Data scattered across systems
ERP, banking, billing, loan and spreadsheet data never quite tie out, so every report starts with a manual reconciliation.
Industries / Finance
Agentic BI for FinanceYour financial data has a goal.It finds why the numbers moved.
The agentic BI platform for finance teams. Your AI analyst investigates cash flow, credit performance and variances across your ledger, payments and loan data. Every number cited, never guessed.
No credit card · 14-day team trial
Finance analysisledger_q3.csv
LiveQuestion
Why is operating cash flow down this quarter?
Invoices paid on time, by segment%
Root cause
Mid-market invoices are paying 19 days late since the billing change, and 14 accounts hold 58% of the overdue balance.
60s
to connect your database and start asking
100%
of numbers cited to a query that ran
24/7
monitoring on the metrics and accounts you put on watch
The finance data problem
Every transaction is recorded. Almost nothing is explained.
Your ledger, banking, billing and loan systems each hold part of the picture. Seeing that a number moved is easy. Knowing why takes an analyst days of reconciling, and the close is already behind you.
Cash flow surprises
Receivables slip and payments land late, and the gap only shows once the cash isn’t there.
Risk building unseen
Delinquency and exposure creep up in pockets of the portfolio long before the quarterly review.
Anomalies buried in volume
Unusual transactions hide in millions of rows, and reviewers can’t sample their way to them.
Variances explained by hand
Budget gaps take days to explain, and the commentary is out of date by the time it’s read.
Reports that go stale
Static packs are out of date the moment they’re sent, and two teams rarely agree on the same number.
How it works
From connected to monitoring in two days
No SQL, no ticket to the data team. SchemaChat does the heavy lifting.
See it in action
Ask the questions finance teams actually ask
Four real-world questions, answered the way SchemaChat answers them: the number, the why, and a chart of what it found.
Ask
Why is operating cash flow down this quarter?
- Compared cash collected with cash due by segment and month
- Aged every open invoice by customer
- Checked payment terms and billing changes over the period
SchemaChat
Operating cash flow fell 14% quarter on quarter. Late collections from mid-market customers explain most of the drop.
Root cause
Mid-market invoices are being paid 19 days later since the billing change, and 14 accounts hold 58% of the overdue balance.
Ask
Where is delinquency rising in the loan book?
- Calculated delinquency by product, channel, vintage and region
- Compared each against its own 12-month trend
- Checked credit bands and loan terms at origination
SchemaChat
30-day delinquency is 4.1%, up from 3.2%. One origination channel and one vintage account for most of the increase.
Root cause
Loans originated through the partner channel last spring have a thinner credit profile, and their early arrears run at three times the book average.
Ask
Which transactions look unusual this month?
- Compared each transaction with its account’s own history
- Flagged unusual amounts, timing, devices and merchants
- Grouped the flags by pattern so reviewers see clusters, not rows
SchemaChat
212 of 4.1 million transactions sit outside the normal pattern for their account or merchant, and are queued for review.
Root cause
Most flags form three clusters: repeated payments just under a limit, new devices at odd hours, and one merchant with sudden volume.
Ask
Why is operating spend 8% over budget?
- Compared actuals with budget by department, category and month
- Separated timing differences from real overruns
- Traced the largest variances back to their transactions
SchemaChat
Operating spend is $1.9M over budget. Cloud costs and contractor spend account for most of the overrun.
Root cause
Cloud usage grew 31% after a product launch that wasn’t in the budget, and contractor hours were extended to cover it.
What teams use it for
One analyst for every finance question
From treasury to credit to the close, the same governed numbers answer every team.
Cash · Days to collect · Collections
Cash flow & liquidity
See cash in and out by segment and week, and which receivables are slipping before they hit your balance.
Delinquency · Exposure · Roll rate
Credit risk & delinquency
Track arrears and exposure across products, channels and vintages, and find the pockets that are moving.
Flag rate · Patterns · Review queue
Anomalies & unusual activity
Surface unusual transactions and group them into patterns, so reviewers spend time on what matters.
Variance · Run-rate · Forecast
Budget vs actuals
Explain variances as they happen, by department and category, instead of a week after the close.
Margin · Cost to serve · Churn
Customer profitability
See which customers and products earn their keep once the cost to serve is included.
Audit trail · Tie-out · Close time
Audit & reporting trail
Produce figures that trace back to source, with every number linked to the query behind it.
Automated dashboards
Finance dashboards that build themselves
- Ask “build me a finance performance dashboard”. It picks the KPIs and charts.
- Live, not snapshots. Every widget re-queries on each view.
- Click any portfolio on the map to cross-filter the whole board.
Try it: click a portfolio on the map.
Build me a finance performance dashboard
30-day delinquency4.1%+0.9pt
Net interest margin3.2%+0.1pt
Cost-to-income58.4%+1.2pt
Collection rate94.6%−1.1pt
Portfolios & flowsColour = 30-day delinquency
Delinquency by portfolio
Collection rate, last 12 weeksNow 94.6% · was 96.6%
Integrations
Works with the data you already collect
SchemaChat reads the database your finance systems already feed. There’s no new tracking to install and no data to re-enter.
- General ledger & ERP
- Banking & payments
- Loan origination & servicing
- Billing & invoices
- Customer & account data
- Market & rate feeds
- Risk & review logs
- Spreadsheets & CSV
Your database read-only
SchemaChat reads from
- PostgreSQL
- MySQL
- BigQuery
- Snowflake
- MongoDB
- CSV files
schemachatAI data analyst
- Root-cause analysisInvestigating cash flow drop
- Live dashboardsLending performance · re-querying
- Alerts & monitoringDelinquency > 5% · watching
- Cited answersEvery number traced to its source
Read-only, credentials encrypted.See all integrations →
FAQ
Questions finance teams ask
Which finance systems does SchemaChat work with?
SchemaChat connects to the database your systems write into: PostgreSQL, MySQL, BigQuery, Snowflake or MongoDB. If your ledger, payments or loan data lands in one of those, or in a CSV export, you can start asking questions straight away.
Do finance teams need SQL knowledge?
No. You ask in plain English. SchemaChat writes and runs the queries, and shows the exact SQL behind every answer, so your data team can check it any time.
How do I know the numbers are right?
Every figure comes from a query that actually ran, with the step behind it cited. Define a metric like days to collect once, and every analysis and dashboard uses the same formula. If the data isn’t there, SchemaChat says so rather than guessing.
Is our financial data safe?
All AI queries are SELECT-only, enforced at the SQL parser layer, so SchemaChat cannot modify or delete your data. Database credentials are encrypted at rest, and you choose which tables and views it can see, so personal fields can be left out. If you handle regulated data, check your own compliance requirements before connecting.
Does SchemaChat give financial advice?
No. It analyses your own business data to explain what happened and why. It does not recommend investments, make credit decisions or replace the judgement of your finance and risk teams.
Can finance and audit teams trace the numbers?
Every figure is cited to the query that produced it, so a reviewer can see exactly how a number was calculated. It doesn’t replace your audit process, but it makes the trail easy to follow.
Can it alert us when a metric goes off track?
Yes. Put any finding on watch, for example a portfolio’s delinquency rate or the collection rate, and you’ll be alerted when it crosses a threshold, along with a digest of what changed.
Can we pull answers into our own tools?
Yes. The REST API lets you ask questions, run read-only queries and pull charts from your own backends, Slack bots and automations using a Bearer token.
How much does it cost to try?
The 14-day team trial lets you connect your own database (read-only) or upload CSVs, run deep analyses and build dashboards, with no credit card and up to 3 seats. After the trial, Premium and custom plans for larger teams are on the pricing page.
Put an AI analyst on your finance data today
Connect a database or upload a CSV of recent transactions and ask your first question in about a minute.
- 14-day team trial, no credit card
- No credit card
- Cancel anytime