# Overview

Managing risk is paramount for a lending protocol dealing with volatile assets and varying network conditions. Helios introduces an **adaptive risk optimization framework** that continuously adjusts parameters like Loan-to-Value (LTV) ratios and liquidation incentives in response to real-time conditions. This is a departure from traditional protocols where risk parameters are set statically by governance and updated infrequently. We will discuss how Helios uses *mempool- and volatility-aware adjustments*, a *convex optimization model*, and how **liquidations** are handled in this dynamic system.

In summary, liquidation in Helios is designed to be **robust and responsive**: robust by staying on-chain in BTC (trustless settlement) and offering clear incentives, and responsive by adjusting thresholds and rewards based on network conditions to always entice liquidators to do their job. Lenders (those supplying BTC) are protected by these mechanisms ensuring troubled loans are handled promptly, while borrowers benefit from a system that might give them chances to save their positions (via top-ups or partial liquidation) rather than an all-or-nothing liquidation. This adaptive liquidation framework ties together with the convex risk model – essentially being the execution arm of Helios’s risk management, ensuring solvency of the protocol under all conditions.

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