Why Telcos Can’t Afford to Think Like Banks –
And Why That’s Their Advantage
Most telcos are barely growing faster than inflation. They’re trapped in saturated markets where customers churn over minor price differences or the promise of a newer handset. The conventional wisdom says they should adopt the same risk-averse, compliance-heavy decision-making frameworks that banks use.
But banks and telcos operate in completely different contexts. Unlike banks, telcos are technology companies that built the networks powering global communication. Their teams already understand AI, real-time systems, and technical complexity. The operators winning today—Verizon in the US, Deutsche Telekom in Germany, Etisalat in the Middle East—compete on coverage and reliability, not price. They’ve moved from “cheapest unlimited data plan” to “best customer experience,” and that requires intelligent, real-time decisioning about which customers to serve, how to serve them, and what to offer.
The advantage belongs to telcos willing to think like telcos, not like banks.
Not All Churn Is Bad (And Treating It That Way Destroys Margins)
Most operators treat customer retention as a binary success metric, measuring every lost customer as failure. This approach ignores a more sophisticated reality: some customers should leave.
Consider the different types of churn from the operator’s perspective. Voluntary churn happens when customers leave for better deals, which most operators want to prevent. Involuntary churn occurs when operators cut off customers who don’t pay. Decisioning becomes critical here by identifying at-risk customers before they owe money, potentially downsizing their package to keep them profitable rather than losing them entirely.
Sophisticated operators diverge from the pack with planned churn, deliberately choosing not to intervene to retain low-value or negative-margin accounts. Others embrace constructive churn, letting high-cost customers leave because they complain constantly, demand credits, or pay late. Losing them actually improves portfolio profitability.
The real opportunity is profit-optimizing your churn: using data and models to selectively target retention offers to customers you genuinely want—high customer lifetime value, low cost to serve—while letting low or negative CLV customers churn without incentives. This is decisioning at its most strategic, preventing the wrong churn rather than all churn.
A related opportunity exists in serving customers other operators reject. Better creditworthiness assessment enables profitable service to “riskier” customers. Someone might want the latest iPhone, but traditional credit checks suggest they can’t afford it. Instead of rejecting them outright, offer an older model or lower-spec Android device. You’ve still acquired a customer and you’re still generating revenue.
Alternative data sources for decisioning beyond financial history – that telcos already have – reveal signals traditional scoring misses: device usage patterns, top-up behavior, payment consistency on other services. This opens entirely new market segments competitors may be ignoring.
The Build Trap: When Time-to-Value Beats “Not Invented Here”
Telcos are technology companies that built their networks. Their teams include engineers and technologists who’ve already experimented with AI and machine learning, creating both opportunity and risk.
- The opportunity:Telcos are more AI-literate and risk-tolerant than banks. They understand technical complexity, they are comfortable with rapid iteration, and they want to see under the hood of any technology they are evaluating.
- The risk: They often believe they can build decisioning solutions themselves, which stretches delivery cycles as internal IT teams advocate for internally built projects. But business strategies in telecom change constantly based on competitor moves. By the time an 18-month internal build is complete, the strategic context has shifted.
The calculation comes down to time-to-value and core competency. Telcos should focus on what they do best: creating reliable networks for calls and data transmission. Decisioning expertise should come from specialists who do nothing else, because the ability to adapt quickly, test new approaches, and optimize in real-time determines who wins. When your competitor launches a new retention offer, you need to respond in days or hours, not quarters.
When Scale Makes Small Problems Catastrophic
At 50 million customers, a 1% false positive rate means 500,000 angry customers, which means everything must be automated, explainable, and reversible. But even for a 5 million customer telco, 50,000 angry customers is 1,000 issues per week!
The complexity is twofold. First, system complexity. Very few large telcos are new. Most are legacy operators that have existed for 20-30 years with multiple systems in each domain. They might have separate billing systems for mobile, fixed line, and broadband, or multiple systems from merger and acquisition history. Verizon is the result of 30+ company mergers, each bringing different systems, different customer data structures, and different business rules.
Second, product complexity. Those mergers mean customers are on thousands of different plans with different rates for calls and data, different included features. Most telcos won’t force customers to change plans, but they sometimes have to in order to shut down old systems and networks. This triggers churn, which intelligent decisioning can mitigate by identifying the right migration timing and offers for each customer.
Also at scale, governance becomes non-negotiable: Who approved this model? When was it last validated? What are the rollback procedures? Infrastructure costs don’t scale linearly, and instead of 5 stakeholders, you’re managing alignment across 20+ groups.
The Technical Conversation That Banks Never Have
When telcos evaluate platforms, their questions differ fundamentally from banks.
Banks ask about accuracy, compliance frameworks, and regulatory alignment. Telcos ask about integrations to telco-specific systems, particularly billing data, because access to usage patterns enables better real-time personalization of decisions and offers.
The technical depth telcos demand actually works in favor of platforms with solid architecture. When you can demonstrate real-time performance, clean integrations, and robust data handling, it builds credibility faster than any deck.
But that technical literacy creates a trap. Operations teams want to understand how the technology works, while C-suite executives want to know what it delivers. The right approach anchors to business goals first: Which KPIs actually matter? Then quantify the impact and frame everything in terms of ROI and outcomes. Senior leaders need to hear financial impact, implementation timelines, and risk reduction.
What Separates Winners from Survivors
Three years from now, the winning telcos will have moved from connectivity providers to intelligent service platforms. They’ll have embedded AI decisioning across the entire customer lifecycle and made those decisions in real-time with hyper-personalization.
More importantly, they’ll have focused on doing right by the customer. Their actions will be customer centric, not operator centric. If a customer has an issue, winning operators will focus everything on fixing it before trying to upsell. Once the issue is resolved, they’ve earned the right to offer additional services. This approach extends customer lifetime, increases total revenue across that lifetime, and reduces price-driven churn because customers are treated as individuals with specific needs.
The telcos still competing on “unlimited data for $X per month” will continue fighting margin-eroding price wars – if they even still exist! The ones delivering seamless, personalized experiences will capture disproportionate value.
The data is already flowing through telco systems. The decisioning platforms are mature. The technical talent exists. The only variable is speed: how quickly telcos move from evaluation to implementation, from pilot to production, from feature parity to competitive advantage.
The operators who win will be the ones who recognize that their engineering culture and risk tolerance are assets, not liabilities. They just need to point them in the right direction.
