- H2O Driverless AI forecasts deposit balances, runoff and cash flows from your own history, with reason codes on every forecast.
- The same forecasts feed liquidity metrics, such as the liquidity coverage ratio and net stable funding ratio, and your funding plan.
- Models of prepayment and deposit behavior help your team size hedges and test them against rate scenarios.
- An agent assembles the liquidity and hedging pack for your asset and liability committee and drafts the commentary; your team reviews it and decides.
Your treasury team reports on yesterday
Your team forecasts liquidity from deposit, loan and market data that sit in several systems. Many of the behavioral assumptions, such as how long non-maturity deposits stay and how fast loans prepay, are reviewed once a year while customer behavior changes faster.
When rates move, you need to know what happens to deposits, funding costs and your hedges at the same time. Rebuilding that view by hand takes days, and the reporting pack often arrives after the market has moved again. Every model also has to be explainable to your committee, your model risk team and your supervisors.
How liquidity risk and hedging analytics works
Your treasury and ALM analysts build forecasting and behavioral models in H2O Driverless AI, deploy them with H2O MLOps, and use an agent to assemble the reporting.
Step 1: bring the balance sheet data together
Start from deposit balances by product and segment, loan cash flows and prepayments, wholesale funding maturities, collateral and liquid asset positions, and market rates.
Step 2: forecast deposits, cash flows and funding needs
Time series models produce forecasting views of deposit balances, runoff and daily cash flows, and regression models estimate how behavior changes with rates, pricing and customer attributes.
Step 3: size and test hedges
Behavioral models of prepayment and deposit duration feed measures of net interest income and economic value, which your team runs under rate scenarios to see where a hedge is too large, too small or no longer effective.
Step 4: explain and document
Reason codes built on Shapley values show what moved each forecast, and AutoDoc records the data, validation and final model for your model risk team.
Step 5: prepare the reporting pack with an agent
An agent collects the latest forecasts, compares them with your limits and last period, and drafts the liquidity and hedging commentary. Your team checks it and decides; the agent does not place trades or change hedges.
What the agent does not do
H2O does not make your models or reports compliant with liquidity, interest rate risk or hedge accounting rules. Your methodology, validation and sign-off stay with your team, and the agent's role stops at a draft your committee reviews.