Sectors / Telecommunication & Energy

Scoring & analytics for telecoms and energy providers

Scoring models and analytics are widely used by telecommunication, internet and energy providers to manage a large client base efficiently and to support expansion into new segments.

Churn Credit risk Propensity MIS

Models are built to answer specific questions the organisation is already asking: what is the probability that a client leaves, will a client pay the bill, how likely is a customer to react to a given action. MIS design then tracks the business KPIs that follow, allows the organisation to adjust to market events, and makes better use of data it already holds.

Scoring models for telecoms and energy providers

Models for energy and telecoms providers usually cover the following.

Risk & default

Credit assessment at acquisition and through the relationship — will the client pay the bill, and on what terms should they be taken on. The models are built the same way as a bank application scorecard.

Attrition & churn

Probability that a client leaves, so that retention effort is directed at the accounts where it changes the outcome.

Response, cross-sell, renewal

Likelihood of a customer taking up an offer, buying an additional service or renewing at the end of a term.

Profitability & lifetime value

Expected value of a customer relationship over its life, as a basis for acquisition and retention spend.

Utilisation of limit

How much of an assigned limit a customer uses, and what that implies for exposure and for limit setting.

Fraud

Ranking accounts and events by fraud probability so that verification resource is allocated where it is most productive.

Propensity

Customer reaction to a specific action, modelled with machine learning or conventional approaches depending on the data and the implementation environment. Propensity models ›

MIS design

Reporting that tracks key areas of business interest, with business targets and benchmarks attached so that performance can be interpreted and monitored.

Learn more ›

Scorecard development

The full project cycle — design, data quality analysis, development, implementation, validation and on-going maintenance — or any part of it.

Learn more ›

What these engagements deliver

With 30 years of experience developing and supporting predictive models, mostly as credit scorecards for lenders, StatDec helps telecoms and energy providers turn their data into decision models and strategies. The benefits usually fall into the following categories.

  • Ability to automate and standardise actions
  • Targeted customer approach
  • Cost reduction
  • Pro-active strategies
  • A champion/challenger business culture
  • Measurable results
  • Closer portfolio monitoring and data management
  • Collections efficiency

Start with the question, not the model

Tell us which decision on your subscriber base you want to improve, and we will scope the modelling and reporting against the data you already collect.

Get in touch