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.
Big Data as a platform for EU Market Regulation....MAR, MIFID II et al..(2/3)
The first post (https://hortonworks.com/blog/european-banking-regulation-evolves-mar-mifid-ii-13/) in this three part series explored the evolution of capital markets regulation in the European financial markets over the last 15 years. We covered the important aspects of MAR (Market Abuse Regulation) and MiFid II. In this second blogpost, we will discuss the business and technology requirements that drive these implementations to an…
Capital Markets Regulation in the EU evolves with MAR, MiFiD II..(1/3)
Today’s European financial markets hardly resemble the ones from 15 years ago. The high speed of electronic trading, explosion in trading volumes, the diverse range of instruments classes & a proliferation of trading venues pose massive challenges. With all this complexity, market abuse patterns have also become egregious. Banks are now shelling out millions of euros in…
A Reference Architecture for The Open Banking Standard..
This is the final post in a series of four posts on the implications of the Open Banking Standard (OBS) in the UK. The first post introduced the specification (https://hortonworks.com/blog/banking-innovation-uk-open-bank-project/). The second post (https://hortonworks.com/blog/business-implications-uk-open-bank-standard/) examined the business implications of the specification. The third examined the strategic drivers for incumbents to drive change in their platforms to achieve OBS…
Predictions for the Global Payments Industry in 2017
The Global Payments Industry enters 2017.. It is not without reason that the payments industry lies at the heart of the FinTech boom. Across the globe, hundreds of startups are vying to provide digital services across the complex payments spectrum. Players ranging from Smartphone manufacturers, FinTechs,Banks and Retailers are all vying for market share. Added to this,…
The Four Strategic Business drivers in the Open Banking Age..
This is the third in a series of four posts on the Open Banking Standard (OBS) in the UK. This second post will briefly look at the strategic drivers for banks while proposing an architectural style or approach for incumbents to drive change in their platforms to achieve OBS Compliance. The final post will discuss a…
The Business and IT Implications of the UK Open Bank Standard…
The first post in this series (https://hortonworks.com/blog/banking-innovation-uk-open-bank-project/) discussed the emergence of the Open Bank Standard Working Group (OBWG) in the United Kingdom. The goal of this standard is to encourage the open and secure sharing of banking data among providers - via open APIs- thus providing more banking service choices for consumers. Open Banking Standard will spur…
How Data Science and Predictive Analytics transform AML Compliance in Banking & Payments..(2/2)
The first blog in this two part series (Deter Financial Crime by Creating an effective AML Program) described how Money Laundering (ML) activities employed by nefarious actors (e.g drug cartels, corrupt public figures & terrorist organizations) have gotten more sophisticated over the years. Global and Regional Banks are falling short of their compliance goals despite huge…
Digital Foundations – the importance of Customer Journey Mapping
The first post in this three part series on Digital Foundations @ http://www.vamsitalkstech.com/?p=2517 introduced the concept of Customer 360 or Single View of Customer (SVC). We discussed specific benefits from both a business & operational standpoint that are enabled by SVC. This second post in the series introduces the concept of a Customer Journey. The third & final…
Building a Modern Data Architecture with Enterprise Level Governance
This guest blog comes from Attivio, a certified Hortonworks Partner with the Governance Ready Badge, indicating that the Attivio Platform is recognized by Hortonworks as an application that integrates with Atlas APIs to access and create business taxonomical metadata like data lineage and tags. Here, Joe Lichtman, VP of Product Management at Attivio shares the…
Apache, Hadoop, Falcon, Atlas, Tez, Sqoop, Flume, Kafka, Pig, Hive, HBase, Accumulo, Storm, Solr, Spark, Ranger, Knox, Ambari, ZooKeeper, Oozie, Metron and the Hadoop elephant and Apache project logos are either registered trademarks or trademarks of the Apache Software Foundation in the United States or other countries.