Data Analysis, a Key factor in the Payment Chain
Analysis, Visualisation, Prediction.
Today’s Data science has been founded through decades of data accumulation.
In fact, we can find the first data transcript in the late 16st century with the Contingency tables of Philip the Second’s Invincible Armada, described by Paz Salaz and Alvarez.
After acouple of decades, the scientists from the 21st century succeed in stocking the data in a digital way. Thanks to this technique, they were able to make much more detailed analyses that are still used in our society.
Data science has multiple uses, from sociology to economy by the way of finance, it has always been there to help to understand metrics and underline tendencies.
Most modern businesses use data analysis to give an overall vision of their activities in a quick view.
Especially in the payment area, Data analysis gives insights on the market, highlights tendencies and offers tangible metrics which are key for understanding the business.
Data Science : a Several Facets’ Science
At Market Pay, data science is crucial to get a clear understanding of the daily activity. It enables our teams to visualize trends and predict movements on the payment market.
With its cross-functional positioning, data analysis has multiple facets and roles to play in Market Pay daily functioning.
Firstly, It helps to keep an eye on our daily activity. “How many transactions do we have per day?”, “Which types of cards have been used ?”, “Where the transactions flows are made?” etc.
These information provided give glimpses about how the machine works and if she needs to be optimised.
Then, it also helps to follow our providers’ charges, to be sure that our business model is still profitable.
Finally, the metrics analysed give several axes and points on which our teams should focus in order to stay competitive on the market and offer the best experience to our customers.
For example, our analysis gives samples to our teams to predict the payment trends and grasp news opportunities first such as the new payment methods.
Machine Learning and Data Visualisation
Data Science and especially data analysis implies several models and techniques to give an effective overview of our daily activity.
The most important of them are named Machine learning .
Machine Learning can be defined as a combination of algorithms that automatically improve themselves through the experiences they made. Thanks to the data they accumulated through their experiments, they are able to improve and create predictions.
These computing algorithms are really helpful in terms of prediction. Thanks to the data they have accumulated, they can anticipate the months to come and predict trends that might occur in a near future.
Actually, most of you already experienced machine learning algorithms.
For example, when you are typing a mail, your computer shows you some proposals to finish your sentence. This is one of the main stream experiences in terms of machine learning.
Regarding the payment market, machine learning is very useful because we get a lot of data on a daily basis.
And more particularly in terms of fraud. Thanks to our tons of metrics we can ensure our customers that their clients’ payments are safe and secured.
They also are very useful regarding reporting and decision taking.
Once the data is fully prepared, data scientists can exploit it and create efficient and resourceful dashboards.
Thanks to regressions, machine learning can predict the fews trends to come and gives the General Management insights to choose one or another strategy.
This activity is not immediately linked with our customers but it is still very precious for our teams in order to develop solutions and strategies that will benefit them.
Because at Market Pay, our priority is our customer profitability and performances.
