Overseas operations governance improvement in banking corporations via Gen AI utilization — A case study on streamlining in operation procedure documentation | Insights

In the overseas expansion of banking corporations, strengthening governance and optimizing operational costs are rapidly gaining importance as management priorities. In particular, integrating localized and branch-specific operation procedures into regional standards is a key decision-making area driven by regulatory compliance, risk management, and talent constraints.
This insight discusses the role that Gen AI can play in enhancing governance of overseas operations and key practical considerations, based on a case study of Gen AI utilization at overseas offices.

About the Author

Tatsuya Oyama

Manager

1. Current state and challenges of overseas operation governance

In the overseas expansion of banking corporations, there is an accelerating movement toward business standardization through the adoption of globally widely used packaged IT systems across core banking operations, including deposits, foreign exchange, and lending. This movement toward system implementation goes beyond mere integration of information technology infrastructure; it is also seen as a significant opportunity to replace operation procedures that have been individually optimized and increasingly complex at each overseas office — based on local business practices and regulatory requirements, leading to discrepancies and inconsistencies between overseas offices—with standardized operation procedures (regional standard operation procedures) shared across multiple overseas offices within the same region.

However, the process of formulating regional standard operation procedures from a system-driven perspective involves highly challenging structural bottlenecks.

High workload for practical operations implementation:
Implementing standard workflows provided by IT system package vendors into concrete and realistic operations in actual banking practice (including exceptional handling, manual processing, and responses to local-specific regulations) requires securing sufficient experts with extensive operational knowledge.
Ensuring consistency with head office regulations:
It is necessary to confirm that the regulations to be followed are properly aligned between the “Head office operation procedures,” which form the foundation of compliance and internal control for the bank, and the newly created regional standard operation procedures. The work of cross-checking vast volumes of procedural regulations and comprehensively verifying compliance and absence of conflicts has limitations when performed manually by humans, and has been a primary factor leading to critical oversights (governance risks) and delays in overall project lead time.

As described above, promoting standardization through system implementation requires addressing two challenges: “high workload for practical operations implementation” and “ensuring consistency with Head office regulations” In the following sections, based on a case in which the incorporation of Gen AI into processes dramatically shortened the lead time for creating regional standard operation procedures, we present a concrete practical approach and the value obtained.

2. Incorporating Gen AI into governance enhancement processes: A practical approach using operation procedures documentation as a case study

The objective of incorporating Gen AI into the process of creating operation procedures in banking corporations is not only to significantly shorten the lead time for creation but also to standardize outputs by unifying variations in level of detail and expression caused by differences in knowledge among personnel. This enables the standardization of operation quality across offices, making it easier for the head office to identify exceptions and deviations between offices, thereby allowing governance management to function effectively.

In addition, the execution of mechanical and comprehensive mapping between operation procedures and head office operation procedures by Gen AI aims not only to reduce the workload of personnel but also to prevent oversight in the linkage work performed by personnel, allowing them to focus on double-checking.

To achieve these objectives, simply providing vague instructions to Gen AI such as “create operation procedure documents” is insufficient; to obtain more expected results, it is necessary to correctly understand the characteristics of Gen AI and conduct advanced prompt engineering (designing instructions for AI).

Specifically, it is effective to have Gen AI thoroughly learn various input materials in advance—such as To-Be workflows upon implementation of target IT systems, operation manuals, and head office operation procedures—and then present “completed sample output (model answers)” created by humans (target business domain experts), using a method known as Few-Shot prompting. This enables Gen AI to learn in advance the required output format, the level of detail required for banking operation procedures, and the context required as a regional standard, making it possible to automatically generate high-accuracy outputs in the desired format and context. This is the key point for achieving efficiency.

The above approach is implemented in accordance with Processes ① and ② below.

Process ①: Regional Standard operation procedures — Automatic generation of 1st draft

In the automatic generation process of operation procedure documents using Gen AI, it is effective to divide the processing into three steps as follows and have the Gen AI learn in stages while distributing the processing load.

Step 1 (Learning input materials): Have the Gen AI ingest and learn, as samples, the To-Be workflow, operation manual, and the head office operation procedures for one product of the target system (for example, L/C issuance operations).
Step 2 (Learning sample output format, expression, and context): Present a “completed sample output (a completed procedure document manually created, for example, a regional standard operation procedures for L/C issuance)” and have the Gen AI learn the target output format, level of detail, and the context specific to banking operation procedures in the form of Few-Shot prompting (learning through examples).
Step 3 (Automatic generation): On the premise that the Gen AI has faithfully learned the input information for L/C issuance operations and the process for creating the sample output from Steps 1 and 2 above, upload the To-Be workflow, operation manual, and relevant sections of the head office operation procedures for another product (for example, L/C Amendment operations), and execute automatic generation of an operation procedure document for L/C amendment while maintaining the same format and context. At this point, each operation process is automatically mapped to the chapters and sections of the head office operation procedures to which it is linked, thereby simultaneously ensuring the traceability of the underlying regulations.

For the creation of a new operation procedure document for a single product as described above, a series of processes that would take from one week to several weeks if performed manually by humans can be executed in just several tens of minutes to automatically generate a 1^st draft with approximately 50% to 70% accuracy through the execution of multiple steps as described above.

<Practical TIPS for overcoming technical and operational barriers>
When utilizing Gen AI in practice as described above, a frequently encountered issue is that as the volume of input prompts and file information increases, the Gen AI’s “attention” becomes dispersed, causing it to lose focus and resulting in a decline in output quality.
As practical tips to address this issue, it is effective to avoid large-scale batch processing in prompts, to minimize and streamline input files so that only key points are learned and analyzed, and to subdivide the process by executing input (learning) and output (generation) processing in multiple stages.
The process of continuously improving prompts through trial and error is the key to ultimately producing better outputs.

Process ②: Final review by experts and deliverables completion

Even if the processing in ① above is executed, the operation procedure document for the target product is not completed with 100% perfect. Ultimately, double-confirmation by humans (experts) and additional revisions are required. This human editing and revision work is expected to take several days, depending on the complexity of the product. Nevertheless, the final outcome is an effective operation procedure document completed by human manually that is easy for readers to understand in practice and that achieves both proper linkage with head office operation procedures and advanced governance.

3. The value of governance enhancement brought by collaboration between Gen AI and humans

As described above, the creation of the 1^st draft of operation procedure documents, which previously required from one week to several weeks, has been significantly shortened in lead time to just several tens of minutes for automated generation processing and several days for additional revisions and edits. In addition, the automatic mapping with head office operation procedures by Gen AI is more accurate and faster than when performed by personnel, and also contributes to minimizing human error. These outcomes should not be viewed merely as operational efficiency improvements, but as enhancements that increase the comprehensiveness of internal controls and elevate the effectiveness of head office governance.

It is important to reiterate the significance of a “completion level of approximately 50% to 70%.” At first glance, it may appear that “manual revisions by personnel are ultimately still required,” but the fact that accuracy can be raised to this level in just several tens of minutes represents a “qualitative turning point.” By having Gen AI replace manual work from a zero base—work that placed excessive burden on personnel—the benefit of releasing personnel from such labor-intensive tasks is substantial.

Furthermore, the greatest benefit lies in enabling personnel to dedicate 100% of their effort and time to the remaining 30% to 50% scope, namely to detailed processing, exception handling, and the refinement of nuanced risk judgments that cannot be fully expressed in To-Be workflows or operation manuals. By having Gen AI take on the generation of standardized “templates,” humans can focus on the intellectual judgment tasks where they should inherently demonstrate their capabilities. This is the essential value of utilizing Gen AI in enhancing governance of overseas operations.

4. Key enablers and future outlook for next-generation overseas governance

This initiative has demonstrated that simply introducing technology is insufficient to leverage Gen AI for the advancement of governance at overseas offices. To ensure effectiveness, it is necessary that the following two conditions are met.

Deep expertise in banking business and overseas operation procedures:
The accuracy of outputs generated by Gen AI is heavily influenced by how well a highly accurate “completed operation procedure document” can be prepared as the initial sample, based on a thorough understanding of exception handling and operation procedures frameworks. It is essential that personnel with deep expertise in banking operations are involved in the creation of this sample.
Capability to integrate Gen AI into actual business operations:
Simply providing vague instructions to Gen AI does not yield the expected outcomes. The ability to clearly envision the deliverables to be automatically generated, to fully understand the necessary input information and steps, and to structure them as a process determines the effectiveness of AI utilization.

These two conditions are required not only for the creation of operation procedure documents as in this initiative but also across a wide range of areas related to governance enhancement, including project management operations, the customer services advancement, and internal audits activities.

Furthermore, the case demonstrated in this initiative is not yet a completed form. With continuous improvement of prompts and the evolution of Gen AI models, further enhancement in the completeness of 1^st drafts is expected. The advancement of governance at overseas offices is a domain that will continue to expand its possibilities in tandem with the evolution of Gen AI.

ABeam Consulting possesses both deep expertise in banking operations and the capability to integrate Gen AI into hands-on operations and supports the advancement of governance at overseas offices, such as in this initiative. If you have an interest in this topic, please feel free to contact us.

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