Over recent years, Business Intelligence has become a major theme for many companies, and the banking sector is no exception.
BI promises to make organizations more agile and responsive, enabling them to seize opportunities and innovate in a strong competitive environment. It also promises to enable organizations to process and exploit large volumes of heterogeneous data more efficiently, offering more precise management at all operational levels –
An “idyllic” situation, but with a few prerequisites. The first of these is a common, unified data approach. Then there is the availability of reliable and easily interpretable data, which is regularly fed and enriched, and usable at all levels: decision-making, transactional, operational, etc. These conditions cannot be met without the help of Business Intelligence.
But how does BI respond to the specific needs of the banking and finance sector? What tangible benefits does it bring? This is what we invite you to discover.
More effective monitoring of financial KPIs
Commercial and financial performance indicators are essential to develop and sustain a company’s activity. Among these are essential financial KPIs, which include changes in sales, working capital requirements and net margin.
Although these indicators are extremely clear, the process of extracting the data required to calculate such indicators is not so clear. It is quite often necessary to juggle between internal and external data, in disparate formats, and to “join” them together. They must also be transformed and shaped so that they are readable and usable.
It is here that a Business Intelligence solution takes on its full meaning, since it is capable of processing raw data to then transform them into practical information. Data visualization also plays a major role, allowing data to be shared in a fun way, with understandable visual representations. It is therefore possible to create a true financial performance dashboard, which is essential for the daily management of an organization.
BI solutions go even further, allowing users to tell stories using data — a process known as data storytelling. So, it is no longer just a case of presenting statistics, but of transforming them into striking and fascinating information.
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An Exemplary Customer Relationship
In the banking sector, BI also means customizing the customer experience. By integrating the different interaction channels available, banks become more connected, offering a continuous customer relationship to ensure greater added value. In fact, the modern-day customer highly appreciates this ability to respond in real time and be available 7 days a week.
They want fast and reliable exchanges, in other words, a bank that is responsive and prepared to listen. This does not mean, however, that the relationship is destined to become fully dematerialized; the dematerialization of day-to-day account management should be used to offer a more human service at key moments, such as when signing up for a loan, among other things.
The creation of data lakes, which enable large quantities of data to be collected, is therefore becoming a priority for companies in the sector. It is with this in mind that Caceis Bank, a Crédit Agricole subsidiary specialized in providing financial services to institutional investors, has developed a secure extranet portal dedicated to its customers.
The aim behind this is to ensure they have a consolidated view of their overall activity in real time.
This major project has significantly improved the customer experience. This required considerable investment in Business Intelligence, which, in turn, necessitated the implementation of a scalable and powerful data visualization tool capable of managing a large number of users. This development was necessary to increase customer satisfaction on a sustainable basis.
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Reports adapted to business requirements
The banking sector is subject to a strict regulatory framework, which imposes special vigilance and transparency in data management. Requirements in this regard include AnaCredit, FRTB, the GDPR, and the BCBS 239 standard. Established by the Basel Committee, the BCBS 239 standard requires banks to collect and store their data, as well as report them to specific regulatory bodies. Changes to accounting standards (IFRS9, IFRS16) should also be taken into account.
In addition, banks must produce regulatory reports, such as the COREP and FINREP. These reports must respect certain prerogatives, as well as specific deadlines, while remaining flexible enough to adapt to new requirements.
All these specificities involve the management of a large volume of data, intervening in many fields. Customers, indicators, market conditions, etc. There are so many data that you need to be able to capture, store and, of course, use.
In this context, Business Intelligence represents a valuable ally when it comes to ensuring data compliance, as well as data traceability. The banking sector must be able to depend on reliable tools that can process a large amount of data quickly, reliably and accurately.
More efficient management of bank branches
If BI can help a bank with the overall management of its performance, it can also help with the day-to-day management of its branches. In fact, the advantage of Business Intelligence is that it “granularizes” data. More specifically, BI allows data to be segmented by geographical area, branch, or even employee.
This ensures a high level of accuracy that greatly facilitates data analysis at the local level. Cash flows, teams and the pressing needs of each branch can be analyzed quickly and independently. It therefore represents a powerful tool in ensuring the good financial health of every bank branch, for example.
By adding predictive analytics to the equation, BI also represents a tremendous asset when it comes to improving branch productivity, since tasks can become increasingly automated. Furthermore, more effective data management increases teams’ availability, who can focus on their core business functions on a daily basis.
Less stressful risk management
The banking sector faces many risks: fraud, credit risks, cyber attacks, etc. But it turns out that Business Intelligence provides an effective defense mechanism against these threats.
For example, BI facilitates the identification of fraud cases, mainly through its ability to quickly process and examine large volumes of data, including unstructured data. By analyzing the history of fraud cases, it is possible to create predictive rules. This allows us to build robust models that can alert organizations in real time, upon detecting suspicious activity.
BI also represents a valuable ally with regard to credit risks. Data mining can be used to determine a person’s ability to repay a loan. By cross-referencing various data sources, it is possible to assign each loan applicant a highly reliable credit score. This typically long and laborious evaluation process almost becomes immediate thanks to BI.
The banking sector is undoubtedly one of the largest “data producers,” hence the need for a tool to collect, manage and, more importantly, harness this tremendous data potential. From monitoring financial KPIs to producing regulatory reports, including risk and branch management, Business Intelligence has many assets. BI now promises a brighter future for players in the banking and finance sectors than at any time before.