Data

J. P. Morgan: Using Transaction Data To Help Merchants Optimize Cash Flow

As merchants accelerate their digitization roadmaps, the volume of data they’re able to work with increases.

But data in payment transactions provides an often-untapped opportunity for merchants to optimize their payment operations and grow their businesses, Tony Wimmer, head of data analytics for J.P. Morgan Wholesale Payments, told PYMNTs.

When optimizing payment operations, “it can all boil down to: How do you help a merchant approve the most transactions at the lowest possible cost?” said Wimmer, who oversees the data and analytics efforts of firm’s payments-focused businesses.

While bringing payments data all into one place is a necessary first step, just collecting information isn’t enough.

“The challenge you really have is that with payments transactions, there is a tremendous amount of data, but data itself isn’t very useful,” Wimmer said. “You've got to transform it into actionable insights.”

The Nine Levers Of Data Optimization

As Wimmer explained, his team of more than 150 data scientists, machine learning (ML)/artificial intelligence (AI) experts and data engineers has developed nine “levers” to help merchants optimize their payments performance.

Six of these levers are all about optimizing payment authorization data to ensure card transactions are approved at the highest possible rate. Before a transaction even happens, there are two levers merchants should systematically consider.

The first is “wallet cleanup,” which ensures that customer payment credentials are up to date. The second is transaction timing, which can make sure that the customer actually has sufficient funds in their account at the time of payment authorization.

Then during the initial transaction, there are three levers the merchant should focus on. A very important lever is optimizing transaction message data elements, which involves understanding which elements of a payments message work best depending on the customer’s card issuer. Routing a transaction through a different network — for example a PIN-less debit network — can in certain situations lead to a higher approval rate.

The fifth authorization lever involves authentication in Europe with PSD2 regulations, which require an elevated level of customer authentication. After an unsuccessful initial transaction, the sixth lever is about a “retry strategy,” or developing a systematic approach to retrying a transaction in case of a decline.

The last three levers are all about using insights from data to lower the cost of payments acceptance for a merchant. These include systematically detecting interchange downgrades, identifying cost-saving opportunities by transmitting level two/level three transaction data, and routing through networks with the most favorable economics for a merchant.

“I want to emphasize these levers shouldn’t be seen in isolation,” Wimmer said. “They are interdependent.”

He said only focusing on one lever like approval rates can end up leading to worse cost of payments or worse fraud. Wimmer said merchants should ensure they work closely with their acquirer to evaluate the levers holistically.

Growing Your Business

“Payment data can be what they call ‘your canary in the coal mine,’” Wimmer said. “If you see a trend in a very important customer segment that is accelerating, you want to know sooner rather than later to take corrective measures.”

To achieve this objective, merchants can leverage payments data to better understand their customers’ behavior.

Wimmer said that as one of the major issuers, J.P. Morgan has lots of insights into customer behaviors in issuing data. When used in aggregate and de-identified format to comply with privacy standards, such payment data can provide businesses with valuable insights while meeting compliance requirements and maintaining high security standards.

“This data can provide insights into how and where customers shop, when they shop, and how a merchant is performing with a particular customer base compared to industry peers,” Wimmer said.

Taking The Headache Out Of Cash Flow Forecasting

Wimmer said J.P. Morgan aims to help merchants avoid spending time collecting, cleaning, organizing and interpreting data and instead focus on making more informed decisions using the information gathered.

Organizations can then wield this information to optimize their own payments and financials. Thanks to accelerated digitization of accounting and finance functions like accounts payable, treasury professionals are empowered through automation and have more time for value-added operations like cash flow forecasting — another area that can benefit greatly from such transaction data.

Wimmer said that optimizing working capital is one of clients’ biggest priorities, and its AI-based cash flow forecasting capabilities “enable them to do that at a click of a button.”

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NEW PYMNTS DATA: HOW WE SHOP – SEPTEMBER 2020 

The How We Shop Report, a PYMNTS collaboration with PayPal, aims to understand how consumers of all ages and incomes are shifting to shopping and paying online in the midst of the COVID-19 pandemic. Our research builds on a series of studies conducted since March, surveying more than 16,000 consumers on how their shopping habits and payments preferences are changing as the crisis continues. This report focuses on our latest survey of 2,163 respondents and examines how their increased appetite for online commerce and digital touchless methods, such as QR codes, contactless cards and digital wallets, is poised to shape the post-pandemic economy.

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