Improved customer satisfaction and loyalty
25%Conversion rates grew from 2% to 25%
9%SME short-term product sales rose from 0,9% to 9%
Increased recommendation rate
Earlier, our client had to manually gather analytics. They didn’t have historical data, which could be used to build algorithms for forecasting. The old front system didn’t store the data about accounts but yet it allowed for effective collaboration between the front office and bank’s clients. However, it was not optimized for efficient work. We had to migrate from a Siebel CRM system to Appian.
A new system, based on BPM principles, is more agile and user-friendly. Our objectives were to ensure the smooth flow of business data to a new system, create analytics, reporting, and other modules important for customer’s business processes.
There was a strong need to develop and implement the data marts that will keep historical and real-time information about the client in the data warehouse, develop and implement an interface for aggregating the client’s data about transactions and operations.
We have to incorporate a few systems together for structuring the information during the operational workflow of the bank. All the systems had to work 24×7 taking into account that the online systems were located in different time zones.
We have developed and implemented ETL processes for the transformation and preparation of data marts for the customer data. The final solution has a new interface for collecting historical and real-time data about the customers from different sources, its aggregation and further transfer to the front system of the bank.
Convenient and fast access to information about customers and their accounts by a wide range of bank employees from retail to back-office and risk managers.
Customers have a better experience with receiving real-time information about their interactions with the bank, accessing the information is much faster.
All the customers are divided into groups according to their operations, incomes, and spendings. There’s a history of operations for marketing analysis.
A single data mart is based on online-DWH and offline-DWH. We eliminated time delays for the data updates for global processing through Swift, VISA, and MC.
Due to real-time data monitoring and accurate segmentation, the bank was able to provide more personalized services and offerings, which significantly increased customer satisfaction and loyalty.
Due to better customer service and improvements in banking products offering, the conversion rate grew up to 25%.
By improving customer experience and providing people with individual product offerings, the bank managed to increase sales rate to 9%.
Software solutions bringing business values
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