Real-Time Insurance ALM Infrastructure
Introducing 1LX — AT1’s Real-Time ALM Engine
Real-time ALM infrastructure for insurers and asset managers.
Estimated yield recaptured
20–100+
bps / year by moving from static to real-time ALM across multiple leakage channels.This simulated scenario
98
bpsTotal yield at stake per year in this stochastic scenario.
Reinvestment drag
Range: 10–40 bps
This scenario:
25.0 bps
Cash flows remain in short-term Treasuries instead of target credit assets.
Duration drift & shocks
Range: 5–25 bps
This scenario:
15.0 bps
Duration gap re-opens between meetings and gets hit by rate moves.
Liquidity buffers
Range: 5–20 bps
This scenario:
12.5 bps
Extra cash and high-grade liquidity held idle to cover uncertain outflows.
Suboptimal deployment
Range: 10–35 bps
This scenario:
22.5 bps
Assets deployed into lower-yield opportunities due to limited visibility into forward needs.
Capital inefficiency
Range: 5–20 bps
This scenario:
12.5 bps
Over-capitalized balance sheet limits leverage and wastes investable spread.
Hedge & collateral drag
Range: 5–15 bps
This scenario:
10.0 bps
Hedge budgets and posted collateral sit in cash instead of earning portfolio yield.
Sliders randomly sample within each range every few seconds to show how quickly leakage can add up.
Yield Leakage
Real-time vs quarterly ALM consistently reveals:
- 20–50 bps in asset-yield loss from delayed deployment and short-term parking
- 5–10 bps from improved asset–liability alignment
- Additional basis points from correcting portfolio drift between meetings.
Capital & Solvency Drag
Static ALM increases surplus volatility and inefficient capital usage. This restricts deployment into higher-yield credit and lowers overall ROE, even when staying within guardrails. Real-time ALM improves capital efficiency and reduces solvency noise.
Portfolio Drift & Operational Friction
Legacy actuarial stacks require manual runs, batch processes, and spreadsheets. This slows response to markets, widens duration gaps, and prevents timely investment decisions. By the time the next ALM meeting arrives, portfolios have already drifted out of alignment.
ALM Leakage Lab
See how reinvestment and mismatch leak yield.
Start with a duration-matched book. Watch how reinvestment into short Treasuries creates duration drift, then see how that drifted gap leaks yield at different ALM frequencies.
Reinvestment drag
14.8 bps / yr
≈ 118 bps of cumulative yield leakage over a 8.00-year block.
Coupons and principal that arrive between ALM meetings are temporarily parked in short Treasuries instead of target assets. The model estimates the annual and lifetime yield shortfall this creates at Quarterly ALM.
Duration drift this period
Liability target duration
8.00 yrs
Target liability profile for this block.
Asset duration after this ALM cycle
7.58 yrs
After reinvesting this period's cashflows into short-term Treasuries.
Drifted mismatch
0.42 yrs
Duration gap opened up over this quarterly as cashflows move into short Treasuries and sit there until the next ALM meeting.
Balance sheet assumptions
Liability / target duration8.00 yrs
Portfolio yield9.0%
Treasury yield3.5%
Average time parked in short Tsies50% of ALM period
The model assumes new cashflows between ALM meetings are parked in short-term Treasuries for the selected share of each ALM period, then rotated into target assets at the next ALM date.
Key takeaway: Even if assets and liabilities are perfectly matched on day one, a meaningful slice of the book comes back each year as coupons and principal. Under quarterly or monthly ALM, that cash is often parked in short Treasuries for part of each period, pulling duration down and creating reinvestment drag. Real-time ALM continuously redeploys those flows into target assets, reducing both duration drift and the annual and lifetime leakage shown above.
Structural ALM Frictions (highest impact)
Persistent, model-driven issues that occur on every balance sheet:
Reinvestment drag
Duration drift
Liquidity buffers
Suboptimal deployment
Capital inefficiency
Hedge & collateral drag
Roll-down not captured
Curve-shape mismatch
Credit migration effects
These are the most measurable and often total 20–80 bps on their own.
Market-Driven ALM Frictions
Harder to time and usually amplify existing mismatches:
Rate shocks
Curve steepening / flattening
Spread volatility
Spread beta mismatch
Secondary-market dislocations
These typically add 5–30 bps depending on market conditions.
Operational & Organizational Frictions
These arise because processes move slower than markets:
Settlement timing mismatches
FX and cross-border settlement delays
Procurement and credit-committee cycles
New business variability
Pipeline visibility gaps
Operational lags (systems, approvals, custodians)
Individually small — but together meaningful, often 5–15 bps.
How 1LX Works
Step 1
Onboard Liabilities
Standardize policy data, cash-flow projections, and reserving assumptions. 1LX ingests your existing models and assumptions—no need to rebuild your actuarial stack.
Step 2
Calibrate to Your Risk & Capital Framework
Align ALM with your duration, convexity, liquidity, capital, and credit-risk tolerances, as well as internal governance standards. This establishes the boundary conditions for ALM and portfolio optimization.
Step 3
Map Deployment Constraints & Investment Universe
Capture your investable universe, mandates, internal limits, sourcing constraints, liquidity needs, and target spreads. Real-world constraints become the optimization inputs.
Step 4
Construct & Maintain Liability-Driven Portfolios
1LX builds portfolios that match liability cash flows, maximize yield, and improve capital efficiency—anchored to your risk and balance-sheet profile. ALM is monitored continuously, and portfolios are rebalanced in real time to minimize drift, reinvestment lag, and yield leakage.
