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Failure is Fuel: How Seven Bank Turns “Good-to-Have” Ideas into Reality with AI and Data
In today’s data-driven world, utilizing AI and data effectively is no longer a luxury, it’s a necessity. Companies across industries are scrambling to embrace these technologies, with the hope of gaining an edge in an increasingly competitive landscape. Yet, amidst the excitement and promise, a crucial question emerges: how do organizations navigate the inherent uncertainty and complexity of AI and data utilization to actually reap the rewards?
Seven Bank, a key player in Japan's evolving financial landscape, came up with a unique approach – its own elite team of data scientists driving innovation and turning “good-to-have” ideas into reality.
Its successes are numerous. In the Philippines, AI optimized cash management in ATMs, reducing unnecessary labor costs. In Indonesia, AI analysis led to strategic ATM placements, opening up new business avenues. Even seemingly mundane tasks, like classifying call center inquiries or predicting office crowding, were tackled with AI, freeing up employees and boosting efficiency.
This journey began in 2018, fueled by a desire to go beyond their 27,000+ ATMs and 2.75 million individual accounts to enhance efficiency, optimize operations, and ultimately, create better experiences for its customers. But its journey hasn’t been without its bumps and detours.
As Yoshiyuki Nakamura, General Manager, Corporate Transformation Division at Seven Bank, readily admits, many projects didn’t pan out as initially planned. The key, he emphasizes, is not to shy away from these failures, but to learn from them and iterate with agility. This requires a culture of transparency and knowledge sharing.
All processes and results are meticulously documented, ensuring that failures are not siloed but become collective learning opportunities for its agile team of 10 data scientists. Additionally, leadership plays a crucial role in fostering a culture of continuous experimentation and risk-taking, understanding that innovation rarely happens in a linear fashion.
At the same time, they are embedded in the business, working hand-in-hand with departments to unlock the true potential of AI. They're not just building models, they're becoming trusted advisors, translating complex algorithms into real-world solutions that tackle head-on the challenges facing the bank. This collaborative approach is breaking down barriers and driving innovation at every level, proving that the human touch is still the key ingredient in the AI revolution.
Also, recognizing that true transformation goes beyond technology, it’s nurturing a culture of continuous learning with programs like the “Data Science Program”, which teaches business departments the fundamentals of data and AI, fostering a common language and understanding across the organization, as well as the “NEC Academy for DX”, which provides comprehensive training for companies looking to speed up the digital transformation of their workforce.
Yosuke Motohashi, Technology Lead, NEC Generative AI Hub, said, “It is important for management to support digital transformation teams as they lead changes in the organization to optimize resources to maximize profits. Leveraging NEC’s technological strengths, the NEC DX Academy is a one-stop service offering solutions to help the organizations become more efficient and data driven for the digital age and to promote DX or digital transformation culture within the company.
Kosuke Yamamoto, Senior Data Scientist, NEC Data Driven DX Division and Principal Data Scientist, dotData Japan, said, “NEC also provides a human resources development service for business departments that utilizes dotData, DX Human Resources Development Service, and supports the development of human resources with both data analysis and business skills. The main focus of training is an OJT-style program. Using raw data, you will learn data analysis by setting a theme that is tied to your actual work. It is already being used by several MNCs in Japan.”
In addition to NEC’s AI used to identify signs of loan demand, further driving this democratization is the adoption of dotData, which automates the feature discovery process. This allows even non-experts such as employees without programming skills to delve into data analysis and contribute to insights generation, breaking down the walls between data scientists and the rest of the organization.
Seven Bank’s journey is far from over. Its next goal is even more ambitious: building a data business that stands on its own, generating profit through their AI and data expertise. We look forward.
March 15, 2023