AI projects in hours instead of months – How a global financial services provider from Japan automates compliance without its own AI experts

The strategic partnership between a leading Japanese financial group and Unframe AI: A groundbreaking success story in enterprise AI implementation

A leading financial group in digital transformation

A leading global financial services provider from Japan, one of the country's most prestigious financial services groups, looks back on a nearly 100-year history. The company has grown into a global player operating in over 30 countries. It offers a wide range of financial services, including wealth management, investment banking, bond, equity, and derivatives trading, and asset management. The company serves individuals, corporations, institutions, and governments and is particularly active in securities trading and investment banking.

As one of Asia's largest investment banks, the group faces the challenge of combining traditional financial services with the demands of digital transformation. The company has recognized that artificial intelligence is a key factor for future competitive advantage in the financial sector. The company's digitalization strategy is based on three key pillars: providing innovative digital services, expanding into digital assets, and unlocking new business opportunities through advanced technologies.

The challenge for the financial services provider lay in the need to implement complex AI use cases quickly and efficiently while meeting the financial industry's strict compliance requirements and security standards. Traditional AI implementations often required months of development time, significant investments in specialized teams, and complicated integrations into existing systems. These hurdles slowed innovation and made it difficult to remain competitive.

Unframe AI: The revolution of enterprise AI platforms

Unframe AI, founded by Shay Levi, Larissa Schneider, and Adi Azarya, represents a paradigmatic shift in the way companies implement and use artificial intelligence. The company was born out of the realization that previous approaches to enterprise AI were too complex, time-consuming, and costly. CEO Shay Levi brings impressive expertise, having previously co-founded Noname Security, a company that grew to $40 million in annual recurring revenue within four years and was acquired by Akamai for $500 million.

Unframe AI's core concept is based on the Blueprint approach, an innovative methodology that enables complex AI use cases to be transformed into functional business solutions in hours instead of months. This approach eliminates the typical obstacles to AI implementations: long development times, high costs, and complex integrations. The platform is designed as a complete turnkey solution, enabling companies to develop customized AI solutions without having to build extensive in-house AI expertise.

Unframe AI's technical architecture is designed to integrate with any SaaS application, API, database, and file system, while ensuring that sensitive corporate data never leaves the secure confines of the client environment. The platform is LLM-agnostic, meaning companies can choose or switch between various major language models without being tied to a specific vendor. This flexibility is especially important in a fast-moving technology landscape where new and improved models appear regularly.

The innovative Blueprint approach in practice

Unframe AI's blueprint approach represents a fundamental innovation in enterprise AI implementation. Instead of forcing companies to train or optimize their own large language models, Unframe provides contextual blueprints that provide AI models with the necessary domain-specific knowledge. These blueprints contain structured information about business processes, industry specifics, and corporate policies, enabling the AI ​​models to deliver precise and relevant results.

The process typically begins with a detailed analysis of the company's specific requirements and use cases. The Unframeteam works closely with clients to understand their unique challenges and goals. Based on these insights, customized blueprints are developed that serve as a knowledge base for the AI ​​agents. These blueprints can transform unstructured data such as PDFs, emails, and Excel files into usable, structured information, automating manual input and processing processes.

A key advantage of this approach is the speed of implementation. While traditional AI projects can often take six to twelve months or even longer, the blueprint approach enables the delivery of functional solutions within hours or a few days. This speed is achieved through the pre-built components and proven methods embedded in the blueprints.

The system's flexibility is also reflected in its ability to support various types of AI use cases. From document processing and compliance checking to customer service automation and data analytics, the platform can be adapted to virtually any business area, taking into account the specific requirements and workflows of each area and optimizing them accordingly.

The strategic partnership: A financial group meets Unframe AI

The collaboration between the Japanese financial group and Unframe AI began as a strategic initiative to modernize operational efficiency and unlock new business opportunities through artificial intelligence. The CIO of the wholesale business recognized the potential of the Unframeplatform and its unique approach to AI implementation. The decision to choose Unframe AI was based on several critical factors that are crucial for a global financial services company of this size.

Initially, Unframe AI's security architecture was a decisive factor. The financial industry is subject to strict regulatory requirements regarding data protection and compliance. Unframe AI was able to guarantee that all sensitive customer data and business information would remain within the company's secure IT environment, without the need for external access or data transfer to third parties. This guarantee was fundamental to the solution's acceptance by the institution's compliance and risk management departments.

The speed of implementation was another key advantage. The financial services provider operates in a highly competitive market environment where the rapid adoption of new technologies can provide a significant competitive advantage. Unframe AI's ability to deliver functional AI solutions in a fraction of the time required by traditional approaches enabled the company to accelerate its digitalization strategy and respond more quickly to market changes.

The platform's flexibility and scalability were also crucial. As a global company with diverse business units, the group needed a solution that could adapt to different requirements and scale with the company's growth. Unframe AI's blueprint approach made it possible to cover various use cases, from automating compliance processes to improving customer service efficiency.

Concrete use cases and implementation successes

The implementation of Unframe AI at the financial group encompassed several strategic application areas, each designed to address specific business challenges and achieve measurable improvements. A key focus was on automating and optimizing compliance processes, which are critical in the financial industry.

In the area of ​​document processing and compliance review, the company implemented AI-powered systems that can automatically analyze large volumes of contracts, regulatory documents, and internal policies. These systems can identify potential compliance violations, conduct risk assessments, and generate recommendations for necessary actions. The automation of these processes not only significantly reduced processing time but also improved the accuracy and consistency of compliance checks.

Another significant application area was the optimization of customer service processes. By integrating AI-powered chatbots and intelligent assistants, the financial services provider was able to increase the efficiency of customer support while improving the quality of customer interactions. These systems can understand complex customer inquiries, retrieve relevant information from extensive knowledge databases, and generate personalized responses that meet each customer's specific needs.

Data analytics and business intelligence represented a third key implementation area. The institute leveraged Unframe's AI capabilities to analyze unstructured data from various sources and gain valuable insights. These analyses support strategic decision-making processes, identify new business opportunities, and improve risk management through more accurate predictive models.

The implementation was carried out in close collaboration between the financial group's teams and Unframe AI. Particular emphasis was placed on change management and employee training to ensure the effective use of the new AI tools. User acceptance was high, as the systems were intuitive to use and enabled immediate productivity gains.

Measurable business results and ROI

The partnership between the financial group and Unframe AI resulted in impressive and measurable business results, clearly demonstrating the effectiveness of the implemented AI solutions. The successes can be divided into several categories, each reflecting specific aspects of business improvement.

The company achieved significant improvements in operational efficiency. The automation of routine compliance tasks led to a reduction in processing times of up to 70 percent. Complex document reviews that previously took several days can now be completed within a few hours. This time savings enabled compliance teams to focus on more strategic and value-added activities.

The accuracy of compliance audits also improved significantly. Consistent application of AI-powered analytics minimized human errors and increased the detection rate of potential compliance violations by over 40 percent. This improvement is particularly valuable in an industry where compliance violations can result in significant financial penalties and reputational damage.

In customer service, the implementation of AI-powered solutions led to a significant increase in customer satisfaction. Response times for customer inquiries were reduced by an average of 60 percent, while the quality and precision of responses improved. Customers now have 24/7 access to intelligent assistants that can answer complex financial questions and provide personalized recommendations.

The cost savings from the AI ​​implementation were also substantial. The financial services provider was able to reduce operating costs in the implemented areas by an estimated 25 to 35 percent. These savings resulted from the automation of manual processes, the reduction of errors, and improved resource allocation. The investment in the Unframeplatform paid for itself within the first year of implementation.

Furthermore, AI integration enabled new business opportunities and revenue streams. Improved data analytics enabled the company to identify new market trends, better understand customer behavior, and develop customized financial products. These data-driven insights led to an increase in cross-selling rates of approximately 20 percent and the development of innovative services that tap into new customer segments.

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Technological integration and security aspects

The technical integration of Unframe AI into the financial group's existing IT infrastructure represented a complex and critical aspect of the partnership. The company operates a highly secure and regulated IT environment that must meet the most stringent security standards and compliance requirements. The seamless integration of the AI ​​platform into this environment required careful planning and implementation.

A key advantage of Unframe AI is its architecture, which requires no data transfer outside of the client's systems. All AI processing takes place within the financial services provider's secure IT environment, ensuring that sensitive client data and business information remain fully protected. This feature was crucial for the solution's acceptance by the company's security and compliance teams.

The platform utilizes advanced encryption technologies and security protocols that meet the highest industry standards. All data transfers between different system components are end-to-end encrypted, and access to AI functions is protected by multi-level authentication and authorization mechanisms. These security measures ensure that only authorized users have access to specific AI capabilities.

The integration was carried out via standardized APIs, enabling flexible connection to various existing systems. The financial group was able to gradually introduce the AI ​​functions into various business areas without having to make disruptive changes to critical production systems. This approach minimized risks and enabled a controlled rollout with continuous monitoring and optimization.

The solution's scalability proved to be another key advantage. The platform can automatically scale with increasing workloads and adapt to changing requirements. This is especially important for a global financial services company like this, which has to handle large volumes of transactions and data processing every day.

Challenges and solutions

Despite the impressive successes, the implementation of AI solutions at the financial services provider was not without challenges. These obstacles and the solutions developed offer valuable insights for other companies planning similar digitalization projects.

One of the biggest challenges was the change management component of the project. The introduction of AI technologies required employees to adapt their workflows and mindsets. Many team members initially had concerns about the impact on their jobs and the complexity of new technologies. The company and Unframe AI developed a comprehensive training and communications program that highlighted the benefits of AI integration and supported employees in developing new skills.

The regulatory requirements of the financial industry posed another complex challenge. Every AI implementation had to not only function technically but also meet strict compliance standards. This required close collaboration between the technical teams, compliance departments, and external regulators. Unframe AI had to develop detailed documentation and attestation procedures to ensure the transparency and traceability of all AI decisions.

Integration with legacy systems proved to be technically challenging. The financial group operates various older systems that were developed over years and support critical business functions. The challenge was to connect modern AI capabilities with these existing systems without compromising their stability or performance. Unframe AI developed special adapters and middleware solutions that acted as bridges between the different system generations.

Data quality and standardization also posed a challenge. AI systems are only as good as the data they work with. The company had to make significant efforts to cleanse, standardize, and harmonize data sources. This required the development of data governance processes and the implementation of data quality monitoring systems.

Scaling and global expansion

The success of the initial implementation at the Japanese financial group led to ambitious plans for scaling and global expansion of the AI ​​solutions. This expansion brings with it both opportunities and new challenges that require strategic thinking and careful planning.

The geographical expansion of AI solutions to various markets in which the financial services provider operates requires consideration of local regulations, languages, and business practices. Unframe AI proved particularly valuable in addressing this challenge, as its blueprint architecture allows for the rapid creation of localized versions of AI solutions. The platform can handle different languages ​​and adapt to local compliance requirements without the need for extensive redevelopment.

The functional expansion includes extending AI applications to additional business areas within the group. Following successful implementations in compliance and customer service, the company plans to introduce AI solutions in areas such as risk management, portfolio optimization, and market analysis. Each new application area requires specific adaptations and optimizations, which are made possible by Unframe AI's flexible approach.

Organizational scaling involves building internal capabilities and developing AI expertise within the organization. The company is investing in training programs and recruiting specialists with AI backgrounds to become more independent in the long term and drive its own innovations. At the same time, the strategic partnership with Unframe AI will continue to ensure access to the latest technologies and methods.

Technical scaling involves expanding the IT infrastructure to support larger workloads and more complex use cases. This requires investments in hardware, cloud services, and network capacity. Unframe AI's modular architecture facilitates these expansions, as new components can be seamlessly integrated into the existing infrastructure.

Industry-wide impacts and market reactions

The success of the partnership between the financial group and Unframe AI has garnered industry-wide attention and prompted other financial service providers to rethink their own AI strategies. This development demonstrates how innovative technology implementations can transform market conditions and create new competitive dynamics.

The company's competitors have begun launching similar AI initiatives to keep pace. This response is reinforcing the trend toward digitalization in the financial industry and accelerating the development of innovative financial products and services. At the same time, new challenges regarding differentiation are emerging as AI technologies become increasingly standardized.

Regulators have also responded to the increasing use of AI in financial services. New guidelines and standards are being developed to ensure that AI systems are transparent, fair, and accountable. The financial services provider benefits from its early implementation, as it has already gained experience with compliance requirements for AI systems and can provide advice on the development of new standards.

Technology providers have observed Unframe AI's success and are developing their own solutions for the enterprise AI market. This is leading to increased competition, but also faster innovation and better solutions for end customers. The market for enterprise AI platforms is growing rapidly, and companies like Unframe AI must continuously innovate to maintain their market position.

The investor community has also responded positively to the company's successes. Unframe AI closed a $50 million funding round, reflecting confidence in its business model and growth prospects. These investments will enable the company to intensify its research and development activities and accelerate its global expansion.

Future prospects and strategic developments

The partnership between the Japanese financial group and Unframe AI is still in its early stages, and both companies have ambitious plans for the future. These prospects include technological innovations, new application areas, and strategic expansions that have the potential to further transform the financial services industry.

In terms of technological advancements, both companies are working on integrating the latest AI technologies, including advanced machine learning techniques and multimodal AI systems. These developments make it possible to address even more complex use cases and further improve the accuracy and efficiency of existing solutions. Of particular interest are developments in the explainability of AI decisions, which are critical for regulated industries such as the financial industry.

The expansion into new application areas includes the development of AI solutions for areas such as algorithmic trading, credit risk assessment, and personalized financial advice. These applications require highly specialized algorithms and in-depth industry knowledge, but also offer significant potential for competitive advantages and new revenue streams. The company plans to further expand its position as an innovation leader in the application of AI in finance.

The strategic expansion encompasses both geographical and sectoral expansion. The financial group is considering applying the developed AI solutions in other business areas and markets. At the same time, Unframe AI is exploring opportunities to expand into other industries with similar requirements for enterprise AI solutions. This diversification can reduce risks and create new growth opportunities.

The partnership also plans to develop industry-specific AI standards and best practices. By collaborating with regulators, industry associations, and other stakeholders, both companies can contribute to the creation of a responsible and sustainable AI ecosystem. This leadership can create long-term competitive advantages and strengthen market positions.

Lessons learned and best practices

Unframe AI's successful implementation of AI solutions at the global financial services provider provides valuable insights and best practices that can help other companies with similar digitalization projects. These experiences are particularly valuable because they come from a real, large-scale enterprise context.

One of the most important findings concerns the importance of executive sponsorship and organizational commitment. The success of the project was largely due to the financial group's senior management fully supporting the initiative and providing the necessary resources. Without this strong commitment, many of the challenges encountered would not have been successfully overcome.

The importance of a phased implementation approach proved to be a critical success factor. Instead of attempting to implement all AI solutions at once, the company focused on specific use cases with high value creation potential. This approach enabled them to achieve success quickly, realize learning effects, and build confidence in the technology.

Close collaboration between internal teams and external technology providers proved crucial. The combination of the financial services provider's deep industry knowledge and Unframe AI's technical expertise enabled the development of customized solutions that optimally address specific business requirements. This partnership mentality was more important than traditional client-vendor relationships.

The investment in change management and employee training paid off significantly. Early end-user involvement in the development process and comprehensive training programs led to high user acceptance and effective use of the new AI tools. These investments in the human side of digital transformation were just as important as the technical implementations.

The importance of robust governance and compliance processes cannot be overstated. Establishing clear guidelines for handling AI systems, data management, and risk assessment from the outset has enabled companies to meet regulatory requirements and build trust with stakeholders. These processes must be continuously refined as both technology and regulatory requirements are constantly evolving.

The measurability of success and continuous optimization proved essential for the long-term sustainability of the initiative. By establishing clear KPIs and conducting regular evaluations, potential for improvement could be identified and implemented. This data-driven approach to AI implementation enables continuous value creation and adaptation to changing business requirements.

The partnership between the leading financial services provider and Unframe AI represents a groundbreaking case for the successful implementation of enterprise AI solutions. The combination of innovative technology, strategic planning, and excellent execution has created a model that can serve as inspiration and guidance for other companies. The successes achieved demonstrate the transformative potential of AI technologies when properly implemented and managed.

Global financial services provider deploys a managed enterprise AI platform: Long project times minimized – 70% faster, 40% more accurate – Image: Xpert.Digital

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• Global financial services provider deploys a managed enterprise AI platform: Long project times minimized – 70% faster, 40% more accurate

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