Cathay United Bank - Best New Business or Competitive Intelligence Solution

Company: Cathay United Bank
Company Description: Cathay United Bank was first established in 20 May 1975 and has served its customers for over 42 years. Cathay United Bank currently has 164 branches in Taiwan. Our overseas presence leaves 67 footprints in 11 countries and areas, including 2 subsidiaries, 1 joint venture bank, 6 overseas branches and 5 representative offices.
Nomination Category: Product & Service Categories - Business Technology Solutions
Nomination Sub Category: Business or Competitive Intelligence Solution

Nomination Title: Cathay United Bank - Digital Transformation in Corporate Finance

If this is a brand-new product, state the date on which it was released. If this is a new version of an existing product, state the date on which the update was released:

Corporate Data Model (CDM) was released in November, 2020. And the update was released in February, 2021.

Intelligent Customer Group Labeling was launched in March, 2021.

Public Opinion Analysis Engine was launched in February, 2021.

Customer Dashboard was released in December, 2020.

Cathay United Bank (CUB) launched the industry's first Digital transformation in corporate finance, targeting a corporate digital ecosystem that includes digital infrastructure construction, data mining module development, and data application scenario expansion. These milestones demonstrate how CUB is solving operating pain points with the help of data technologies:

Data infrastructure construction – Corporate Data Model (CDM)

CUB interviewed more than 20 departments to collect, process, and summarize their data and created the model for intuitive use. This project designs the data model from the business perspective that can be conveniently used in application scenarios. The customer-centric database simplifies data analysis, reduces data search time across systems, helping relationship managers (RMs) and product sales (PS) quickly learn about customers' latest status and set product prices accordingly.

Data mining module

Intelligent Customer Group Labeling

CUB replicated the idea of labeling, which is widely used in consumer finance, to the enterprise finance sector. We used data mining technologies to analyze enterprise data, and designed labels in 5 dimensions: basic profile, product potential, risk type, transaction preference, and enterprise owner profile. Compared with standardized products from competitors, products specifically designed for customer groups can better meet customers' needs and make CUB more competitive on the market.

Public Opinion Analysis Engine

In this project, we interview various business departments to replicate their understandings about risks and include them in CUB's unique financial vocabulary. The public opinion engine then extracts keywords about risks and business opportunities, adds values to news from various sources, and analyzes corporate sentiments and market trends, so that business departments can quickly learn about enterprises’ operating status and avoid transactions with high-risk enterprises.

Corporate Finance Connection Network

Apart from the operating status of enterprises themselves, risk events of individuals and companies related to the customer may affect their risk ratings. This project replaces the single-factor evaluation mode with the corporate finance connection network, which integrates organization and transaction connections to reveal risk events of related entities, so that RMs can evaluate corporate risks more comprehensively.

As of 2020, the CDM team has integrated more than 76 information sources (including enterprise information left in CUB systems and imported open information from external sources), designed 50 data tables, and determined more than 13,000 fields for data analysis to make business operations of corporate finance more efficient through digital transformation.

Building the data infrastructure and lay a foundation for the data-driven policy culture

This project abandoned previous troublesome customer development process and extracts data insights from the analytical database. After labeling and grouping similar customers, CUB can invest business resources in potential clients. For example, by looking at the transnational trade volume and transaction records of customers, we can identify industries with trade finance demands (labeled as "industry with trade finance potential") to make customized marketing plans for such customer groups.

Using data technologies to build the public opinion analysis engine and reduce the news exploration cost

Traditionally, RMs spent lots of effort collecting news and visiting enterprises in person to gain a comprehensive picture of the enterprise’s status. This project integrates information from different news sources and removes duplicate information to precisely provide customer-related information. It also analyzes external information of enterprises (for example, Environment, Social Responsibility, and Corporate Governance (ESG), and lawsuits) and internal information (for example, financial statements, and due diligence) to provide a 360° view of the corporate health status. By revealing all-round information, the engine helps RMs evaluate customers and loan conditions for them with cautions, significantly reducing the post-loan management cost.

Building a visualized customer search platform to reduce the information collection cost

In the past, RMs had to go through more than 10 systems to fully learn a corporate customer. Considering each RM serves an average of 30 corporate customers; information collection occupied a huge part of their work time. This project integrates internal and external information and adds values to them through data technologies. Moreover, the project incorporates a great UI and UX design to create user-friendly visualized tool, keeping RMs updated with the latest enterprise status, strengthening their risk awareness, and help them acquire value customers.

To review the full version of supporting materials, please see: https: //cathaybk.tw/5JwURZ46