The financial industry knows full well the value of getting to know its customers better. Innovating with customized products is, more and more, a matter of survival in the fierce competition with which banks and insurance companies live, whose main input is information. However, an innovative way to capture this data in an automated and secure way is while using Web Scraping for Banking and Insurance companies. In this post, we will explore its main opportunities and benefits.
Changing a paradigm in the way of developing the business is not easy but it opens a window of unimaginable opportunities. To automate the extraction of information, there is Web Data Extraction, also called Web Scraping. Combining technology and specialized knowledge, companies turn to these solutions to exponentially expand their ability to access any website and extract valuable data on a massive, orderly, and quality scale.
A business sector that is beginning to take great advantage of Web Scraping is that of banks and insurance companies: credit risk departments, insurance risk assessment, sales, operations, and marketing go out of their way to find ways to be more efficient in the analysis of the preferences, history of actions, consumption, and ability to pay off your current and potential customers.
However, solving data access and processing internally and with the highest efficiency requires specialized knowledge that takes time and resources from software development or IT departments.
Banks turn to Web Scraping to solve their needs to capture information in an automated way, improving knowledge of their customers’ preferences and consumption patterns without major restructuring of their processes.
Regulations of Web Scraping for Banking and the financial field
There are more formal than substantive reasons that have generated transitory minorities, who have resisted advanced Web Scraping, but those same groups and communities have ended up understanding that it is positive.
This was the case in the Australian Senate investigation, which concluded that there is no evidence that the services provided using Web Scraping represent an additional risk. In this sense, the instance sentenced recommendation number 22 of the Committee for Financial Technology and Technological Regulation of Australia, with which it rejected the idea proposed by bank representatives who sought to prohibit advanced Web Scraping.
In Europe, the issue was also debated: the PSD2 standard established the obligation to implement APIs and banks asked that Web Scraping be prohibited because it seemed unnecessary.
However, after a long discussion, it was finally concluded that it is better to keep it as an option. The central reasons are: A) Complete the offer of data and services; B) Alternative mechanism for contingencies of the APIs and C) An alternative to the APIs allows better agreements.
By putting the latest PSD2 (Revised Payment Services Directive) regulations in place, banks were allowed to connect with third-party providers (TPPs) through standardized and secure APIs. So Web Scraping was pretty much the only way the Open Banking movement could develop.
Unfortunately, those APIs were limited in scope: they only allowed the secure exchange of checking account data. Of course, that makes a lot of sense for most Open Banking related needs. But understanding the full financial picture of a person or business requires much more than just checking account details. This is why web scraping is very much an essential tactic in moving the world toward a future of open finance and eventually open data.
Web scraping for Open Finance is more or less a way for users, be they individuals or businesses, to give their consent to TPPs, such as payment service providers like Powens, to be able to access a variety of useful financial data. This data can include anything from checking account transactions to details of savings and investments in a wealth management portfolio.
To access this data, the user must share their financial account login details with a TPP, who then “logs in” to the account, with the user’s explicit permission, to “scratch” their data. By having access to this data, companies can provide their customers with better user experiences or more personalized products, services, and offers. For example, many financial service providers or insurance companies may want to see this data before making credit decisions, terminating insurance policies, processing instant payments, etc.
Web Scraping for Insurance Data
Web scraping of insurance data can reveal a great deal of information about the insurance market. It is one of the most data-rich industries in the world.
This data is used by businesses and organizations in a variety of ways, from understanding consumer behavior to predicting future trends in the industry.
Currently, there are several reasons to implement Web Scraping in the insurance industry. The first reason is to get an idea of how the market is behaving in general. Another reason is to examine the performance of the different types of insurance policies on the market. Finally, executives may want to analyze insurance data to see how premiums and other factors vary by location, evaluate a customer’s credit score to assign different types of insurance, or simply perform a general risk analysis according to current customer behavior.
Main Benefits for Banking and Insurance
The main benefits and opportunities observed in the field of fintech, banking, and insurance companies are related to:
- Analyze the competition: through Web Scraping it is possible to evaluate, for example, the efficiency of marketing campaigns, guidelines in social networks, and advertising messages, detecting how they impact users.
- Sentiment analysis: users’ “moods” can be extracted before publications are made, and services or products launched. In this way, Web Scraping makes it possible to find out if the campaigns launched by a bank or company that sells insurance are positive or negative and, thus, apply the appropriate corrective policies.
- Market research: Opens the knowledge of consumption habits, needs, and preferences of customers and prospects. It also allows understanding aspects to be reinforced in marketing campaigns and detecting new market niches.
- Data Enrichment: Allows the generation of products, notes, and documents from different media to centralize the information for later consultation or use.
The main sectors of companies that fully benefit from these optimal automated data extraction solutions are:
- Sales: The combination of demographic information with data on consumption, habits, and product preferences allows for customizing the commercial proposal. For example, personal loans or credits can be offered to clients detected to make large purchases (real estate, cars), while those with travel plans can receive international credit cards or travel assistance insurance.
- Marketing: Through data extraction, the impact of a product or service launched can be known based on the opinions and feelings transmitted by users. In the same way, it is possible to predict the success of a campaign, relieving the expectations and needs of customers.
- Product: A Web Scraping project can offer information systems that group disorganized data in multiple sites, making it easier to consult them.
Why choose Scraping Pros?
At Scraping Pros we have extensive experience in developing solutions adapted to the needs of Banking and Insurance. We are leaders in providing Web Scraping services for large-scale information requirements.
With our flexible Web Scraping service, you can feed your business with audited and integrated data from different websites, relying on Scraping Pros’ complete data extraction and web data integration solutions. We adhere to all ethical and legal standards for our automated data extraction practices.