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Generative AI là gì? Khác biệt giữa AI tạo sinh và AI truyền thống & Ứng dụng trong tài chính doanh nghiệp

AI is evolving from data analysis (traditional AI) to new content creation and intelligent data modeling (Generative AI). ChatGPT, Gemini, Claude, Midjourney are popular examples.

Gen AI trong tài chính mở ra khả năng tự động sinh báo cáo, dự báo rủi ro, và hỗ trợ quyết định tài chính. Tuy nhiên, để vận hành hiệu quả, doanh nghiệp cần hệ thống dữ liệu và quản trị (như EPM) đủ mạnh – đây thường là “điểm nghẽn” mà nhiều tổ chức gặp phải.

Let's find out with Bizzi in this article what Generative AI is! 

What is Generative AI and how does it work?

Before understanding how Generative AI is changing the way businesses operate, we need to understand What is Generative AI and how does it work?.

This section will help you visualize cơ chế “tự học – tự tạo” by Generative AI – the technology platform behind ChatGPT, Gemini or Midjourney that you hear every day.

What is Generative AI? 

Generative AI is a type of artificial intelligence that has the ability to create new content – văn bản, hình ảnh, âm thanh hoặc dữ liệu – thay vì chỉ phân tích hoặc dự đoán dựa trên dữ liệu có sẵn. Khi bạn hỏi “generative ai là gì”, đó chính là khả năng “sáng tạo dữ liệu mới” từ mô hình học máy.

Common models in generative AI include LLM (Large Language Models), GAN (Generative Adversarial Networks), Diffusion Models and architecture Transformer.

generative-who-is-what-6

How Generative AI Works

A simple way to visualize it: if data is the “seed”, generative AI is the “tree” that grows new knowledge from that seed.

The Difference Between Generative AI and Traditional AI

To choose the right application, businesses need to clearly understand difference between generative ai and traditional ai in many aspects.

Criteria Traditional AI Generative AI
Main function Historical analysis & prediction Create new content or simulate data
Input data Structured (tables, quantitative data) Unstructured (text, images, audio)
Target Data-driven decision support Generate reports, simulate, and create content automatically
Background technology Machine Learning, rule-based, regression, tree-based LLM, GAN, Diffusion, Transformer
Main applications Revenue forecasting, fraud detection, classification Generate financial reports, create investment scenarios, and automatically generate content

Economic example:

So when you look for “difference between generative ai and traditional ai”, note: Traditional AI helps understand the past & present; GenAI helps expand creativity, simulation and create new insights.

Practical applications of Generative AI in finance

Generative AI không chỉ là công nghệ mới mẻ – nó đã bắt đầu được ứng dụng trong nhiều mảng tài chính doanh nghiệp, từ tự động hóa báo cáo đến hỗ trợ thay đổi chiến lược.

Automate reporting and data aggregation

GenAI can automatic generation of accounting / FP&A reports from ERP/EPM input data, without the need for time-consuming staff compilation.

For example, GenAI can generate balance sheets, profit & loss (P&L) statements, or cash flow reports in real time from multiple source systems.

Financial forecasting & scenario simulation

Generative models help businesses perform cash flow forecasting, sensitivity analysis, and simulate business scenarios under various conditions (growth, crisis, market volatility).

As a result, CFOs can predict and react faster, using “dynamic” data rather than relying solely on history.

Fraud Detection & Smart Auditing

An interesting application: GenAI can generate simulated data to detect anomalies. If the real data deviates from the generated model, the system alerts the suspicious transaction.

In practice, this solution helps audit teams detect unusual transactions approximately 50% faster than manual methods.

Virtual Financial Assistant (AI Copilot)

GenAI can also play a role AI Copilot for FP&A / accounting:

These applications demonstrate GenAI's ability to turn data into action in finance.

What are the challenges when businesses deploy Generative AI?

Despite its strong potential, AI Gen Deployment There are many obstacles in corporate finance. This section identifies four major challenges and approaches to their mitigation:

Data Governance

If the input data is not clean (missing, wrong, inconsistent), the GenAI model can generate incorrect results, called hallucination.

Therefore, businesses need a strict data management system, input data verification, and output verification before putting it into use.

Security and accounting standards

Financial data is extremely sensitive. When using Gen AI in finance, the risk of information leakage, hacker attacks or misuse increases.

Therefore, organizations must comply with security standards (GDPR, ISO 27001) and accounting standards (IFRS, GAAP) during the process of creating AI content.

Cost and ROI

Investment in GPU/TPU infrastructure, API copyright, and system integration is not small.

The ROI of GenAI depends on businesses having good data, standard processes, and the ability to apply insights. Otherwise, the costs can outweigh the benefits.

Lack of data skills & culture

If the finance/accounting team is not familiar with working with AI, giving good prompts, checking results, then the ability to exploit Gen AI in finance is very limited.

Need training, culture building data-driven decisions bottom up so AI can be effective.

Barriers businesses need to overcome to effectively apply GenAI

Generative AI is ushering in a new era of financial automation and analytics. But in reality, More than 651 TP3T Vietnamese enterprises have not been able to effectively deploy GenAI., the causes come from internal barriers: data, infrastructure, human resources, compliance and strategy.

Problem group Reason Consequences Solution
Data Most of the enterprise data today is scattered in ERP, Excel, CRM or internal accounting systems. Data is not standardization, lack of governance and lack of unified flow. GenAI cannot understand the context properly, leading to misleading content or reporting (phenomenon) AI hallucination). This is especially dangerous in finance, where just one wrong number can affect investment decisions or budget management. Standardize financial data into the same structure.

Apply EPM to consolidate and control all data before entering GenAI.

Set up the process Data Governance and Data Validation.

Infrastructure Vietnamese businesses still rely heavily on old on-premise ERP systems that lack open API connectivity.

At that time, integrating Generative AI or intelligent analytics platforms was almost impossible.

Real-time data extraction is not possible.

Unable to connect to new AI or BI tools.

AI projects stop at “demo” level, cannot be expanded.

Upgrade your ERP or add an EPM middleware layer with 2-way API connectivity.

Platform priority EPM Cloud like Sactona – có thể tích hợp dễ dàng với các hệ thống ERP phổ biến (SAP, Oracle, Bravo…).

Human Resources Traditional accounting and finance departments are often unfamiliar with working with AI models or unstructured data. Don't know how to "train" GenAI with the right data.

It is easy to misunderstand or misuse the results AI generates.

Unable to exploit insights from predictive models.

Skills training AI Literacy for financial staff.

Use a system with a familiar interface like Sactona EPM (Excel-based) makes it easy for the FP&A team to get started.

Build a “hybrid” FP&A team (finance + data) to bridge the gap between humans and AI.

Follow Generative AI can access sensitive data such as profit and loss statements, cash flow forecasts, HR or supplier data. Without a control policy, businesses can violate privacy regulations (GDPR, ISO 27001). Financial data leak.

Risk of being fined or losing brand reputation.

Deploy internal AI (Private GenAI) combined with EPM with access control.

Thiết lập phân quyền người dùng theo vai trò (CFO, FP&A, Controller…).

Maintain regular audits of data systems.

Strategy Many businesses invest in AI as a fad without a clear financial goal: reducing costs, speeding up reporting, or improving ROI. AI projects are deployed sporadically and cannot measure effectiveness.

Cannot scale or sustain long term.

Building an AI strategy that is aligned with Financial KPI specifically.

Connect GenAI to the FP&A (Financial Planning & Analysis) process.

Use EPM as a central platform to measure the performance of each AI model.

EPM – Mảnh ghép nền tảng giúp doanh nghiệp khai thác GenAI an toàn và hiệu quả

Most businesses are experimenting Generative AI all face a major obstacle: fragmented and uncontrolled dataEven the most powerful AI models become useless if their “feed” is unstandardized or biased data.

For GenAI to truly be powerful, businesses need a data-secure platform standardization, hierarchy and tight control – và đó chính là vai trò của EPM (Enterprise Performance Management).

Why does GenAI need EPM as a data platform?

GenAI cannot generate accurate content or forecasts if the input data is fragmented, biased, or without governance standards.

EPM solve this problem completely by:

As a result, EPM becomes trusted data platform that every AI application can “learn” and “understand” the business accurately.

EPM tạo ra “Single Source of Truth” – nguồn dữ liệu duy nhất cho GenAI

One of the core benefits of EPM is the ability to Consolidate data from ERP, accounting, CRM, FP&A, and other operational systems.
Instead of having to extract and process discrete data from multiple sources, EPM helps businesses:

Thanks to that, GenAI can “learn” faster, respond more intelligently, and minimize the risk of generating misleading content (AI hallucination)..

EPM helps businesses deploy GenAI securely and in a controlled manner

Unlike spontaneous GenAI adoption, EPM helps businesses Build a data governance framework and controlled decision-making model.
Specifically:

This is especially important with CFO and FP&A team, khi họ cần vừa tận dụng được sức mạnh AI, vừa đảm bảo tuân thủ quy định tài chính – kế toán.

Giải pháp từ Bizzi.vn: Sactona – EPM giúp doanh nghiệp vận hành GenAI hiệu quả

Sactona is the foundation Enterprise Performance Management (EPM) new generation, Bizzi.vn distribution Exclusive from JapanThis solution is designed to hợp nhất dữ liệu tài chính – kế toán – vận hành into a central system, creating a solid foundation for businesses to deploy AI and GenAI one way safe, effective and sustainable.

Unlike traditional EPM platforms, Sactona bring an approach “Human-centric AI” – tập trung vào việc giúp con người ra quyết định nhanh và chính xác hơn, thay vì chỉ tự động hóa quy trình.

One of the biggest challenges when businesses apply GenAI To be data quality and consistency. Sactona was built primarily to solve this problem:

Detailed success stories with Sactona EPM 

LIXIL Corporation – Triển khai toàn cầu chỉ trong 2 tháng

LIXIL – công ty chuyên sản xuất vật liệu xây dựng & thiết bị vệ sinh – đang mở rộng toàn cầu sau nhiều thương vụ M&A. Trước đó, quản trị tài chính, FP&A vẫn được vận hành chủ yếu bằng Excel: thu thập dữ liệu từ các chi nhánh, tổng hợp thủ công, và đối chiếu giữa các hệ thống kế toán (J-GAAP vs IFRS).

Special requirements

Reasons to choose Sactona

Result

Panasonic – Kết nối toàn cầu, dự báo nhanh hơn

Panasonic – tập đoàn sản xuất điện tử & thiết bị gia dụng – đang vận hành hơn 600 subsidiaries across the globe. They use multiple accounting and management systems, resulting in fragmented data, slow updates, and difficulty consolidating information. Before Sactona, monthly budget updates took seven days; when there was an organizational change, the system had to stop for a month to modify the structure.

Reasons to choose Sactona

Results achieved

Monex Group – Tối ưu hóa quản lý ngân sách và phân tích hiệu suất với Sactona

Monex Group is a company operating in the field of financial transactions and securities services, where Forecasting financial performance according to market fluctuations is mandatory.Before adopting Sactona, Monex Group struggled with budgeting and allocating costs across departments. Manual tools made the process time-consuming, data inflexible, and difficult to react to market fluctuations.

Reasons to choose Sactona

Results achieved

Kết luận: Generative AI không thay thế con người – mà tăng tốc khả năng ra quyết định của doanh nghiệp

Hopefully, through this article you have clearly understood what Generative AI is. Generative AI does not come to replace people, but to expand analytical and decision-making capabilities of financial leaders. When applied properly, GenAI can automate repetitive tasks, Simulate hundreds of business scenarios and provide strategic recommendations based on real data – thứ mà các CFO và FP&A trước đây phải mất hàng tuần mới có thể thực hiện.

However, for Generative AI to truly create value, businesses need a trusted data platform. And that is the role of EPM (Enterprise Performance Management). EPM giúp chuẩn hóa, hợp nhất và kiểm soát toàn bộ dữ liệu tài chính – từ ERP, kế toán đến CRM – tạo nên “single source of truth” for all analysis and decisions.

When Sactona integrated with tools Generative AI, businesses can:

Generative AI is a new step forward, but EPM is the solid foundation help businesses exploit its full power. When these two technologies combine, AI doesn't just "think" smarter – it also helps businesses "act" faster and more accurately.

👉 Learn about Sactona EPM solution now to experience fast, efficient data management, planning and forecasting for your business.

Registration here

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