The last post in this blog (handy link below) discussed my predictions for the payments market in 2017. The payments industry is large, quite diverse from a capabilities standpoint while being lucrative from a revenue standpoint.
Why is that?
First, payments are both an essential daily function for consumers and corporates alike which means a constant annual growth in transaction volumes. Volumes are the very lifeblood of the industry.
Second, thanks to the explosion of technology capabilities especially around Smartphones & Smart Apps – the number of avenues that consumers can use to make payments has virtually surged.
Thirdly, an increasing number of developing economies such as China, India and Brazil are slowly moving over massive consumer populations over to digital payments from previously all cash economies.
Finally, in developed economies – the increased regulatory push in the form of standards like PSD2 (Payments Systems Directive 2) have begun blurring boundaries between traditional players and the new upstarts.
All of these factors have the Payments industry growing at a faster clip than most other areas of finance. No wonder, payments startups occupy pride of place in the FinTech boom.
The net net of all this is that payments will continue to offer a steady and attractive stream of investments for players in this area.
Big Data Driven Analytics in the Payments Industry..
Much like the other areas of finance, the payments industry can benefit tremendously from adopting the latest techniques in data storage and analysis. Let us consider the important ways in which they can leverage the diverse and extensive data assets they possess to perform important business functions –
Integrating all the complex & disparate functions of Payments Platforms
Most payment providers offer a variety of services. E.g. credit cards, debit cards and corporate payments. Integrating different kinds of payment types – credit cards, debit cards, Check, Wire Transfers etc into one centralized payment platform. This helps with internal efficiencies (e.g collapsing redundant functions such as fraud, risk scoring, reconciliation, reporting into one platform) but also with external services offered to merchants (e.g. forecasting, analytics etc).
Detect Payments Fraud Big Data is dramatically changing that approach with advanced analytic solutions that are powerful and fast enough to detect fraud in real time but also build models based on historical data (and deep learning) to proactively identify risks.
Risk Scoring of Payments in Realtime & Batch
Payment Providers assess the risk score of transactions in realtime depending upon various attributes (e.g. Consumer’s country of origin, IP Address etc). Big Data enables these attributes to become granular by helping support advanced statistical techniques to incorporate behavioral (e.g. transaction is out of normal behavior for a consumers buying patterns), temporal and spatial techniques.
Detect Payments Money Laundering (AML)
A range of Big Data techniques are being deployed to detect money laundering disguised as legitimate payments.
Understand Your Customers Better
Payment providers can create a single view of a Cardholder across multiple accounts & channels of usage. Doing this will enable cross sell/upsell and better customer segmentation. The below picture says it all.
Payment providers have been sitting on petabytes of customer data and have only now began waking up to the possibilities of monetizing this data. An area of increasing interest is to provide sophisticated analytics to merchants as a way of driving merchant rewards programs. Retailers, Airlines and other online merchants need to understand what segments their customers fall into as well as what the best avenues are to market to each of them. E.g. Webapp, desktop or tablet etc. Using all of the Payment Data available to them, Payment providers can help Merchant Retailers understand their customers better as well as improve their loyalty programs.
Cross Sell & Up Sell New Payment & Banking Products & Services Most payment service providers are also morphing into online banks. Big Data based Data Lakes support the integration of regular banking capabilities such as bill payment, person-to-person payments and account-to-account transfers to streamline the payments experience beyond the point of sale. Consumers can then move and manage money at the time they choose: instantly, same-day, next-day or on a scheduled date in the future
Delivering the best possible highly personalized Payments Experience Mobile Wallets offer the consumer tremendous convenience by Data Lakes support the integration of capabilities such as bill payment, person-to-person payments and account-to-account transfers to streamline the payments experience beyond the point of sale. Consumers can then move and manage money at the time they choose: instantly, same-day, next-day or on a scheduled date in the future
As we have discussed in previous posts in this blog, the payments industry is at the cusp (if not already, in the midst) of a massive disruption. Business strategies will continue to be driven by technology especially Big Data Analytics. Whether this is in Defense (cut costs, optimize IT, defend against financial crimes or augment existing cyber security) or playing Offense (signing up new customers, better cross sell and data monetization) – Big Data will continue to be a key capability in the industry.
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