Data Analytics Financial Services – The banking, financial services and insurance (BFSI) industry is the most vulnerable sector due to its dependence on global trends, changing regulations and diverse consumer demographics.
Customer satisfaction is a very important parameter for any industry and even more so in the case of BFSI. Customers share all their details with the bank/insurance provider, which has mutual implications;
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Second, their customers feel that their service providers are obligated to inform them, and thus customer satisfaction is very low.
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Industry-leading organizations are using data and analytics to redefine the playing field. They enrich their customer information by collecting new information from telecommunication service providers, retailers and social media. With this 360-degree view of the customer, they can drive revenue, reduce risk and control costs.
Banks require significant investment in staff to run their day-to-day operations. Implementing ways to improve operational efficiency can significantly reduce profits. An analytical system can provide the following benefits to the bank:
Revenue and revenue analysis helps banks reduce ongoing costs by analyzing operational processes. Understanding customer-relevant sales patterns can increase repeatability. Sales is a very strategic function and there are Business Intelligence (BI) tools that can help establish metrics such as net new customers and identify profitable segments from existing customers.
Sales Performance Analytics provides a comprehensive report on employee performance. It can provide insights to identify performance bottlenecks for all customer-facing employees, such as salespeople, account managers and cashiers, to uncover ways to improve the customer experience. This analysis can be extended to any new financial product or service to determine its profitability and make any strategic adjustments in line with the organization’s long-term goals.
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Analyzing online and in-branch sales can help banks create an optimal sales strategy. Customers now interact with their bank through multiple channels. Their journey through them is extremely complex: they often start in one channel, take intermediate steps in another, and end in another. Bankers can leverage this to provide a truly seamless omnichannel experience by capturing real-time data and using analytics to understand the buyer’s journey. It also helps them track their competition.
Banks can proactively collect data on customer transactions to recommend products or services that are right for them. This leads to better conversion rates and customer satisfaction. Banks can use BI tools to analyze the following group of information related to customers:
Banks can analyze transactional activity such as information about deposits, withdrawals or payments for existing customers. It helps bankers to understand the spending patterns of customers and offer attractive offers on their credit/debit card or some new financial product. This analytics can be used to provide timely spend notifications and upcoming payment reminders to improve the customer experience.
The banking transactions and inquiries of these customers can provide detailed information about their mortgage and credit requirements. If they are offered the right benefits and access them at the right time, the result can be a dramatic increase in conversions.
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By monitoring customer transaction history and identifying patterns, banks can detect fraudulent transactions and take measures to avoid such incidents. Top banks use analytics-enabled techniques such as digital credit scoring, advanced early warning systems, next-generation stress testing and credit collection analytics to protect their customers from fraud.
Increasing customer information provides banks with an opportunity to reduce risk or take preventative measures whenever possible. BI systems can provide early indications of these potential risks and help mitigate them:
Credit risk and customer credit risk analysis can provide detailed information about customers with a number of outstanding payments. Credit profiles of these customers to highlight their assets and customer behavior information such as outstanding payments, any payments, income, etc. can be used to generate an individual customer’s credit score.
Market and portfolio analysis is very important for acquiring new customers and keeping existing ones. An analytics system can help portfolio managers maintain consistent returns and recommend investment opportunities to clients based on their existing portfolios. Again, market analysis is key to creating a portfolio that thrives even in turbulent economic conditions.
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Operational and liquidity risks: Every banking process can be made faster and more efficient. Among other things, banks can use advanced analytics to provide faster and more accurate responses to regulatory requirements and provide advanced decision support teams with analytics.
Banks are faced with very strict regulatory and compliance requirements. This has a lot to do with the extent of downside risk they are exposed to. Analyzing your customer data (KYC) is critical to meeting regulatory requirements as well as a way to mitigate risk. These BI tools help anti-money laundering (AML) analysts effectively identify and monitor all suspicious account holders.
Like any other business, finance is at the heart of any business. In the case of banks, this has an even greater impact, because in addition to managing the day-to-day operations of the bank, it also has to take care of the financial requirements of its customers. Analytical systems can find the following use cases in banking finance:
Banks need to maintain their own solvency in order to effectively manage their clients. Analyzing past cost requirements enables decision makers to develop a clear set of factors, critical success factors, turning short-term cost reductions into long-term, sustainable changes and ideal cost management.
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BI systems can eliminate complexities associated with financial reporting and management. These systems can significantly reduce the effort required for financial reporting by automatically generating periodic key statements. They also help spread information more quickly and keep decision makers interested in the financial health of the bank.
Profit and loss analysis by line of business (LOB) allows decision makers to determine how a particular line of business is performing profitably. Based on this information, the relevant banking authorities can plan their short-term and long-term goals.
Since the process of digitalization of the bank, the process of IT support and back office has played an important role in the operation of the bank. Whether banks have these processes in-house or outsource them, testing these processes is essential to maintaining an excellent end-consumer experience. BI tools can help banks in the following ways:
Analytics in banking and financial services can help effectively manage IT systems and service level agreements (SLAs). These systems provide stakeholders with all metrics related to workforce performance. This information helps decision makers evaluate supplier performance and avoid unnecessary costs.
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By using BI tools to predict the amount of cash needed at each of their ATMs across the country and combined with route optimization techniques, banks can achieve ATM efficiencies.
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Sometimes you need to approach existing customers differently. Banks need to present new and optimized product portfolios to existing customers and this information will reach them at the right time. Analysis of existing customers shows that the best strategies have worked in the past and the same can be applied to new customers. The BI system can be used
Deeper and more detailed customer profiles, along with transactional and transactional analytics, can improve customer acquisition and retention, as well as cross-selling and up-selling.
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Another important use case for an analytics system is customer portfolio analysis and segmentation. To sell to customers, you need to segment them properly. Customer segmentation for financial services companies looks like customers are applying for a home loan or other auto loan, it could be a specific bank account such as a checking or money market account. A relevant offer or call from a customer relationship manager can lead to a successful conversion. Similarly, the audience list for launching any new offers can be narrowed down based on the customer’s credit score.
Analyzing marketing campaigns provides insight into the types of channels that work for the bank and optimizes spend across those channels. Top banks use information from credit card transaction data (both from their own terminals and from other banks’ terminals) to create incentives that encourage customers to make frequent purchases at the bank’s card-accepting locations. in the banking and financial services sector even before the pandemic. With open banking, fintech and other financial services companies growing at breakneck speed as more and more people access and create customer data, making good use of that data means the difference between business success and failure. Data transformation is a key success factor for digital transformation. The biggest challenge facing financial services organizations today is the lack of clean, consistent and accurate data.
Today’s consumers have always shown an interest in sharing their information to receive personalized and innovative services. Banks and financial institutions use (other) data carefully and ensure a well-thought-out customer-centric user experience.
As banks, credit unions, mortgage companies and wealth managers acquire more customers and
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