallacy of the maturity of chance”)… Read more

Truthseeker - logical fallacies

Latest Posts

My learnings on the effective use of automated self-service bots.

Organisations and individuals, need to adapt and change to the new ways of working to ensure that we survive this pandemic, and protect our sustainability for the future.

The time is NOW for model validation and adjustment.

One of the major premises used in credit scoring is that “the future is like the past”. It’s usually a rational assumption and gives us a reasonable platform on which to build scorecards whether they be application scorecards, behavioural scores, collection scores or financial models.  That is reasonable until something unprecedented comes along.  You can read about this black swan event in our previous two blogs here and here

10 ways the COVID-19 crisis will affect your credit models (PART 2)

This is the second of a 2-part blog. You can read the first blog here.