Business Intelligence and Analytics in Banking
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The document discusses the importance of business intelligence (BI) and analytics in the banking sector, highlighting the need for banks to leverage data to differentiate their services and innovate offerings. It outlines key challenges faced by banks, such as unstructured data and customer analytics, as well as statistics revealing a gap between banks' understanding of customer needs and customer expectations. The document also identifies key drivers for analytics in banking and how analytics can aid in customer acquisition, retention, and maximizing share of wallet.
Business Intelligence and Analytics in Banking
- 1. [email protected] | www.sesameindia.com BI and Analytics in Banking
- 2. Introduction Banking has advanced from individual brick-and-mortar silos to networked institutions that caters to individual requirements of its customers. Today, more than ever, it has become crucial for banks and financial institutions to differentiate their services from the rest. To create new and innovative services that benefit customers and add to the bank’s business value, banks must leverage the banking data and utilise it. BI and analytics solutions can help banking institutions manage all banking and customer data to gain insights and make informed decisions.
- 3. 03 [email protected] | www.sesameindia.com Few Challenges Faced by Banks (that can be conquered using BI and Analytics Solutions) Unstructured data Customer analytics Single view of customer Governance Fraud identification
- 4. 04 [email protected] | www.sesameindia.com Take a tour on these statistics 70% Over 70% of the executives in banks worldwide say customer centricity is important to them. Only 29% analyse customers’ share of wallet, one of the key measures of a bank’s relationship with its customers. Less than half of banks analyse customers’ external data, such as social media activities and online behaviour. According to Capgemini and EFMA’s research, only 37% of customers believe that banks understand their needs and preferences adequately. 37% According to Capgemini and EFMA’s research, only 37% of customers believe that banks understand their needs and preferences adequately. 37% Only 37% of banks have hands-on experience with live big-data implementations, while the majority of banks are still focusing on pilots and experiments. 37%29%
- 5. 05 [email protected] | www.sesameindia.com Key Drivers for Analytics in Banking Digital challengers End-to-end process optimisation Risk and compliance Unified channel experience Increasing digital footprint
- 6. 06 [email protected] | www.sesameindia.com How can Analytics and BI help banks with customer data? In acquiring new customers By retaining customers By growing share of wallet.