eBook: Data Driven Telco

HOW DATA DRIVES THE FINANCING SHIFT IN TELCO Telecoms increasingly deploy data-driven decisioning tools to combat fierce competition and credit risk challenges.

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How Data Drives the Financing Shift in Telco TELECOMS INCREASINGLY DEPLOY DATA-DRIVEN DECISIONING TOOLS TO COMBAT FIERCE COMPETITION AND CREDIT RISK CHALLENGES. Today’s telecommunications industry faces cutthroat competition, underscored by disintegrating profit margins and high customer churn.

Once monopolistic telcos’ luxury phone services have now turned into commodities.

With subscriber loyalty largely hinging on data-delivery speed, quality of service and attractive financing offers, telcos are increasingly deploying data-driven strategies to improve their existing products and services, create new business revenues, secure customer retention and achieve growth.

HOW DID WE GET HERE? Global Advancements Through the evolution of the telecom industry—in tandem with the innovation of new modes of communication such as the smartphone and the internet—once monopolistic telcos’ luxury phone services have now turned into commodities.

The single phone line has faded into a distant memory, and rotary and touch tone telephones have been largely consigned to antique stores, sold on eBay, or rented as theatrical props. Indeed, they represent a type of technological tombstone, along with answering machines, manual and electric typewriters, transistor radios and cathode ray tube TVs—as reminders of how far global communications have advanced.

From Rotary to Commodity The global telecommunications sector has staged a substantial transformation from its late 19th century roots in American Bell Telephone Company, the construction of the single phone line, and the emergence of monopolistic telco giants.

Arguably, however, the most transformative events didn’t occur for over a hundred years, with the EU’s liberalization of the sector starting in 1988, as well as with former US President Bill Clinton’s signing of The Telecommunications Act of 1996.

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Against this historical backdrop, many telcos have ventured into consumer and enterprise financing, equipment leasing, IT services, and even solutions for auto insurers and retail banks.

With these policies, the European Commission and the US government each resolved to open the industry up to competition, which generally led to lower prices, as well as a heavy wave of small, independent wireless and internet-focused startups that were quickly absorbed by larger players.

Given the global changes in the regulatory landscape, as well as the steady growth in wireless mobility and internet usage, telcos began to diversify their operations away from traditional wirelines, which meant a host of new revenue streams—as well as increased exposure to credit risks.

The itemization on customers’ phone bills exploded from traditional fixed-line features such as local calls, international dialing, and call waiting to smartphone handset financing, domestic and overseas wireless calling, roaming charges, minutes packages and data plans.

With the onslaught of the smartphone and mobile digital voicemail, once-familiar items such as the “tangled-cord wall phone” and household answering machine began to fade into antiquity.

A BIGGER TELCO PIE Creating Room to Grow Against this historical backdrop, many telcos have ventured into consumer and enterprise financing, equipment leasing, IT services, and some now even offer solutions for auto insurers and retail banks, among other innovative business lines.

Telcos may offer financing for services such as fiber-to-the-home (FTTH) installation and technical equipment leasing—with many large operators providing enterprise solutions such as private cloud and managed hosting, IT and unified communications.

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With each digital movement a customer makes, useful data for credit risk managers is created.

Telcos are also increasingly employing data-driven decisioning tools to help refine existing products and services, as well as innovate new business segments, while limiting further organizational complexity.

UK-based Vodafone, for example, uses real-time driving and environmental data to enable auto insurers to better assess their risks and more accurately price their policies. The British telco has even embarked on machine-to-machine (M2M) solutions for retail banking because, it says, “data communication happens in real-time — without the need for human intervention”.

Using data-driven decisioning tools to address complex credit risk challenges Given the explosion of telcos’ product and service lines, telecommunications credit analysts no longer focus solely on whether a customer has sufficient creditworthiness to add international dialing or call waiting to their landline phone bill, but are now faced with enormous complexities that demand simple, real-time solutions.

The sector’s transition from single fixed phone lines to wireless and digital services has enabled many telcos to capture critical customer information in real-time on a daily basis, and operators are increasingly using this data in their decisioning models and analytics tools.

With each digital movement a customer makes, whether filling out an online loan application, or changing their employment status on LinkedIn, useful data for credit risk managers is created.

By analyzing data—which may be sourced from mobile phone bill payments, social media feeds, electronic transactions and location information— telcos are generally better equipped to achieve more efficient credit scoring, reduce churn, fine tune their advertising, improve upon their portfolios of products and services, limit capital spending, and even tap into hidden pools of new potential borrowers.

Credit scoring When the popularity of wireless mobility began to eclipse fixed-line services, and financing arrangements for the trendy handheld devices quickly mushroomed, the need for faster, and more adept credit scoring on a larger scale became increasingly critical—not only at the time of application but also over the life of the loan.

Credit managers know that when consumers become unemployed or focus on savings, they will abandon their telecom-related debt in favor of other payment priorities, such as their mortgage, auto loans or credit cards. Amid the financial crisis of 2008, for example, US incumbents Verizon and AT&T lost more than two million subscribers in the first quarter of that year alone.

Data and decisioning tools can help score and assess borrowers’ creditworthiness in real-time, identify opportunities to cross-sell and upsell products, and may even uncover prospective borrowers without credit histories, or so-called ‘credit invisibles’, to increase lending opportunities.

Source: J.D. Power Survey © 2018 PROVENIR ALL RIGHTS RESERVED

TELIA: A TELCO STORY Swedish telco Telia, for example, recently adopted Provenir’s credit risk analytics and decisioning platform, enabling the company to conduct straight-through processing for its FTTH loan applicants.

Among other benefits associated with reducing credit risk, Provenir’s platform enables Telia’s credit managers to integrate structured and unstructured data sources, and deliver decisions in seconds and even milliseconds.

Bart Baesens, professor of Big Data and analytics at the University of Leuven in Belgium, pointed out as volume, variety, and velocity of data continue to grow—along with a decline in issues regarding accuracy—new opportunities for building better credit scoring models also increase.

“Provenir empowers the Telia Finance team to create and change credit offerings independently, process customer applications in seconds, and easily integrate into multiple data sources for better quality decisioning.”

- FREDRIK NILSSON, TELIA FINANCE

He added: “By using alternative data sources, a better assessment of the credit risk can be made.”

DATA AND ANALYTICS USE CASES Alternative Data Expands the Population The US Consumer Financial Protection Bureau (CFPB) also believes the use of alternative data may help expand lending opportunities to consumers who lack sufficient history with a nationwide consumer reporting agency to obtain a credit score.

According to the CFPB, an estimated 26 million Americans are so-called ‘credit invisible’, and another 19 million consumers have a credit history that has gone stale, or is insufficient to produce a credit score under most scoring models.

The CFPB said for some consumers, “the use of unconventional sources of information, called ‘alternative data’, may be a way to gain access to credit to build a credit history.

“Alternative data draws from sources such as bill payments for mobile phones and rent, and electronic transactions such as deposits, withdrawals or transfers. This information could show a track record of meeting obligations that may not turn up in a credit history. As a result, some who now cannot get reasonably priced credit may see more access or lower borrowing costs.”

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As competition has grown fierce and products have become commoditized, customers have placed more demands on their carriers.

Better Data Means Less Churn To combat the danger customers will switch to a competitor—a process widely known as ‘churn’—industry experts generally agree telcos need to better understand their clients’ needs.

Telecom companies typically list churn as one of the highest—if not the highest— concerns on their list of credit risks, and since the cost of Source: Strategy Desk switching is low, buyer power has risen.

As competition has grown fierce and products have become commoditized, customers have placed more demands on their carriers for greater data-delivery speed and higher service quality. They also expect to experience the same level of service despite location or device used.

Churn may be mitigated through strategies such as financing arrangements, as well as by uncovering, targeting and better responding to customers’ behavioral usage patterns. Decisioning and analytics tools can also help maximize the efficiency of marketing campaigns and service quality, which in turn can further reduce customer loss.

Telcos that have developed more effective advertising tactics, who are better tuned-into current trends to determine future demand, and who offer individually-tailored products and financing options are most likely to keep their churn rate low.

“The better you understand your customers and their needs, the more you’ll be able to develop the right products, set the right stock levels, tailor your marketing, improve your customer service, identify trends and forecast demand, and ultimately outflank your competitors.”

-Verizon

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Data is worthless if the business can’t make use of its insights in time.

SERVICE QUALITY: VERIZON CASE STUDY During the third quarter of 2017, Verizon maintained the best postpaid phone churn rate among the four largest US wireless carriers—a healthy 0.75%.

According to analysts, AT&T and T-Mobile had rates of nearly 0.85% and about 1.2% over the same period, respectively, while Sprint posted a little more than 1.5% in its fiscal second quarter.

Through data-driven decisioning and analytics tools, Verizon believes it has improved customer retention in large part by offering better service quality.

The company said: “Data is worthless if the business can’t make use of its insights in time.

“The goal is to create an empowered, real-time business where employees can connect to cloud-based dashboards or analytics tools— even when mobile—to get access to the insight or alerts they need.”

Verizon boasts it “generates a lot of data” through the management of its nearly 5,000 networks and more than 340,000 security, network and hosting devices in over 150 countries.

The US’s largest telco said it uses that data to “improve the performance, reliability and security” of its global infrastructure and to shape its investment plans to meet its customers’ capacity needs.

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Capital Spending According to a recent study conducted by Jacques Bughin, a director of the McKinsey Global Institute, nearly half of the 273 global telecommunications executives surveyed— representing about a quarter of the industry’s revenues—were considering investing in data used in decisioning and analytics tools, while 30% had already made them.

50%

30%

Considering

Already use

Use of data in decisioning and analytics

Predicted network usage Bughin found that one of the companies had strategically employed analytics models to predict when network usage from video streaming were heaviest. It then managed to relieve the congestion, and reduced its planned capital expenditures by 15%.

15% capital expenditures

Another company employed a machine-learning model that combined sociodemographic data, information from customer touchpoints such as call centers and social media, as well as network usage data.

Based on the resulting reports, Bughin noted the firm was able to identify, in real-time, the customers most likely to defect or have trouble paying their bills, as well as to cut churn by 3%, and to improve payment recovery by 35%.

 Use of customer touchpoints

3% churn

35% payment recovery

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A Sound Connection Data-driven decisioning and analytics tools provide simple, real-time solutions for the telecom sector’s complex credit risk concerns.

While credit risk managers in the telecommunications sector have faced increasingly complex challenges over the course of the industry’s evolution, today’s data-driven decisioning and analytics tools have helped provide simple solutions with dramatic upsides.

Among other benefits, telcos can now achieve more efficient, real-time credit scoring, lower churn, and even uncover large populations of potential new lending opportunities. Moreover, as fierce competition and commoditization of the industry has stifled growth, data-driven decisioning and analytics can help telcos construct entirely new sources of revenue—especially as they branch out into consumer and business financing and other financial services solutions.

As the telecommunications sector expands further, with billions of people, businesses and devices eagerly awaiting connectivity, the need for companies to have the right data, at the right time, and in the right place will become even more critical.

Data-driven decisioning and analytics tools enable operators to have an exponentially greater chance of outdoing their rivals by homing in on the right products, such as tailored financing options, while engaging more effectively with their customers—clearly creating very sound and lucrative connections.

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