Construction practice of bank intelligent analysis and decision-making platform

Because of the special nature of its industry, financial enterprises , Compared with other industries, the demand for big data analysis will be more urgent , therefore , Major domestic banks and comprehensive financial service institutions have basically established their own data modeling and analysis teams and data report development teams .

However, in recent years, due to the rapid development of the financial Internet , The online comprehensive business of the financial industry is expanding , The amount of data is growing rapidly , A new transformation dilemma has also emerged ：
Owned by financial enterprises Data analysis The team , Although it has its own mature coding tools 、 Deployment system 、 Data index system , Work efficiency always lags behind the speed of business expansion , The front-line business personnel and the data analysis team are all overwhelmed .

Why is the business expanding , The efficiency of the data analysis team is getting lower ？

Here small T So Tempo Experienced users of the product , A large domestic bank as an example .
In the past , All the data analysis work of the bank is in the charge of a professional data analysis team , With the continuous expansion of business scale , The capacity of its data analysis team has gradually reached its limit , The core issues are as follows 2 spot ：
► High technical threshold , Demand pressure is too concentrated
Data analysis, especially AI The technical threshold of modeling and analysis is high , Ordinary people are incompetent , The limited data development and analysis personnel bear the huge work pressure .
► The existing data system of the enterprise is difficult to connect with the outside
The bank set up a professional data analysis team earlier , It has formed its own data indicator system and report review management habit , High demand for personalized data analysis , It is difficult to access the existing agile data analysis and reporting tools on the market , The efficiency of data analysis cannot keep up with the demand for ad hoc data analysis on the business side .
In the past , When business managers face such difficulties , We can only choose to increase the labor cost and expand the size of the data analysis team , However, this is obviously not in line with the original intention of enterprises to realize cost reduction and efficiency increase through digital transformation .
For the core requirements of the bank in the two modules of data modeling and analysis and report making ,Tempo The team designed the construction scheme of the integrated big data analysis platform for the bank ：

AI Analysis upgrade , Lower the threshold , Easy to develop

Create integration AI The ecological system

To release the productivity of the data analysis team , We must find a way to decompose and delegate the daily heavy data analysis work .
Tempo AI Modeling operations with low code reduce AI The threshold of analysis , So that more business personnel can pass the self-service 、 Drag and drop modeling , Independently solve daily business data analysis needs , Deep insight mining of data can be realized in the business line .

introduce Tempo After the platform , The original data analysis team also does not need to change the previous working methods , With the help of Tempo AI rich API Interface ,Tempo The platform can be connected with the feature center that the bank has established 、 Seamless integration of modeling platforms , Create a unified... According to business needs AI ecology , Create an overall AI Algorithm management “AIC platform ”.

From then on, all data analysis and development work within the bank can be carried out in the same platform , Not only the progress is clear at a glance , It can also realize shared results management 、 Modeling application, etc , Let the knowledge assets generated in data development realize precipitation reuse .

BI Report upgrade , Self-help , Easy to share

A flexible and easy-to-use report presentation platform

In the past , Because the bank has an independent data index system , All data reports need to be made by special data report developers , Personalized data viewing needs on the business side are often not met in time .
And based on Tempo BI Developed “B+” Big data analysis platform , You can use the Tempo The opening of API The system realizes seamless integration with the bank's original big data index system , At the same time with the help of Tempo Simple self-service operation , So that more business personnel can explore and analyze business problems by themselves , The purpose of cost reduction and efficiency increase can be achieved without increasing manpower .

Besides , stay B+ In the platform , We can also make reports 、 Look up 、 Manage the platform integration of various functions .
Not only business personnel can flexibly query in the platform 、 Analyze your own customer information data , Discover customer characteristics , Keep abreast of customer trends , Assist in your daily service work 、 Marketing, etc , Leaders can also flexibly subscribe to reports they care about , And check regularly by email , Maximize the efficiency of information sharing .

Enterprise digital transformation , It's a strategy , It is also a practical process , It is inseparable from the understanding of various resources inside and outside the company 、 Participate in , It is the result of the joint efforts of many parties . Therefore, in the process of enterprise digital transformation , We need to pay more attention to the original mature business processes of the enterprise , Build an integrated data analysis platform from a business perspective , Realize the transformation and upgrading of the development direction of the enterprise on the premise of making full use of the original resources and manpower of the enterprise .

Merrill Lynch data has been deeply involved in the field of big data comprehensive services for many years , It has a wealth of enterprises Integrated big data analysis Platform building experience , Help enterprises in various industries with low time cost and human investment , Effectively reduce the threshold of data analysis , Rapid response to business development needs , Realize the summary and integration of data resources , Data assets are used together , With “ Business + Big data value ” Mode realizes the continuous innovation of enterprise business mode , Cultivate their own data core competitiveness ！