The landscape of financial services is rapidly evolving, spurred by advancements in artificial intelligence technologies like DeepSeekAs organizations across various industries race to integrate this technology, the financial sector, including banks, investment funds, insurance companies, and securities firms, is at the forefront of this transformationThis phenomenon has led to intense discussions about the implications of AI in finance, particularly regarding the potential impact on jobs traditionally held by finance professionals or what has been termed “financial laborers.”
Supporters of DeepSeek argue that rather than replacing human workers, AI creates opportunities for existing financial personnel to develop skills that enhance their rolesBy evolving into “AI-enhanced talents,” these professionals can leverage the collaboration between human insight and AI capabilitiesThis shift calls for a blend of expertise in both financial processes and technological applications, expanding career opportunities for those who adapt to the changing environment.
A financial industry professional articulated this sentiment, suggesting that “DeepSeek is not a disruptor; it’s an enabler.” The view that AI will augment human capabilities rather than eliminate them is a prevailing thought among many in the fieldHowever, experts caution that the deployment of AI, particularly in banking which has stringent regulatory and security requirements, may still carry risks.
Experts interviewed express concern over the unpredictable nature of large AI models, stating that while these models like DeepSeek offer potential, their outputs can still be uncontrollable, especially when interacting directly with clientsThe current practice involves these large models generating content that is then reviewed by humans to mitigate risks.
The introduction of DeepSeek’s latest models, V3 and R1, is a significant milestone for AI application within the financial sector
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These models present advantages of low cost, high performance, and openness, making it easier for enterprises to adoptMajor technology companies have quickly adopted DeepSeek, with platforms such as Huawei Cloud, Tencent Cloud, Alibaba Cloud, Baidu Cloud, and JD Cloud incorporating these models.
As more institutions integrate DeepSeek into their operations, the financial industry showcases a plethora of AI use casesFor example, Hai’an Rural Commercial Bank recently showcased its integration with DeepSeek on social media, prompting discussions about the bank's strengths through AI-driven insights.
In a more proactive stance, Jiangsu Bank made headlines by announcing the localization and fine-tuning of DeepSeek’s models within its “Smart Little Su” language model service platformThe bank has successfully employed these models for quality checks on smart contracts and automated valuation reconciliation processesBy adopting DeepSeek’s technology, “Smart Little Su” has improved its efficiency in handling complex tasks and processing multi-modal data.
Industry insiders affirm that the R1 model’s impressive reasoning capabilities allow it to manage intricate financial data and tasks effectively, optimizing various banking functions including customer service, investment guidance, and risk management.
Data provided by Jiangsu Bank highlights the benefits realized from implementing the R1 modelWith automated handling of tasks such as email classification and transaction entry, the bank has achieved over a 90% success rate in accurately processing complex operations, significantly reducing manual workload on a daily basis.
Moreover, those working within state-owned banks emphasize the opportunities presented by DeepSeek’s open-source platformThey anticipate enhancing their operations in intelligent investment guidance, smart customer service, risk monitoring, and compliance management fields following discussions on its technologies.
The enthusiasm for AI is not only present in banking but spans across the asset management sector, where multiple public fund firms have recently deployed various iterations of DeepSeek
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For instance, Huitianfu Fund confirmed the completion of local deployment for DeepSeek models, intending to use them in key areas like investment research and risk management.
Similarly, Nuolan Fund has initiated pilot applications of its “Nuolan AI Assistant,” built on DeepSeek’s framework, aiming to streamline customer service and investment analysis capabilities.
In the insurance sector, China Ping An has been committed to leveraging big data and artificial intelligence, actively exploring the integration of AI technologies with their operations to enhance their transition to a digital platform while expanding their ecosystem in comprehensive finance and healthcare services.
The securities industry is also embracing DeepSeek, with several brokerage firms including Guotai Junan and China Merchants Securities announcing their successful local deployment of the R1 modelGuotai Junan is particularly focused on various applications, from information retrieval to market analysis.
Amid these developments, financial technology companies are also seeking to amplify their offerings through local deployments of large AI modelsRecently, Yizhantong announced their AI solution adaptable for banks, incorporating frameworks like DeepSeek to enhance operational efficiencies.
As financial institutions explore these opportunities, the consensus emerges that local deployment of large AI models may become a standard practice, given the industry’s high data security demandsAnalysts liken this to a foundational shift in how financial firms manage and utilize vast amounts of data for operational advantage.
However, the implementation of DeepSeek is not without challengesSome practitioners note that while DeepSeek models display significant promise, there are instances of inaccurate output causing concernFor example, errors in generating academic content or skewed market analysis could lead to misguided business decisions.
Additionally, the handling of substantial quantities of sensitive data raises alarms regarding privacy and data protection
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