1. Building a Financial Knowledge System
Financial personnel building a system rely on personal experience, which may be limited by knowledge level, resulting in an imperfect system.
Based on big data and machine learning, it integrates industry best practices with real-time data to automatically generate adaptive solutions; it identifies risks through AI algorithms, optimizes resource allocation, and reduces human error; the system continuously learns from business data and external environmental changes, automatically updating rules and models to maintain system advancement.
2. Financial Risk Control
Financial personnel analyze risks through periodic reports, but problems may have already caused losses (such as overdue accounts receivable).
Based on the provided data, it performs real-time monitoring of customer credit, payment terms, industry fluctuations, etc., triggers alerts, and recommends coping strategies (such as adjusting credit limits).
3. Financial Forecasting and Budgeting
The finance team needs to manually summarize historical data and coordinate departmental needs, which takes 2-3 weeks and can easily lead to deviations due to inconsistent data standards.
It automatically fetches historical data and business system information, generating multiple versions of budgets (optimistic/neutral/pessimistic) in 1-3 days, and supports dynamic adjustments.
Financial personnel develop tax planning schemes based on the enterprise’s current situation and tax law knowledge, but are limited by personal knowledge reserves and sensitivity to policy changes, leading to obvious policy delays in obtaining or missing out.
Based on the enterprise’s historical data, industry data, and real-time policies, it generates optimal solutions through algorithms; it comprehensively considers the overall tax burden of the enterprise, optimizing across tax types and business links (such as VAT, income tax, customs duties, etc.).
5. Financial Data Analysis
Financial personnel need to manually input data, apply various functions, and spend a lot of time organizing data.
With its built-in data analysis engine, DeepSeek can quickly conduct multi-dimensional analysis on extracted data, extract key data, and generate preliminary analysis results.
6. Financial Process Auditing
Financial personnel need to manually review original documents, accounting vouchers, and other financial materials to ensure their authenticity, completeness, and accuracy. During the review process, financial personnel need to judge financial data based on their professional knowledge and experience.
DeepSeek can quickly read and understand complex financial documents using natural language processing (NLP) technology, automatically identify and extract key information, thus improving auditing efficiency.
True financial experts are adept at using modern technological tools, delegating repetitive tasks to tools, thereby freeing their time and energy to focus on strategic decision-making, and creating more value for the enterprise.
The future of financial personnel is not about being replaced, but about reshaping. Embracing DeepSeek is embracing a future of wisdom and efficiency.
