Challenges in Analyzing Blockchain Data

1. Introduction

When looking into a wallet, account movements are often not immediately understandable. Inflows and outflows of ETH or stablecoins like USDC leave room for interpretation: Is it a trade, a transfer, or an interaction with a liquidity pool?

The analysis of on-chain transactions reveals a high degree of complexity. Blockchain explorers provide raw data, but without the necessary context. They show cash flows, fees, and token interactions, but deliver no semantic classification. For portfolio tracking, reporting, and tax returns, these uninterpreted data are often insufficient.

The challenge of on-chain analysis affects many market participants. The following explains the limitations of blockchain explorers and the advantages of automated solutions.

2. Limitations of Blockchain Explorers

Explorers like Etherscan or BscScan are essential tools, but primarily offer a technical view of the data. Transactions are presented as raw data, which complicates interpretation.

Typical problems include:

• Inflows: The distinction between rewards, trades, or transfers is not immediately apparent.
• Outflows: It is often unclear whether a sale, an exit from a liquidity pool, or an internal transfer has occurred.
• DEX Interactions: With a swap on Uniswap (e.g., ETH → USDC), context information regarding fees, slippage, or LP tokens is often missing in the explorer.

Especially in the DeFi sector, complexity increases. Withdrawing liquidity from a pool is incorrectly classified by some tools as a taxable sale. Internal transfers between own wallets can also be mistakenly interpreted as income.

Conclusion: Blockchain explorers document that a transaction took place, but do not explain its economic substance. For precise portfolio management and tax reporting, the missing context is problematic.

3. Tax Classification of Transactions

A common source of error in crypto tracking is the incorrect tax classification of transactions. Not every movement is taxable, nor is every movement tax-free. Correct classification is essential for compliance.

Overview of Transaction Types:

✅ Trades (Crypto Trading)
→ Generally taxable (Profit/Loss).
The sale against fiat or the exchange of crypto to crypto (e.g., BTC → ETH) is considered a taxable disposal in many jurisdictions.

✅ Swaps
→ Generally taxable.
The exchange within the crypto ecosystem (e.g., ETH → USDC) is also often evaluated as a realization event.

✅ Staking/Lending Rewards
→ Potentially taxable.
Taxation varies by country; inflows are often evaluated as income upon receipt.

❌ Wallet Transfers (Self-Transfers)
→ Not taxable.
Transfers between own wallets (e.g., Ledger to MetaMask) do not represent a tax event, but are often misinterpreted by simple tools.

❌ Provision of Collateral
→ Not taxable.
Depositing collateral (e.g., ETH on Aave) is comparable to a security deposit. Tax relevance often arises only upon liquidation.

⚠️ Liquidity Providing & Withdrawals
→ Complex.
Contribution to liquidity pools can be evaluated as an exchange depending on the design. Upon exit, users often receive a different token composition back. Precise documentation is indispensable here.

Without correct categorization, there is a risk of miscalculating the tax burden. Intelligent data preparation helps with correct classification.

4. Challenges of Manual Recording

With low trading activity, manual recording may be possible. However, with more complex portfolios, this method reaches its limits.

Factors that increase complexity:

• Use of multiple wallets (CEX, DEX, Cold & Hot Wallets)
• Regular trading
• Provision of liquidity in DeFi pools
• Reinvestment of rewards

Manual documentation, valuation, and categorization of these processes is time-consuming and prone to error. Even minor input errors can distort the entire reporting. Automated systems offer a necessary solution for efficient data processing here.

5. Automated Tracking via APIs

An efficient solution lies in the use of API-supported tracking systems. These automate data collection and ensure correct classification.

Our Analytics API enables professional preparation of data without manual effort.

Functionality:

• Automatic Wallet Sync: By connecting wallets, transactions are imported automatically and seamlessly.
• Intelligent Categorization: Trades, transfers, rewards, and DeFi interactions are recognized and assigned.
• Transparent Reports: Structured data enable analyses for taxes, portfolio performance, and compliance.
• Real-time Analysis: Tax-relevant events are identified.

API-based systems replace uncertainty with structured data and enable efficient reporting. The focus is thus on asset management rather than data maintenance.

6. Conclusion: Structuring On-Chain Data

Manual tracking or the sole use of explorer data is often insufficient for complex requirements. On-chain data requires categorization to be usable for reporting and tax purposes.

Summary:

• Explorers offer transaction data, but often without the necessary context.
• The tax relevance of transactions varies and requires precise classification.
• Automated solutions via APIs offer efficiency and data accuracy.

The use of API-supported tracking systems ensures a clean, auditable database for professional actors.