Financial Graph product

As the prototype shows, let's conclude with a summary about the features of the Financial Graph product
About us
The application scope of GraphTech in China's Financial industry is relatively small, and the application level is not high either,
Current Fintech of China's banking industry has two service models.
GraphTech situation in China's Fintech field.
Most other GraphTech based products are created for knowledge expression only, or purely technical tools with weak business fit.
It's inefficient that the scenarios of GraphTech are developed only by technicians, but GraphTech is more relevant to business logic.
Why should business analysts be the primary users of GraphTech?
What kind of Graph product is needed to solve these problems?
We designed the graph model with the UK government's public database called "psc". And what you see now is the schema.
we map the data and complete the data import. The number of nodes and edges after import is shown in the load data module.
The first model in the demo we showed is Absolute_Holding_Model , which for the identification of absolute control in an enterprise group.

Inspiration

It was in the process of undertaking GraphTech based projects in top banks of China for many years that our passion for Financial Graph product was kindled by discovering the core problem of applying graph technology, for we realized that without business understanding and business experience of banking, it is limited and insufficient that GraphTech application scenarios are developed by technology personnel alone, thus a GraphTech product mainly based on business analysis is needed.

The future is a world where data creates value, and everything is connected and high-dimensional data is connected. Therefore, multi-dimensional correlation analysis is the route one must take of data analysis in the future, which is also an important weakness of Fintech in banking.

Compared with traditional relational data analysis, GraphTech is much more effective in multidimensional data analysis, however, which is narrow in the fintech market of China and has less application scope. Due to technicians' lack of understanding and experience of banking business, the development of Graph application scenarios by technical personnel alone is currently limited and inefficient.

Therefore, from the angle of future development trend of interconnection of high-dimensional data, our team resolutely put forward Financial Graph product that relies mainly on business perception and experience for Graph analysis and and mining, aim to the full integration of GraphTech with financial business needs, and thus unleash the infinite potential of GraphTech.

Apart from that, we found that the current status of creating graphs according to a number of independent needs leads to duplication of data and work, therefore, our team realized that this situation could be settled effectively if Graph could be redefined as a knowledge management platform that can integrate all explicit data, can be easily used by business analysts and mine tacit knowledge, and can enable the knowledge created to be shared among different departments, thus forming a virtuous cycle.

What it does

Financial product is a platform for business analysts to explore and mine with multidimensional data based on highly packaged graph technology, also providing a knowledge management system to sort out the achievements of Graph analysis and share with others among the enterprise.

Firstly, unlike other Graph products on the market that are purely based in technical tool calls, our Financial Graph product is totally designed based on financial analysis scenarios, which means that knowledge can be expressed in a form close to business logic, and knowledge integration, storage and sharing can be carried out from the perspective of business need of banking, thus it could be easier to understand and accept.

Secondly, Financial Graph product provides Quick start module that is in order to help users quickly obtain the competence of GraphTech in a short period of time and easily start subsequent graph analysis work. The Quick Start module is the achievement of our team’s years of experience in Graph analysis at top major banks of China, including numbers of commonly used and ready-made financial application scenarios with common labeling systems, and validated models, rules, preset parameters are accessible and can be applied and adjusted by yourself with one click.

Thirdly, knowledge mining with Financial Graph product is totally based on business logic of banking, which embodied in the design of analysis function, highly packaged graph algorithms, and step-by-step application guidelines for numerous segmented scenarios.

Last but not least, Financial Graph product provides a knowledge management system for users to systematically conduct knowledge integration, knowledge inquiry, knowledge mining and knowledge sharing.

How we built it

The Financial Graph product consists of both Graph Analysis and Graph Application Management.

For the first, Graph Analysis is designed for knowledge mining, and users can quickly handle it with common popular scenarios that they are familiar with and a series ready-made rules, models and preset thresholds. Then, the users can make further exploration in the scenario they are interested in. Our team designed six common popular financial scenarios in Graph Analysis, including Enterprise Relationship Graph, Transactions Graph, Products Relationships Graph, Enterprise Marketing Mining, Enterprise Risk Mining, Customized Scenes.

For the other, Graph Application Management is designed for knowledge management, which consists of Labels Management, Models Management, Visualization Management, Tasks Management, Reports Management, API Management. The user can manage and share their analysis achievements as labels, rules, models, and obtain real time feedback from visualization module. The user also can run batch data with the knowledge they created as labels or models in Task Management and output as reports.

Challenges we ran into

The most important challenge in the development of GraphTech in the Fintech of Chinese banking is not a technical problem that is difficult to break through, but find the proper breakthrough point for China's GraphTech in the market. What are the main problems GraphTech faced in China? What is the market and competing products situation? Who should be the main users of GraphTech? What kind of graph product is needed to solve these problems? These are the main issues we were trying to figure out in the design of Financial Graph product.

In the process of product development, a challenge we faced was that there is rare mature GraphTech product that we could refer, especially for business analysts. While, this challenge happens to be our breakthrough and innovation point. The most important feature of Financial graph product is close to the banking business analysis logic, so it's easy to use, rather than obscure and difficult to understand technical tools.

Accomplishments that we're proud of

From the market investigation, we found that it is very important to identify the positioning of GraphTech product in China's Fintech market in terms of users and product features, which is why we have confidence that Financial Graph technology product will receive a rapid and positive response once it introduced into the market.

What's exciting is that we have conducted research for this product with many financial institution clients, and most of them are really interested in this creative product, especially for those institutions that have used other GraphTech products but feel that the results are not good. We have already conducted POC in one of the large banks who plan to project and implement the project.

Now, we have a simple first vision of the product prototype of Financial Graph product, which only shows the part of Enterprises Relationships Graph of Graph analysis, and you will see it in the video. The first vision is not perfect but you can get what the whole thing looks like.