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The Kamino Risk Assessment Framework (KRAF) dashboard is a public, real-time risk monitoring tool available at risk.kamino.finance. It provides complete visibility into the protocol’s risk posture — every metric referenced in the risk framework documentation is available live on this dashboard. The dashboard is maintained by Allez Labs, Kamino’s risk management partner, and is updated continuously with on-chain data.

Risk Overview

The main view provides a summary of protocol-wide risk metrics:
  • Deposits, borrows, and rates for every listed asset across all Kamino markets
  • Utilization rates — how close each reserve is to full utilization
  • Global caps — supply caps, borrow caps, and their current utilization
  • Liquidation-at-risk — the dollar value of positions that would be liquidated at various price shock levels (e.g., -10%, -20%, -30%)
  • Deposit and borrow distribution — composition of the protocol’s total TVL by asset
  • Interest rate curves — the current rate curve parameters and actual rates for each token
This view answers the question: what does the protocol look like right now, and where are the pressure points?

Loans Analysis

A filterable, tabular view of every active loan on the protocol:
FieldDescription
Current LTVThe loan’s current loan-to-value ratio
Max LTVThe maximum LTV allowed for this loan’s collateral mix
Liquidation LTVThe threshold at which the loan becomes liquidatable
Total DepositsDollar value of all collateral in the position
Total BorrowsDollar value of all debt in the position
Net ValueDeposits minus borrows — the borrower’s equity
Each loan can be expanded to show a detailed per-loan visualization — how the LTV has changed over time, which assets compose the collateral and debt, and how close the position is to liquidation.

Token Decompositions

For each loan, the dashboard breaks down:
  • Deposit composition — which tokens make up the collateral, in what proportions
  • Borrow composition — which tokens are borrowed, in what proportions
This reveals concentration risk at the individual loan level — a loan that is 100% JitoSOL collateral / 100% USDC debt has a very different risk profile than a diversified position across multiple collateral tokens.

Volatility Risk

The volatility tab provides:
  • Token price time series — historical price charts for all listed assets
  • Parkinson’s realized volatility — rolling Parkinson’s volatility time series, showing how each asset’s volatility has evolved over short, medium, and long-term windows
This allows direct comparison of volatility regimes across assets and over time. A sudden spike in an asset’s Parkinson’s volatility may signal the need for parameter review.

Liquidity Risk

The liquidity tab provides real-world, on-chain liquidation cost data:
  • Percentage price impact for buy and sell Jupiter swaps at various USD sizes ($10K, $50K, $100K, $500K, $1M+)
  • Impact comparison across assets — which assets can absorb large trades, and which cannot
  • Historical price impact trends — whether liquidity is improving or deteriorating for each asset
This data directly answers the core market risk question: at the current supply cap, could a max-size position be liquidated profitably? If the price impact at cap-implied max position size exceeds the liquidation bonus, the cap may need to be lowered.

Price Shock Analysis

The most sophisticated section of the dashboard. It models four types of stress scenarios:

Uniform Shock

All token prices drop by the same percentage simultaneously (e.g., -20% across the board). This models a broad market crash and shows:
  • How many positions become liquidatable
  • Total dollar value at risk
  • Expected bad debt (if any positions would cross the insolvency threshold)

Individual Token Shock

A single token drops by a specified percentage while all others remain stable. This models an idiosyncratic event (e.g., a smart contract exploit, a depeg) and reveals:
  • Protocol exposure to that specific token
  • Which loans are affected
  • Whether isolation mechanisms contain the damage

Correlation-Based Shock

Correlated groups of tokens decline together (e.g., SOL + all LSTs drop 25%, while stablecoins hold). This is the most realistic stress model, as it reflects how markets actually behave during downturns — correlated assets move together.

Historic Event Replay

Replays actual historical events (e.g., the February 2026 crash, the April 2025 SOL/ETH crash) against the current protocol state. This answers: if that event happened today, with today’s positions and parameters, what would the impact be?

Stress Testing Data

The monthly risk reports published by Allez Labs include detailed stress testing at standard shock levels. Representative data from the November 2025 report:
Shock LevelLiquidation VolumeEstimated Bad Debt
-10%~$50M$0
-20%~$137M~$2.3M
-30%~$275M~$11.6M
-40%~$419M~$32.6M
-60%~$845M~$119M
These stress tests calibrate the protocol’s resilience envelope. A -10% shock produces zero bad debt. A -20% shock produces minimal bad debt. Beyond -30%, the numbers grow — but these are instantaneous, uniform shocks (all prices drop simultaneously with no time for liquidators to act), representing an extreme worst case. In practice, even the February 2026 event — SOL -18% over 48 hours — produced $0 bad debt, because liquidators had time to act and the price decline was not instantaneous.

Risk Reduction Modeling

The risk reduction tab models the impact of proposed parameter changes before they are implemented:
  • Cap reductions — if supply cap for Asset X is reduced from $50M to $30M, how does the risk profile change?
  • Auto-deleverage scenarios — if positions above a certain LTV are deleveraged, what is the net effect on protocol risk?
  • LTV adjustments — if Max LTV for Asset Y is lowered from 75% to 65%, how many positions are affected and what is the change in liquidation-at-risk?
This allows the Risk Council to quantify the impact of proposed interventions before executing them — ensuring that parameter changes achieve the intended risk reduction without unnecessary disruption to users.

Monthly Risk Reports

Since early 2025, Allez Labs has published comprehensive monthly risk reports to the Kamino governance forum. Over 14 reports have been published to date. These reports provide:
  • Protocol-level metrics: Total supply, debt, TVL, transaction volumes, liquidation counts
  • Market-by-market analysis: Supply, borrow, and utilization trends across all Kamino markets
  • Stablecoin and SOL market analysis: Composition shifts, rate dynamics, LST trends
  • Vault performance: TVL, curator activity, user flows across Earn Vaults
  • Stress testing scenarios: Instantaneous price shock modeling at multiple severity levels
  • User behavior analysis: Wallet activity, transaction patterns, concentration metrics
These reports create a public, auditable record of Kamino’s risk posture over time. Anyone can review the historical data, methodology, and track record. View all risk reports on the governance forum →