Skip to content

Revenue Protection Analyst

Investigate commercial and industrial theft-of-service cases

Enhances✓ Available Now

What You Do Today

Handle the high-value cases — large commercial accounts with CT tampering, demand ratchet avoidance schemes, and industrial customers manipulating power factor to reduce bills.

AI That Applies

C&I theft AI analyzes demand profiles, power factor patterns, and CT ratios against expected values for the premise type, identifying sophisticated manipulation that simple threshold alerts miss.

Technologies

How It Works

The system ingests demand profiles as its primary data source. The analytics engine aggregates data across sources, applies statistical analysis to identify significant patterns and outliers, and presents the results through visualizations that highlight what needs attention. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

Sophisticated commercial theft schemes become detectable. AI identifies the CT ratio manipulation or the demand limiter that shaves peak demand — schemes designed to evade simple monitoring.

What Stays

C&I investigations require deep technical knowledge of metering, rate structures, and electrical systems. You still investigate on-site, work with metering engineers, and build cases worth six or seven figures.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for investigate commercial and industrial theft-of-service cases, understand your current state.

Map your current process: Document how investigate commercial and industrial theft-of-service cases works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: C&I investigations require deep technical knowledge of metering, rate structures, and electrical systems. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Demand Analysis AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long investigate commercial and industrial theft-of-service cases takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your CFO or VP Finance

What are the top 5 reasons customers contact us, and which of those could be resolved without a human?

They're prioritizing which finance processes to automate first

your ERP or finance systems admin

How do we currently measure service quality, and would AI-assisted responses change that measurement?

They know what automation capabilities exist in your current stack

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.