Key Use Cases For Payments Data Analytics

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With more people transacting online, collecting customer data across channels and experiences is easier than ever. This data is especially useful for improving the customer experience, detecting patterns, identifying trends, and fueling proactive strategy. In the case of payments through online payment gateway, the ability to capture these customer insights has allowed businesses to anticipate customer requests and detect fraudulent activity before it causes damage.

According to Mordor Intelligence research, the big data Analytics market will grow at a compound annual growth rate of 22.97 percent between 2021 and 2026 due to the vast impact of data on the payments industry. This growing investment in big data is directly related to the rise in fraud; according to Mordor Intelligence, finance organizations lose more than 5% of their annual revenue to fraud. Companies cannot afford to ignore data analytics because it is critical to successful fraud prevention.

Data collection alone is insufficient. Companies must understand where to collect data, what questions the data answers (or prompts), how data can inform strategy, ...
... and how analytics fits into their current operations. Only then can the full potential of data be realized.

The Added Value of Data Analytics
Data analytics can quickly organize massive amounts of data to provide critical insight for businesses looking to optimize operations. Effective data analytics can have an impact on all areas of the business, as illustrated by the examples below.

In general, the ability to synthesize large amounts of data and identify patterns can be useful for both refining existing processes and informing new ones. Payments data can reveal operational hiccups, critical behavioral trends, and new opportunities for business growth.

Data is also multi-purpose; businesses can feed the same data into multiple analytical programs to reveal different insights, resulting in a complex and complete view of the customer. For greater added value, this information can then be integrated into various areas of the business or even sold to partners.

Specific Use Cases of Data Analytics in Payments
Data has the potential to transform a company's operations when used correctly. Payment institutions can focus their strategy on key business areas that would benefit the most from this additional insight with the right data analytics program. This allows you to be proactive rather than reactive and stay ahead of your competitors.

Lending, Payment & Transaction Analysis
Payments companies can collect and track customer activity data to gain a macro and micro view of spending patterns. This can then be used to determine which products and services to offer customers. Thanks to transaction analysis, credit limit increases and special promotions can be more accurately extended, increasing the chance of conversion while minimizing risk on the company's behalf.

Fraud Prevention
When there is a better understanding of daily customer activity, it becomes easier to identify deviations from the norm on both an individual and collective level. Machine learning models can identify anomalies in customer behavior faster and more accurately than manual review. This ultimately saves time and money while decreasing costly false positives, which can erode trust and cost businesses money.

Machine learning models can also detect and warn about potential cyberattacks, allowing for faster response times and a more proactive approach to security. By noting when and how attacks are most likely to occur, this level of visibility can also provide useful insights to strengthen existing prevention protocols.

Risk Management & Investigation
Lending money and supporting digital transactions carry a certain amount of risk. While this can never be completely eliminated, smart data analytics use can reduce risk and allow businesses to be more confident in their customer management. A detailed analysis of a customer's payment behavior — from repayment rate to number of defaults on the account — can provide rich customer profiles aimed at reducing risk.

Marketing & Product Management
Strategic businesses are always looking for opportunities to upsell in addition to keeping customers satisfied with their current service. Data analytics can reveal which approaches have been successful in the past, as well as identify new trends in customer preferences that may inform future strategies. Data can be used to fine-tune marketing language and product offers — the possibilities are truly endless.

Most businesses have a wealth of data at their disposal. Payment companies and the best online payment gateway can refine their offerings, reduce risk, and prevent fraud by utilizing advanced data analytics effectively.

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