English 
Preferred Networks, Inc. began offering a derivative model of the large-scale language model (LLM) “PLaMo,” called “PLaMo-fin-base,” which enhances Japanese financial knowledge, to financial institutions. PFN’s financial team will provide total support to financial institutions, from identifying issues, verifying technologies and use cases, to developing and operating applications, in order to improve the accuracy of various processes that require natural language processing technology and increase operational efficiency.
PFNグループは、既存のLLMを一切使わず、事前学習からゼロからPLaMoを開発しました。そこで得たLLM開発のノウハウやモデルを活用し、業務プロセスに適したシステム設計や、特定分野に特化したLLMに必要な追加学習・機能開発を柔軟に行えることが強みです。
PLaMo-fin-base is based on PLaMo, which has world-class Japanese language capabilities, and PFN’s finance team has additionally trained it with a large amount of Japanese language data from the Japanese financial sector, further improving its ability to answer tasks that require domestic financial knowledge. For example, by using PLaMo-fin-base as the LLM at the core of the AI agent, it can be used to streamline and enhance a wide range of operations at banks and securities companies, such as drafting proposals based on sales daily reports, creating investment and loan approval documents, role-playing counter and corporate sales, analyzing companies based on IR information, and summarizing information issued by regulatory authorities.
PLaMo-fin-baseは、金融分野の日本語ベンチマークである「日本語モデル金融評価ハーネス」において高い評価を得ており、証券アナリストや会計士などの金融プロフェッショナルに求められる能力を問うタスクにおいて高いパフォーマンスを発揮しています。 また、社内データやノウハウの活用・連携が可能であり、RAG（Search Augmentation Generation）により、業務日報、研修資料、マニュアル、顧客データベースなどの社内独自ファイルの活用が可能です。また、追加学習により、投資における評価基準など、独自の業務ノウハウをモデル自体に反映させることも可能です。
It is designed for use in financial institutions that require extremely high security standards, and can be used in an on-premise environment where no data is allowed outside the company. PFN’s financial team, which has been highly praised by customers and at academic conferences both in Japan and overseas, will support practical application. In addition, the company has an extensive track record of developing and providing solutions based on cutting-edge machine learning and deep learning technologies, such as parameter tuning through additional learning of LLM.
PFNは、金融分野に特化したLLMの開発を継続し、PCなどのエッジデバイスで動作する軽量モデルの開発や、安全性・性能の向上を目指していると説明。また、これらを活用したAIエージェントの開発も進めており、金融機関向けのLLM活用支援サービスをさらに充実させていくと説明。
日本語