RawStone’s new-generation mobile billing system provides superior user experience, account analysis and online transaction services. It is able to support different channels (e.g. email, SMS and LINE, etc.) to push-notify billing links and elevate the billing click through rate.

Through data analysis, we can promote personalized content and marketing plans for targeted customers, together augmenting opportunities for cross-selling and up-selling financial products.

1. The innovative mobile billing front desk provides customers with superior user experience, account analysis and online transaction services.
2. Support goals such as ESG sustainable management, energy conservation and carbon reduction. Carbon emissions of personal consumption is reviewed monthly.
3. E-bills are sent at high speed, and the actual measurement at the ground end can reach at least 10,000 bills sent per hour.
4. The event-driven micro-service architecture is adopted. Each service can be rapidly expanded according to the amount of data processed, such as file transfer and delivery, to ensure that the performance is maintained at a set level.
5. Using Java open architecture, it is easy to maintain and expand the system.

RawStone assists financial institutes by providing fast, efficient and compliant digital onboarding journeys upon customer’s application for financial products. According to applicant’s identity and type of account to open, corresponding processes will be dynamically generated and a number of identification methods in compliance with regulations by RawStone will be in place to allow identity authentication.

1. Integrate omni-channels (online, over-the-counter and on-site opening) to promote a fully digitalized account opening process for different channels.
2. Provide a standard and compliant process framework that can be adopted by financial institutes to accelerate the timetable for the launch of financial services.
3. RWD web application development, which can meet the use of various devices of customers.

In addition, it can promptly respond to processing strategy in real time according to the level of the risk detected. In which way, potential exposure from risky transaction by customer from the AML list can be prevented.

1. Flexible list management and configuration – The list combination and the configuration of various business types can be flexibly used for screening purposes according to compliance requirements.
2. Intelligent Matching Algorithm – Supports multi-language exact matching and Chinese and English fuzzy matching. Two sets of different fuzzy matching algorithms are used for Chinese and English to improve the hit rate and reduce the false positive error rate.
3. Self-developed deep learning model – Based on BiLSTM-CRF neural network algorithm, self-developed deep learning model suitable for Chinese address word segmentation tagging.

RawStone has accumulated more than 40 financial customers, providing users with the best application experience. With the OCR recognition for ID cards and identity verification module known as Smart Genie, both the application time and process are significantly shortened.

1. With the RawStone OCR ID-card recognition module, it can accurately identify the customer’s document and retrieve the information, reducing large amount of time traditionally needed for manual input.
2. For the image which meets the given shooting conditions, the identification rate of the ID cards can reach up to 90%.
3. Combined with third-party face recognition technology, face liveness detection and automatic identification of witness comparison are enabled in the process of video verification.

Provide a 360-degree view of customer operations for Banks, Securities and Insurance industries for, plus online account opening and service application with RawStone KYC/AML module. Concurrently it can improve the document reviewing efficiency of financial service personnel, reduce cost of labor and improve user experience.

1. Self-owned RawStone Status Machines, which can establish different internal processes according to various customer needs.
2. Micro-service architecture can be quickly expanded with different functional modules, allowing the need of business and system requirements to be more speedily fulfilled.
3. The data management framework specially designed for Client Lifecycle Management improves the scalability upon adding different successive processes.
4. The customer credit investigation procedure is automated (RPA) to speed up the case review process and reduce the manual review time.
5. Provide automated process monitoring, according to the formulated process SLA. After time needed for each level or for the entire process is determined, issue warning reports will be produced.

Through accurate customer positioning, CDP provides financial institutions with complete data analysis. This allows full understanding of customers’ behavior patterns, creating the best customer experience process and customer life cycle management.

1. Integrate bank internal and external customer data through standard APIs to analyze and optimize marketing activities of financial services.
2. Strengthen the prediction of customer behavior through AI learning models.