Trends & Forecasts
Every metric projects forward from one shared dataset - net interest income, the full balance sheet, cash, funding, forward rates, and the capital and liquidity ratios. Run it across the horizons and granularity your institution sets; the three-year, quarter-by-quarter view below is illustrative. Change a rate path or a business assumption once, and every projection re-derives together.
Forecast horizon
12 quarters
Q3 2026 → Q2 2029
Net interest income
$148M → $173M
+16.9% over horizon
CET1? ratio
12.4% → 13.2%
+80 bps capital build
Liquidity coverage
118% → 125%
LCR, period-end
How forecasting works
Each method runs against the same shared dataset, so results are directly comparable - and any method can challenge another.
Business-as-usual baseline
Market forward curves drive repricing, reinvestment, and new-business yields - a market-consistent path with no manual rate view.
Output · market-consistent path
Management growth, volume, and spread assumptions by segment translate into a projected balance sheet and earnings plan.
Output · plan vs. actual
Contractual and behavioral runoff plus replicating-portfolio reinvestment age the existing book forward realistically.
Output · maturity & reprice ladder
Stress & scenario
Base, rising, and falling rate paths run through the shared dataset. Every metric reprices on the same explicit assumptions.
Output · point estimate per path
Thousands of correlated rate and balance paths produce full distributions - percentiles and tail outcomes, not a single line.
Output · P5–P95 ranges
Regressions link GDP, unemployment, and home prices to balances, deposit betas, and losses - aligning forecast with stress.
Output · macro-linked forecast
What gets forecast
SOFR and the UST curve by tenor - the path that drives every repricing assumption.
View curveLoans, securities, cash, deposits, wholesale funding, and equity - projected and tied.
View projectionQuarterly NII, NIM, earning-asset yield, and cost of funds.
View forecastCentral-bank cash, HQLA (High-quality liquid assets - cash and assets easily sold under stress.), term funding raised, and the survival horizon.
View positionCET1, leverage, total capital, LCR (Liquidity Coverage Ratio - 30-day cash survival under stress.), NSFR (Net Stable Funding Ratio - 1-year funding stability.), plus ROA, ROE, and efficiency.
View ratiosThe trades the optimizer proposes to hit the forecast - with full metric impact.
View ticketsRate environment
The market-implied curve that drives repricing, reinvestment, and new-business yields across the projection.
Period-average yield, percent
Business balance sheet
Asset and funding mix aged forward on runoff and new-business assumptions - both sides tie to total assets each quarter.
Earnings
NII rebuilds as the book reprices into the forward curve; margin compresses early, then stabilizes as funding costs reset.
NII $M (left axis) · NIM % (right axis), per quarter
Liquidity & cash
A 13-week (90-day) projection of the cash balance against the minimum operating buffer - the treasury view of the immediate liquidity runway.
$ in billions · 13 weeks
Starting cash
$3.80B
90-day low
$3.27B
week 7
Ending cash
$3.85B
Buffer headroom
+$0.27B
above $3.0B floor
Ratios
The full ratio set is tabulated; the two most-watched constraints - CET1 and LCR - are charted against their regulatory floors.
Critical metric · percent, period-end
Critical metric · percent, period-end
From forecast to action On deck
When the forecast surfaces a gap, the optimizer generates the actual trade and funding tickets to close it - each priced with its full impact on earnings, capital, and liquidity before you execute.
Trade source
Input your own desired trades, or let the optimizer solve for the least-cost set based on your defined constraints - the platform prices the full impact on earnings, capital, and liquidity either way.
Select a quarter to inspect its tickets
Interactive · click to exploreDeposit behavior
Deposit balance and pricing models are calibrated in a single framework (alongside mortgage prepayment), so a pricing change flows consistently into behavioral response, funding stability, and market share - then conditioned on the prevailing Fed policy regime. These assumptions feed the NII?, cash, and liquidity forecasts on this page.
Deposit balance & pricing model
Each segment carries up- and down-rate betas (pass-through), a behavioral life, and a non-core share that prices like wholesale funding. Calibrated alongside mortgage prepayment, the model keeps behavioral response, funding stability, and market share consistent - especially during large market moves.
Deposit market share vs. relative pricing
illustrativeShare rises with relative pricing; the model solves the share-versus-cost-of-funds trade-off rather than assuming a fixed balance.
| Segment | Balance | β ↑ | β ↓ | Beh. life | Non-core |
|---|---|---|---|---|---|
| Retail checking (DDA) | $9.8B | 8% | 5% | 6.2y | 12% |
| Savings & MMDA | $14.2B | 42% | 35% | 3.8y | 22% |
| Retail CDs | $6.1B | 78% | 70% | 1.1y | 5% |
| Commercial operating | $11.4B | 35% | 28% | 4.5y | 30% |
| Brokered / wholesale | $4.7B | 95% | 92% | 0.5y | 100% |
Fed regime modeling
IllustrativeDeposit behavior is not static. Rate regimes - hiking, on-hold, cutting - reprice deposits (they move betas). Balance-sheet regimes - QE and QT - change the total volume of deposits in the system. Select a regime to re-flow betas, runoff, and volume.
Blended deposit beta
40%
balance-weighted · price
Total deposit volume
$46.2B
base · quantity
| Segment | Balance | Deposit beta | 12-mo runoff |
|---|
These deposit assumptions are the same ones driving cost of funds in the NII forecast and the deposit run-off in the cash & survival projection below - change the regime and the whole forecast re-prices.
Ready to see it live?
A guided demonstration using public filings and disclosed assumptions. Institution-specific risk estimates depend on data availability; production analysis requires more detailed inputs.
About us
Bulls-Eye Solutions builds the enterprise platform for financial institutions - one platform that unifies risk, capital, liquidity, funds transfer pricing and attribution on one shared dataset, with optimization on deck. Founded by veterans of top-tier bank treasury and risk management, we pair the platform with experienced treasury and risk practitioners, delivered as Risk-as-a-Service.