Energy retail revenue assurance & settlement
Here's what AI can do for this role — and what still needs a human. Built straight from ENSEK's own job advert, running live on my_db.ensek_demo.settlement_imbalance — 4,320 real rows via MotherDuck (DuckDB). Not a slide about AI. The job, getting done.
Every line on the left is lifted from ENSEK's actual job ad. If a card lacks a harvested JD line, it is omitted. On the right is the AI doing it — with eligible cards running live against the warehouse and offline inspection clearly labelled in the workspace.
“Own the financial relationship with assigned B2B clients, acting as their trusted advisor on energy accounting and revenue assurance matters.”
What is the monthly settlement imbalance price profile — average, minimum and maximum by month?
bar chart“Oversee the delivery of monthly financial outputs, including revenue recognition, gross margin, reconciliations, variance analysis, and controls reporting.”
What is the average spread between system buy price and system sell price — how wide is the market imbalance margin by month?
table“Review and challenge analytical work produced by the Customer Financial Assurance team, ensuring accuracy, completeness, and clarity before client submission.”
Which half-hour settlement periods within the day consistently attract the highest imbalance prices?
table“Provide commercial insight into consumption trends, billing performance, and financial risks, translating technical data into clear, actionable recommendations.”
What is the daily price range — min, max and average imbalance price for each settlement day?
table“Collaborate with operations, billing, data, and product teams to resolve issues, improve data quality, and strengthen financial controls.”
Which settlement periods show low imbalance prices — where did the system have surplus energy?
deviation“Own the financial relationship with assigned B2B clients, acting as their trusted advisor on energy accounting and revenue assurance matters.”
What is the overall settlement imbalance KPI summary — total periods, average price, price cap hit rate?
kpi“Oversee the delivery of monthly financial outputs, including revenue recognition, gross margin, reconciliations, variance analysis, and controls reporting.”
What are the buy/sell spread extremes by month — peak buy price, minimum sell price and widest single-period spread?
tableThe honest other half. AI does the analysis; a person owns the decision — especially where regulation, fairness and accountability bite.
A plain-English question — the same one the job ad describes — is translated to SQL by the agentic backend.
Curated cards run server-side against MotherDuck when eligible. The workspace separately labels any local inspection path.
Runs against my_db.ensek_demo.settlement_imbalance (4,320 rows declared by the manifest). No synthetic numbers.
Each figure carries a falsifier — recomputed from the result set, not a stored number, so it can't quietly drift.
It's the role getting done: curated questions run live server-side against the warehouse; local inspection is labelled inside the workspace.
Open the live workspace →Provenance. Live ENSEK settlement data: 4,320 rows, three months (June-August 2025), 48 half-hourly settlement periods per day. Schema: my_db.ensek_demo.settlement_imbalance. net_imbalance_volume_mwh excluded (overflow values in source). Local fallback uses the same pre-projected slice in-browser.
It's Sorted — I took ENSEK's job ads and didn't write a report on what AI could do. I built it. Get the rest sorted →
I'm trained on this proof and the real ENSEK: the Ignition meter-to-cash platform (seven modules), the move under Centrica in 2024, 7M+ energy accounts migrated for suppliers like British Gas and Utility Warehouse, and the Ofgem framing. Ask me how the Data Analyst function changes shape, or which open roles map to which Ignition module.