Customer Risk and Transactions Analysis
A risk desk view of 2,000 banking customers and 157,224 transactions: high-risk segmentation, transaction value, and failed-transaction rate, with a drilldown tab per dimension.
Every artifact below was generated by the Wren AI agent against a governed context layer; no dashboard was hand-built. Open one to read the exact prompt and the steps the agent took.
A risk desk view of 2,000 banking customers and 157,224 transactions: high-risk segmentation, transaction value, and failed-transaction rate, with a drilldown tab per dimension.
The prompt
ask ▸ Analyze customer risk and transaction behavior across the banking dataset. Surface the high-risk customer share, total and failed transaction value, and let a reviewer drill from the overview into customers and transactions.
17 / 17 artifacts
A risk desk view of 2,000 banking customers and 157,224 transactions: high-risk segmentation, transaction value, and failed-transaction rate, with a drilldown tab per dimension.
Eleven widgets over customer behavior, card portfolio mix, transaction patterns, geographic concentration, and risk segmentation: time series, category mix, geo, heatmap, radar, bubble, and dual-axis views.
The full transaction history read by merchant category: transaction mix, customer risk segments, card brands, and top geographies across Jan 2022 to Oct 2024.
An analyst-style operating readout of completed-order sales, customer concentration, product demand, inventory risk, web activity, and geographic revenue concentration.
A CS and RevOps read on account health: average and total MRR, churn rate, and the large neutral middle whose sentiment hides early churn risk.
A five-part diagnostic of where revenue is leaking: logo churn, gross MRR churn, NRR and GRR, average tenure at churn, and which accounts deserve intervention first.
Where inventory capital is parked, how demand compares with supply, where flow is breaking down, and which SKUs need attention next, with turnover, weeks of cover, and reorder signals.
The path from global demand to category-level product opportunity, weighing momentum, penetration, repeat behavior, and basket adjacency to pick the strongest category candidate.
A SaaS operating view across 3,000 accounts: current MRR base, active-account share, churn rate, and portfolio health score, split into overview, plans, usage, and retention tabs.
Whether care delivery is producing good outcomes across 3,500 encounters in 10 departments: a composite quality lens over mortality, readmission, complications, improvement, and patient satisfaction.
An executive KPI rail (encounter volume, readmission rate, trend performance, and mix) presented with chart-level callouts so the important signals read without studying the charts.
Sixteen charts plus KPI widgets on patient experience, channel mix, financials, and risk, with an interactive department filter for drilling into a single service line.
5,531 diagnosis records across 969 patients and 3,500 encounters: primary diagnosis rate, present-on-admission rate, and more than ten widgets on volume, outcomes, demographics, and financial performance.
A population read on 1,000 patients and 3,500 encounters: age and gender balance, insurance mix, where care activity concentrates across outpatient and inpatient settings, and readmission burden.
Portfolio production and revenue against target (1.46bn barrels, $106.92bn revenue, 75.79% capacity utilization) with downtime, safety, and intensity metrics pointing at where operational focus should shift.
20.4K deliveries across 10 distributors, 49 pickup states, and 49 delivery states: 87.6% on-time rate, 90.3% successful-delivery rate, and a 68.5-hour average delivery time.
A plant executive layout with a left KPI rail and 20 widgets: 99.6% yield on 4.78M good units, production and labor cost trends, and top production lines by runtime versus downtime.
Connect a warehouse, model it once, and ask. The agent writes the plan, runs the SQL under your access policy, and hands back the artifact.
