2. The social behavior of social marketers generates huge data. With the help of social platforms and big data analysis, the financial industry can carry out low-cost social marketing, and promote products and channels with the help of an open Internet platform and a large number of customer demand data. Through the massive data returned by the Internet social platform, we can evaluate the phased results of the marketing plan, adjust the marketing plan in real time, and use word-of-mouth pyramid schemes and viral communication to help the financial industry quickly promote products, brands and channels.
3. How can the data platform achieve accurate marketing, thus increasing customer stickiness? Undoubtedly, it is necessary to have a strong data platform as the backing, relying on big data platform, similar to cloud data, as the fulcrum to guide customers' needs, constantly strengthen the practical application of internet plus, and quickly obtain customers' purchasing desires and needs from big data.
4. Credit Risk Assessment Banks can use big data to increase the latitude of credit risk input, improve the level of credit risk management, and dynamically manage the forms and use risks of enterprises and individual customers. Establishing a credit risk assessment model and method based on big data will improve the financial support of banks for small and medium-sized enterprises and individuals. The establishment of personal credit scoring standards will help banks to take the lead in the coming credit consumption era. The dynamic credit risk management mechanism based on big data will help banks predict the default time of high-risk credit in advance, intervene in time, reduce the default probability and prevent credit fraud.
5. Fraud Risk Management Credit card companies can use big data to predict and discover malicious fraud events in time, even if measures are taken to reduce the risk of credit fraud. Banks can establish an anti-fraud monitoring system based on big data to dynamically manage fraud events in online banking, POS machines, ATMs and other channels. Big data provides multi-latitude monitoring indicators and linkage methods, which can make up for and improve the current anti-fraud monitoring methods. Especially in identifying customer behavior trends, big data has great advantages.
6. Enhance customer experience Banks can provide customized services and greetings to customers entering outlets based on big data analysis, provide customized services to customers on holidays, predict the future capital needs of corporate customers, make appointments in advance, and enhance customer experience. According to the big data analysis report, private banks can help customers invest in financial market products, earn excess profits, form competitive advantages and improve customer experience. Insurance business can provide effective services to customers in advance according to big data forecast, improve customer experience and increase business opportunities. The wealth management business can use large number analysis to quickly launch industry reports and market trend reports to help investors keep abreast of hot spots and improve customer satisfaction.
7. Demand analysis and product innovation Big data provides overall data from which banks can use the overall sample data to filter. Customers can be classified according to their occupation, age, income, residence, hobbies, assets, credit and other aspects, and their needs can be determined according to other data input latitudes to customize products. Banks can also predict the development characteristics of the industry according to the transaction data of enterprises and provide financial products and services for corporate customers.
8. Improve operational efficiency Big data can show the actual income and cost of different product lines and help banks manage products. At the same time, big data provides a comprehensive report for management, revealing the efficiency of internal operation management, which is powerful for improving internal efficiency. Big data can help marketing departments effectively monitor marketing plans and promotion, improve marketing accuracy and reduce marketing expenses. Big data can display a risk view to control credit risk and speed up credit approval. Big data can help the insurance industry to provide insurance solutions to customers quickly, improve efficiency and reduce costs. Wealth management products can also use big data to provide industry reports dynamically and help investors quickly. 9. Decision Support Big data can help financial enterprises to provide data support for upcoming decisions, and at the same time, it can further deduce new decisions based on big data analysis and summary rules. The decision tree model based on big data and artificial intelligence technology will effectively help the financial industry to analyze credit risk and provide strong support for business decision-making. Before the new products or services of the financial industry are put on the market, they can be tested in local areas. Big data technology can accurately analyze the collected data and provide decision support for the marketing of new products through statistical analysis reports.