Global Payments Industry in 2018 – Breaking Through to New Horizons..

The Global Payments Industry in 2018…

In 2017, the Payments industry largely kept its promise of leading financial services – http://www.vamsitalkstech.com/?p=3425. This evidenced in two important categories – consumer adoption and technology innovation. From a numbers standpoint, this has been accompanied by healthy growth in both the volumes and the count of payments. Mckinsey estimates that (as of 2017) the payments industry now makes up 34% of the global banking industry.[1] The coming year will find that three key forces – Digital technology, Consumer demands & Regulatory change – will continue to drive growth in the industry. With that in mind, let us consider the top industry themes and trends for 2018.

Image Credit – Pmts.com

Background and my predictions for 2017..

Payment Providers – How Big Data Analytics Provides New Opportunities in 2017

Trend #1 Digital Payments volumes continue to surge in 2018

Consumer payment volumes are now beginning to overtake business payments. McKinsey forecasts that from a volumes standpoint, by 2021, global payment volumes will surpass 2.2 trillion US dollars [1] –  a massive increase from just 450 billion US dollars in 2017.  The key drivers for this increase are the number of consumers rapidly coming online in countries such as China and India (with the latter alone contributing a base of 500 million internet subscribers) in 2017.  In India, the demonetization campaign conducted a year ago has resulted in a surge of digital transactions.

Banks have not been sitting still in the face of the instant payment paradigm. Across the globe, Banks have been nudging more consumers to begin using digital payments as a way of providing speed while managing both cost & risk – often at the expense of cheque payments. In the UK, Fast Payments Service which was launched in 2008, processing the five billionth payment in 2015.

The Faster Payments Scheme – UK

Currently, four types of payments can be processed through Faster Payments – immediate payments, forward dated payments, standing payment orders and Direct Corporate Access (single business payments with upto 250k pounds per transaction). Nearly every large and medium-sized Bank in the United Kingdon supports Faster Payments including the likes of Barclays and HSBC.

In response to all this rapid change, players across the payments spectrum and in adjacent verticals such as Retail & Telco will need to begin enhancing their mobile apps & in-store payments. Established card schemes such as Mastercard and Visa have begun rolling out API driven interfaces.

Trend #2 The Internet Leaders take increasing share of the consumer and corporate payments…

We are also witnessing a whole range of nimble competitors such as FinTechs and other financial institutions jockeying to sell both closed and open loop payments products to customers.

The likes of Apple, Amazon, Facebook, Alibaba, and Google are originating payments from not just their online portals and mobile apps but also from sensors, personal assistants (Echo, Siri etc) and voice-driven interfaces. These players will also drive capabilities into a range of payments related usecases – from Single View of Customer to Data Monetization to AML/Risk & Fraud detection.

Euromonitor contends that the leading mobile-centric nation in the world is China. In 2015, Chinese consumers made more purchases through mobile phones than using traditional computers. As of 2016, this number had increased to 2/3rd of all online purchases. Chinese players led by AliPay and WeChat are increasingly looking to replicate their domestic success abroad. This is being helped by global travel by Chinese consumers who are expected to take 225 million international trips in 2030, at a compound annual growth rate (CAGR) of 7.3% over 2016-2030. [3]

Trend #3 Regulators push for  Open Data Sharing & Innovation…

With Payment Systems Directive 2 (PSD2), the European Parliament has adopted the legal foundation for the creation of an EU-wide single payments area (SEPA).  While the goal of the PSD is to establish a set of modern, digital industry rules for all payment services in the European Union; it has significant ramifications for the financial services industry as it will surely current business models & foster new areas of competition. The key message from a regulatory standpoint is that consumer data can be opened up to other players in the payment value chain. This will lead to a clamor by players to own more of the customer’s data with a view to selling business services (e.g. accurate credit scoring, access to mortgage & other consumer loans and mutual funds etc) on that information.

Why the PSD2 will Spark Digital Innovation in European Banking and Payments….

Trend #4 Customer Experience drives volumes growth…

Customers are demanding smarter UX capabilities and intuitive cross-channel interfaces. Technology built around ensuring that payment providers can create a single view of a Cardholder across multiple accounts & channels of usage will result in more ecross-sellross sell/upsell and better customer segmentation.

For instance, the 360 degree view is a snapshot of the below types of data –

  • Customer’s Demographic information – Name, Address, Age etc
  • Length of the Customer-Enterprise relationship
  • Products and Services purchased overall
  • Preferred Channel & time of Contact
  • Marketing Campaigns the customer has responded to
  • Major Milestones in the Customers relationship
  • Ongoing activity – Open Orders, Deposits, Shipments, Customer Cases etc
  • Ongoing Customer Lifetime Value (CLV) Metrics and the Category of customer (Gold, Silver, Bronze etc)
  • Any Risk factors – Likelihood of Churn, Customer Mood Alert, Ongoing issues etc
  • Next Best Action for Customer

Payment providers have been sitting on petabytes of customer data and have only now begun 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. Web apps, 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.

Trend #5 Cross-Border Payments offer a lot of business growth but Compliance and Security remain huge challenges…

While Cross-border transactions still generate substantially higher margins than domestic. This blog has cataloged a range of Risk/Fraud and KYC/Compliance usecases in the cards industry. We increasingly find that banks across the spectrum are putting in strong capabilities around real-time fraud detection, risk management and AML (Anti Money Laundering).

Big Data Counters Payment Card Fraud (1/3)…

Advanced analytics and business reporting are being used to target money launderers and fraudsters. These projects, however, have large and complex outlays and needs advanced capabilities around Big Data & Artificial Intelligence.

Conclusion…

The Payments industry is the most dynamic portion of Global Banking. Players will need a lot of creativity to connect the twin worlds of slow-moving finance and fast-moving technology. In 2018, the pressure will be on players to deliver higher rates of adoption, margins leveraging technology driven innovation.

References…

[1] McKinsey – Payments Insights https://www.mckinsey.com/industries/financial-services/our-insights/global-payments-2017-amid-rapid-change-an-upward-trajectory

[2] Faster Payments UK –

http://www.fasterpayments.org.uk/about-us/how-faster-payments-works

[3] Forbes – “Three Payment Trends that will change how we pay in 2018”

https://www.forbes.com/sites/michelleevans1/2017/10/27/three-payment-trends-that-will-change-how-we-pay-in-2018/#7aca91b46c2c

What Banks, Retailers & Payment Providers Should Do About Exploding Online Fraud in 2017..

Despite the introduction of new security measures such as EMV chip technology, 2016 saw the highest number of victims of identity fraud , according to a new report from Javelin Strategy & Research and identity-theft-protection firm LifeLock Inc[1]. 

Image Credit: Wall Street Journal

Background

The Global Credit Card industry has industry players facing new business pressures in strategic areas. Chief among these business shifts are burgeoning online transaction volumes, increased regulatory pressures (e.g. PSD2 in the European Union) and disruptive competition from FinTechs.

As discussed in various posts in this blog in 2016 – Consumers, Banks, Law Enforcement, Payment Processors, Merchants and Private Label Card Issuers are faced with yet another critical & mounting business challenge – payment card fraud. Payment card fraud continued to expand at a massive clip in 2016 – despite the introduction of security measures such as EMV Chip cards, multi-factor authentication, secure point of sale terminals etc. As the accessibility and modes of usage of credit, debit and other payment cards burgeons and transaction volumes increase across the globe, Banks are losing tens of millions of dollars on an annual basis to fraudsters.

Regular readers of this blog will recollect that we spent a lot of time last year discussing Credit Card and Fraud in some depth. I have reproduced some of these posts below for background reading.

Big Data Counters Payment Card Fraud (1/3)…

Hadoop counters Credit Card Fraud..(2/3)

It’s time for a 2017 update on this issue.

Increasing Online Payments means rising Fraud

The growing popularity of alternative payment modes like Mobile Wallets (e.g Apple Pay, Chase and Android Pay) are driving increased payment volumes across both open loop and closed loop payments. Couple this with in-app payments (e.g Uber) as well as Banking providers Digital Wallets  only driving increased mobile payments. Retailers like Walmart, Nordstrom and Tesco have been offering more convenient in-store payments.

This relentless & secular trend towards online payments is being clearly seen in all forms of consumer and merchant payments across the globe. This trend will only continue to accelerate in 2017 as smartphone manufacturers continue to produce devices that have more onscreen real estate. This will drive more mobile commerce. With IoT technology taking center stage, the day is not long off when connected devices (e.g. wearables) make their own payments.

However, with convenience of online payments confers anonymity which increases the risk of fraud. Most existing fraud platforms were designed for a previous era – of point of sales payments – with their focus on magnetic stripes, chips and EMV technology. Online payments thus present various challenges that Banks and Merchants did not have to deal with on such a large scale.

According to the WSJ [1] more consumers (15.4 million in the US) became victims of identity fraud in 2016 than at any point in more than a decade. Despite new security protections implemented by the industry in the form of EMV – about $16 billion was lost to fraudulent purchases with online accounting for a 15% rise in cases.

Fraud is a pernicious problem which in a lot of cases leads to a much worse crime- identity theft. The U.S. Department of Justice (DOJ) terms Identity theft as “one of the most insidious forms of white collar crime”. Identity theft typically results in multiple instances of fraud, which exact a heavy toll on consumers, merchants, banks and the overall economy. Let us look at some specific recommendations for Payment providers to consider.


Sadly, the much hyped “Chip on your cards” are useless in countering online fraud..

Javelin Research noted in their study that the vast majority of identity theft fraud was linked to credit cards.[2]

Most credit card holders in the USA will remember 2016 as the year when electronic chip technology became ubiquitous and required at the majority of retail establishments. The media buzz around chips was that this would curtail fraudster activity. However, this has been accompanied by a large in online theft. Card-not-present (CNP) fraud, which is when a thief buys something online or by phone, rose 40%.[2]

So did Account takeover fraud, where thieves access ongoing customer accounts and change the contact details/security information. These increased 61% compared to 2015, and totaled around 1.4 million incidents.[2]

It is very clear that the bulk of fraud happens over online transactions. It is here that the Banks must focus now. And online is a technology game.

How should Banks, Retailers & Payment Providers Respond..

Online card fraud revolves around the unauthorized stealing of an individual’s financial data. Fraudsters are engaging in a range of complex behaviors such as counterfeiting cards, committing mail fraud to open unauthorized accounts, online Card Not Present (CNP) transactions etc. Fraud patterns are quickly copied and reproduced across diverse geographies.

Let us consider five key areas where industry players need to make investments.


#1 Augment traditional Fraud Detection Systems & Architectures  with Big Data capabilities

Traditional Fraud detection systems have been built leveraging expert systems or rules engines. These expert systems are highly mature as they take into account the domain experience, intuition of fraud analysts. Fraud patterns called business rules are created in the form of IF..THEN.. format and made available in these systems. These rules describe a range of well understood patterns as shown below.

If Consumer Credit = yes And Transaction amount ≤ 1000 And Card present = yes Then Fraud = no

Typically hundreds of such rules are applied in realtime to incoming transactions.

Expert systems have been built for the era of physical card usage and can thus only reason on a limited number of data attributes. In the online world they are focused on looking for factors such as known bad IP addresses or unusual login times based on Business Rules and Events.However, the scammers have also learnt to stay ahead of the scammed and are leveraging computing advances to come up with ever new ways of cheating the banks. Big Data can help transform the detection process by enriching the data available to the fraud process including traditional customer data, transaction data, third party fraud data, social data and location based data.

Big Data also provides capabilities to tackle the most complex types of fraud and to learn from fraud data & patterns to be able to stay ahead of criminal networks. It is recommended that fraud systems be built using a layering paradigm. E.g. Provide multiple levels of detection capabilities starting with a) configuring business rules (that describe a fraud pattern) as well as b) dynamic capabilities based on machine learning models (typically thought of as being more predictive). Fraud systems also need to adapt Big Data frameworks like Spark, Storm etc to move to a real time mode. Frameworks like Spark make it extremely intuitive to implement advanced risk scoring based on user account behavior, suspicious behavior etc.

Advanced fraud detection systems augment the Big Data approach with building models of customer behavior at the macro level. Then they would use these models to detect anomalous transactions and flag them as potentially being fraudulent.


#2 Create Dynamic Single View of Cardholders

The Single View provide comprehensive business advantages as captured here – http://www.vamsitalkstech.com/?p=2517.  The SVC can help with the ability to view a customer as a single entity (or Customer 360) across all those channels & to be able to profile those.Ability to segment those customers into populations based on their behavior patterns. This will vastly help improve anomaly detection capabilities while also helping reduce the false positive problem.

#3 Adopt Graph Data processing capabilities

Fraudsters are engaging in a range of complex behaviors such as counterfeiting cards, committing mail fraud to open unauthorized accounts, online Card Not Present (CNP) transactions etc. Fraud patterns are quickly copied and reproduced across diverse geographies as fraudsters operate in concert. Thus, fraud displays a strong social element which leads to a higher risk of repetitive fraud across geographies.

The ability to demonstrate Social Network identity links with customer profiles to establish synthetic (or fraudulent) customer profiles and to reduce false identities is a key capability to possess. As fraud detection algorithms constantly analyze thousands of data points, it is important to perform Network based analysis understand if an account or IP Address or fraud pattern is occurring across different and seemingly unrelated actors.  The ability to search for the same Telephone numbers, Email accounts, social network profiles etc – in addition to machine data such as similar IP Addresses, device signatures and addresses can be used to establish these connections. Thus, graph and network analysis lends a different dimension to detection.


#4 Personalize Fraud Detection by Adopting Machine Learning

Incorporating as many sources of data (both deep and wide) into the decisioning process helps majorly in analyzing fraud. This data includes not just the existing – customer databases, data on historical spending patterns etc but also credit reports, social media data and other datasets (e.g Government watch-lists of criminal activity).

Some of these non-traditional sources are depicted below –

  • Geolocation Data
  • Purchase Channel Data
  • Website clickstream data
  • POS Sensor, Camera, ATM data
  • Social Media Data
  • Customer Complaint Data

Payment Providers assess the risk score of transactions in realtime depending upon these 100s of such attributes. Big Data enables these reasoning on more detailed and granular attributes. Advanced statistical techniques are used to incorporate behavioral (e.g. transaction is out of normal behavior for a consumers buying patterns), temporal and spatial techniques. The models often weigh attributes differently from one another thus separating the vast majority of good transactions from the small percentage of fraudulent ones.

We discussed the fact that fraud happens at every stage of the process – account opening, customer on-boarding, account validation & cross verification, card usage & chargebacks etc. It is imperative that fraud models be created and leveraged across the entire business workflow.


#5 Automate the Fraud Monitoring, Detection Lifecycle

Business Process Management (BPM) is a more prosaic and mature field compared to Big Data and Predictive Analytics. Pockets of BPM implementations exist at every large Bank in customer facing areas such as issuance, on-boarding, reporting, compliance etc. However, the ability to design, deploy automated processes is critical across the Cards fraud lifecycle. In areas like dispute management, false positive case resolution etc depend upon robust Case Management capability – which a good BPM platform or tool can provide.

Improvements can be noticed in agent productivity, number of cases handled per Agent and improved customer satisfaction. Errors and lags due to issues in human driven manual processes come down. On the front end, providing customers with handy mobile apps to instantaneously report suspicious transactions as well as tying those with automated handling can drastically improve fraud detection thus saving tens of millions of dollars. Major improvements can also seen in compliance, dispute resolution and cross border customer service.

Conclusion  

Online fraud keeps going up year after year, thus enterprises will remain vigilant especially banks and retailers. Online retail sales are expected to total nearly $28 trillion in 2020 [2] and it is a given that fraudsters will invent new techniques to steal customer data. Effective Fraud prevention has become an essential part of the customer experience.

References

[1] WSJ – Credit Card Fraud Keeps Rising Despite New Security Chips – “https://www.wsj.com/articles/credit-card-fraud-keeps-rising-despite-new-security-chipsstudy-1485954000

[2] Forbes – That Chip on Your Credit Card Isn’t Stopping Fraud After All – “http://fortune.com/2017/02/01/credit-card-chips-fraud/ “

Payment Providers – How Big Data Analytics Provides New Opportunities in 2017

                                                         Image Credit – JDL Group

Payments Industry in 2017..

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.

My Last Post for the Year – Predictions for the Global Payments Industry in 2017

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 –

  1. 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).
  2. 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.

    http://www.vamsitalkstech.com/?p=1098

  3. 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.
  4. Detect Payments Money Laundering (AML)
    A range of Big Data techniques are being deployed  to detect money laundering disguised as legitimate payments.

    http://www.vamsitalkstech.com/?p=2559

  5. 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.

    http://www.vamsitalkstech.com/?p=2517

  6. Merchant Analytics 
    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.
  7. 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
  8. 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

Conclusion..

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.