June 29, 2015
I am sure you would have already heard about Falcon 9 that had experienced a problem shortly before first stage shutdown yesterday (Yes, it’s rocket science!). Apparently, the only way to know what happened there is, as Elon Musk describes in a tweet, Cause still unknown after several thousand engineering-hours of review. Now parsing data with a hex editor to recover final milliseconds.
Think about it for a moment. Payment businesses today are equally complex; the number of parameters to manage have grown so much in numbers that you need to really manage the data tsunami (Did I mention fraud and risk?). No longer can human minds and simple dashboards keep your business up and running, not to talk about disasters. Increasingly data analytics is connecting, calibrating and creating new opportunities not only for realizing the full potential of the data wave, but also for unleashing new experiences that have not yet been articulated.
Some easy examples here are personalized digital offers, dynamic pricing for goods and services, risk scoring for authentication, etc. The more interesting examples will involve synthesis of multiple, disparate data sets from multiple industries—both real time and historical—mashed up to generate a nuanced understanding of consumer behavior and an unprecedented ability to generate experiences that delight.
Analytics allows organizations to identify patterns and categorize cardholders through a multitude of attributes and variables. Mobile technologies have greatly enhanced this data collection by giving organizations valuable information about individuals’ transactions, preferences and online interactions. For example, data-driven insights generated by analytics solutions help capture as-is costs which can further be compared with bank and industry benchmarks to help drive a cost management program. Other major applications include reduction in payments fraud occurrences and building a body of knowledge from customer data points in order to structure value-added services and bring opportunities for cross selling.
Here are some notable organizations (of course, there are more) in the payments industry generating insights through their analytics solutions:
The company focuses on next-generation fraud prevention software that protects electronic transactions. It credits its rapid success to its early focus on big-data analytics applications. Feedzai leverages modern in-memory data processing techniques that are different than older fraud prevention software solutions; its software detects 3 times more fraud at the same level of false positives. This means that Feedzai customers spend 4.5 times less on labor costs to review false positives, a key efficiency metric for fraud and risk departments. Furthermore, in contrast to the traditional approach of updating analytics models every 6 months, Feedzai’s unique machine learning technology—combined with its sub-second analytics engine—allows companies to block new fraud efforts on the first attempt.
MyBank by Alibaba
China’s e-commerce giant Alibaba has launched an Internet bank called MyBank which will offer loans to small and medium-sized enterprises (SMEs). They are targeting the market that is not served by traditional financial institutions. Unlike its conventional competitors, the online bank neither deals with cash nor with big clients but instead focuses on the bottom 80% which is the small, mid and micro-sized businesses. MyBank’s target customers lie in rural China. MyBank will not be taking collateral from debtors. Instead, it will look at the financial data that customers and small businesses have accumulated on Alipay, Ant’s third-party payment service used by vendors and buyers on Taobao and Tmall to purchase items. Data-driven loan provision is the next big thing, and that is exactly what MyBank will be doing.
The company supplies data analytics, marketing and loyalty services that are built off credit card swipe transactions. This gives merchants valuable tools to break down sales trends, better identify their best customers and reach out to loyal or lapsed customers through email marketing and retention tools. Swipely provides spending data on individual users, so a merchant can see what its top users are doing in real time and cater to their needs. Swipely also provides a CRM tool complete with customer profiles for merchants.
Back in November 2013, BillGuard made a prominent upgrade to its platform bringing in analytics capabilities. BillGuard utilizes big data analytics in conjunction with reviews/insights from thousands of users to identify harmful or potentially fraudulent transactions in a user’s bank and credit card financial statements. It is basically an algorithmic, crowd-sourced approach to protecting and saving the user some money. The Spend Analytics feature of the platform offers personal finance management tools that will provide a wide range of analytics, enabling users to compare their current spending to earlier months. BillGuard also performs location-based analytics to detect fraudulent transactions. When users opt-in for the service, BillGuard starts keeping track of locations where the user’s card is being used on a regular basis. It can use this data to match with the location of future transactions and alert users when a suspicious change occurs.
Wealthfront is one of the fastest-growing automated investment services with over $1.2 billion in assets under management. The company leverages its horizontally scalable, modular and pipelined data platform. Data is loaded from all origin sources: event ingestion, internal operational systems, external partner systems, SaaS APIs and infrastructure service providers. Wealthfront uses Hadoop for offline batch processing via Cascading. A Cascading job rolls up information into daily metrics for each account, tracking things like account balance and daily rate of return. For each area of business, Weatherfront has built dashboards that can be used to track things like new-feature adoption, the business at-large and operational performance.
The company powers an online portfolio manager that looks at your existing investment portfolio and uses data analytics to recommend how to best invest your 401K savings. Jemstep’s technology compares data about every mutual fund/ETF with data about every other mutual fund/ETF to provide up-to-date market data. It combines this information with investor profiles, including financial goals, current situation and investment preferences to make personalized recommendations for each investor.
By using big data analytics, SigFig provides a single view across multiple investment accounts and an in-depth analysis of those investments on a single dashboard. SigFig offers a portfolio tracker that provides real-time stock, bond and mutual fund information, as well as detailed charts and analytics to dig down and review performance and investment allocation. Using the analytics driven dashboard, users can access asset allocation, geographic allocation, dividends or risk to see which holdings are impacting the makeup of their investment portfolio.
In July 2014, Oversight had launched its Insights On-Demand for Procure-to-Pay cloud-based web application for detection of fraud in payment transactions. Structured in a software-as-a-service format, Insights reviews invoice and payment data stored in enterprise systems like Concur, Oracle, SAP and Chrome River. Customers receive visualized reports highlighting duplicate payments, ghost vendors and repeat expense reports. Oversight’s Insights On-Demand delivers analysis that leads to better business decisions. The web-based application examines 100% of company transactions by combining complex, predictive analytics with transaction analysis. Insights On-Demand’s best practice technology makes it easier than ever for customers to uncover possible misuse, fraud and corruption, and compliance violations.
This social lending startup leverages social data analytics to make loans cost less. The company’s concept is to give consumers a way to receive lower interest rates on loans by having other family members and friends vouch for them. Vouch plots the user’s network and social ties in order to deduce creditworthiness within the loan application. The startup looks at a number of explicit and implicit factors to determine interest rates to be offered to a borrower. Factors considered are social data, including things like response rates for vouch requests, the overall size of someone’s network, how many vouchers took the extra step to sponsor a loan and much more.
Fundbox fills the void left by banks and credit companies, and fixes the small-business economy using data science. Fundbox leverages newly available cloud services and deep data science to deliver financial services. By processing data based on tens of thousands of invoices daily, they offer small business owners the ability to fix their cash flow by advancing payments for unpaid invoices. Fundbox taps into numerous sources of data, including the user’s financial health, the demographics of their customers and even the seasonal nature of some specific businesses. Leveraging cutting edge data science, behavioral analytics and finance theory, Fundbox automatically analyzes the user’s business and invoices not only from a financial perspective, but also from behavioral and psychological perspectives.
The card-focused banking group pioneered the use of analytics to understand consumer spending patterns to come up with products and offers best suited to the requirements of various consumer groups. Capital One runs algorithms on millions of customer card transactions to determine the most common co-occurrences—that is where customers who spend money at one retailer are most likely to also spend money elsewhere. Capital One had acquired Bundle to leverage its proprietary analytics technology powered by data from more than 20 million Visa and MasterCard branded cards.
American Express Business Insights offers a unique view of customer behavior, market activity and industry trends. Based on transaction data from a network of approximately 90 million cards in circulation in over 125 countries, Amex gathers a wealth of timely information that sheds light on the actual aggregate spending behaviors of consumers and businesses and enables the ability to see trends as they’re developing. Through advanced modeling and analytics, Amex transforms raw data into a suite of powerful business intelligence offerings. The analytics solutions help increase engagement with current customers, find and acquire new ones, benchmark against the competition, improve business planning and more. From customized engagements to web-based reporting, Amex’s analytics solutions can provide actionable insights that can lead to improved business performance.
Bank of America
Back in July 2013, the bank had launched Dashboard Analytics, a new module on the Global Reporting and Account Management system which is available to commercial card clients in more than 70 countries and in 21 languages. The new dashboard tool helps senior level executives and treasury departments make better educated decisions to improve their working capital, negotiate better terms with key suppliers and facilitate compliance with company policy. Dashboard Analytics harnesses the power of big data to translate millions of transactions from across the globe into a sleek and actionable dashboard view. Dashboard Analytics promises executives the ability to quickly pinpoint negative trends or non-adherence to company policy. The invaluable intelligence—that has a variety of detailed data—can help companies save on expenses and ultimately improve their working capital.
First Data’s analytics solutions enable evaluation of data from multiple sources to drive decision-making across the customer lifecycle, from customer acquisition to retention to collections. Some major offerings include:
First Data has also been building out the Insightics analytics service in the cloud that aggregates both internal data collected by First Data and external data sources. The latest external data source that First Data has included comes from Factual, provider of a location-based service that helps organizations deliver mobile experiences based on the physical location of a mobile computing device.
The company has directed its efforts to building analytics solutions that unlock the business value in very large and unstructured data sets. The analytics and decision management software company has introduced innovations to support analysts working with big data, and also to extend access to its capabilities to a broader community. FICO is perhaps best known for the FICO Score—a standard measure of consumer credit risk in the US—and for solutions that help customers manage credit accounts, identify and minimize the impact of fraud, and customize consumer offers. FICO also works with many of the leading insurers, retailers, pharmaceutical businesses and government agencies. Its offerings fall into three broad categories: decision management tools which include software for business rules management, model development and optimization; decision management applications or integrated systems that apply analytics, decision logic and industry expertise to strategy and execution across the customer lifecycle; and standard scores and models to manage risk, identify opportunities and help clients forecast customer behavior.
In March 2014, the company had announced Elevate Data Services, a comprehensive Business Intelligence solution designed specifically for online payments and chargebacks. With Elevate, GlobalCollect merchants are able to apply advanced data analytics and visualization to their unstructured payments data, transforming it into a rich source of strategic insights that help optimize their online business and drive sales. Elevate combines GlobalCollect’s payments knowledge with strategic guidance from leading international e-commerce companies and the industry-leading data visualization platform by Tableau, to create a payments intelligence solution consisting of highly interactive management dashboards that answer real business questions.
BNY Mellon’s Payment Analytics
Investments and analytics service provider BNY Mellon has expanded its services to provide payment analysis for treasury services clients. The Payments Analytics service is designed for institutional clients with a high usage of wire transfers.
Payment Analytics provides real-time updates on day-to-day straight-through processing (STP) rates. It helps in meeting the demands of vendors and clients for immediate and accurate payments. The service aims to provide information regarding wire payment trends to quickly see the status of the payments, anticipate the availability of funds and effectively manage the current cash position.
BNY Mellon’s Payment Analytics is also designed to provide graphical representations related to straight-through processing rates, inquiry reporting and historical trend data for an in-depth view of how wire payments are moving through the system and to find out where there may be delays. Payment Analytics can provide reports on payments by account, time intervals, beneficiaries and payment channels.
MasterCard Acquisitions in This Space
Cloud-based analytics and big data company, Applied Predictive Technologies (APT), was acquired by MasterCard for $600 million. MasterCard plans to utilize APT’s Test & Learn platform and other services in combination with its own analytics expertise to provide customers with enhanced decision-making capabilities. Previously in this space, MasterCard had acquired 5one Marketing Limited, a global consulting firm. 5one specializes in providing analysis and software services for retail management and business growth. MasterCard integrated 5one into its MasterCard Advisors service, which combines analytics and payments expertise to enable its customers to make informed insights and decisions.
There are more companies than I could possibly list in this article when it comes to payments analytics. The LTP team had previously estimated the creation of 40,000+ new jobs in payments and commerce in the US. Not surprisingly, many of these opportunities are in technology and data sciences. As the large FIs continue to expand and improve their tech capabilities and the tech & mobile players begin building at scale to support payments & commerce, product and development skills will be in increasing demand.