JapanFinance and insurance2019 – ongoingSumitomo Mitsui Trust Bank
Machine learning for retail financial-product campaign targeting
Sumitomo Mitsui Trust Bank reported higher conversion rates after using machine learning in retail campaigns
Problem
The bank wanted to understand customer needs more accurately using its accumulated data. Retail campaign planning required identifying suitable audiences for financial products.
Approach
The bank introduced dotData software in 2019. The platform automated feature extraction and machine-learning model construction. Staff used it when planning campaigns for term deposits and investment trusts.
Results
No published figures
Takeaway
Machine learning became part of campaign planning for existing products. The bank reported higher conversion rates without quantifying the gain in its investment announcement.
Categories
- Size
- Large enterprise
- Industry
- Finance and insurance
- Business function
- Marketing and sales
- Innovation type
- Process innovation
- Adoption
- Off-the-shelf tool or platform
- Evidence
- Company's own claim
Sources
Source summaries
The bank confirmed introducing dotData in 2019 and using it in retail campaigns. It reported improved conversion rates and announced an investment to deepen the partnership.
Full details are in the original sources.
