GEO (Generative Engine Optimization) Optimization Training – Shinhan Savings Bank
Recently, we provided GEO (Generative Engine Optimization) optimization training for internal members of Shinhan Savings Bank.
This training was not an external public lecture, but an internal training held at Shinhan Savings Bank’s in-house training center, with practitioners from marketing, planning, and related departments participating.
Discussions about AI search, generative search, and zero-click environments are already frequently mentioned across the industry, but it is often difficult to apply them directly in the financial sector’s practical environment. This is due to realistic constraints such as security issues, regulatory environments, and internal system structures.
Therefore, this training focused less on technological trends themselves and more on organizing the criteria that practitioners in the financial sector actually need to consider.
Why was GEO training necessary now?
In 2026, the search environment of Naver and Google has not become simpler, but rather more fragmented and complex.
In a situation where Naver, Google, and AI search interpret and expose content based on different criteria, financial practitioners inevitably have to consider what criteria to choose.
This training was not about an approach of ‘unconditionally having to respond,’ but aimed to distinguish how far preparation is realistic.
Key contents of this GEO optimization training.
1. GEO does not replace SEO
While AI search is growing, search traffic still accounts for a large proportion in terms of conversion and sales contribution. Therefore, a strategy that combines GEO with SEO is necessary.
2. Realistic Scope of Application in the Financial Sector
The reason it is difficult to directly apply overseas cases is that security, server structures, and regulatory environments are different. In the training, we explained by distinguishing between actionable areas and reference areas.
3. AI Reads Content Differently
Even if a page is well-made from a human perspective, AI recognizes content based on structure and context. The starting point of GEO is understanding this difference.
4. Areas for Automation vs. Human Responsibility
Repetitive and informational content should be automated, while content requiring judgment and responsibility should be handled by humans. This division of responsibility is the most realistic operational approach.
In Closing…
What was clear through this training was that financial practitioners are in a situation where they need selection criteria more than technology.
Demand for AI Search Exposure Optimization (AEO, GEO) is just beginning to rise, and it is a market where changes are occurring very rapidly due to updates from search engines and AI services.
In a situation where preparation to interpret and respond to changes is more important than a complete solution, this training received high evaluations because it was conducted based on actual cases rather than unverified methods.
If you need training related to GEO (Generative Engine Optimization) and SEO (Search Engine Optimization), please contact Marumo Research Institute, which has the largest number of training cases in Korea.
