In today’s competitive financial marketplace, big data is a fact of life. But data is useless, without the skills and tools to analyze it. Financial organizations of all sizes are realizing the importance of integrating data analytics into their processes.
In our recent blog ‘Transaction Analytics: The key to improving Customer Experience’, we focused on the crucial impact of CX on revenue, and how monitoring and analytics can fine-tune the customer journey.
Today we’ll discuss how leveraging analytics and new technologies can help payments providers uncover more intelligent insights and improve business performance.
Why analytics matter
In the business world, a massive volume of data, both structured and unstructured, inundates businesses and financial institutions every day. But it’s not the volume of data that’s important – it’s what you do with that data that counts.
Your data contains a wealth of information business leaders need to make better decisions and execute the most beneficial strategic business moves. For example, it can help you to:
- Better allocate funds, and find cost reductions
- Discover root cause failures and defects
- Better align your business with your customers’ payment preferences
- Reassess risk portfolios more quickly
- Detect fraud before it impacts your customers
- Understand buying behaviors and trends
But in order to do this, you need to turn your data into insight that is easily accessible and understandable.
How analytics can drive business growth
Analytics-driven strategies can lead to increased profitability by reducing costs and optimizing revenue in a great variety of areas. In fact, there’s a plethora of information and actionable insights to be harvested from your payment data. The most successful companies in the world like Amazon, Netflix, and Google owe that success to early investments in analytics.
Today’s new technologies make modern analytics extremely powerful and beneficial.
Machine Learning
Artificial Intelligence (AI) and Machine Learning (ML) enable algorithms to learn on their own. ML allows applications to find patterns and correlations in data at scale and without human programming. The more data a machine can observe, the more accurate the learnings, leading to greater confidence in using its recommendations.
Data Management
Analyzing data properly is about organizing and managing the flow in and out. Data needs to be high-quality, and collected in a central Data Management Platform (DMP) where it can be accessed by the appropriate organization leaders.
Data Mining
This refers to the process of sorting through the huge volumes of data to identify patterns and reveal relationships between data points, enabling organizations to assign relevance. Today’s data mining technology allows fast, accurate analysis and allows business leaders to make informed decisions.
Predictive Analytics
This technology allows organizations to analyze historical data to predict future outcomes and/or the likelihood of specific outcomes occurring. Predictive analytics enables organizations to anticipate customer needs and concerns, predict future trends and ultimately gain an advantage over the competition.
Analytics deliver real-time intelligence and actionable insights that no business can afford to be without. With transaction volumes increasing, new payment methods rapidly emerging, and greater customer expectation for a seamless, personalized payments experience, it’s vital your business can keep up with changing market demands.
With the ability to easily turn payments data into business insight, you can be confident that your organization is investing in the right areas and making the right decisions to ensure ongoing growth and success.
