Grab that stash of dirty cash from under your pillow Mr/Mrs Moneybags, and shake your money-maker over here. Why? Because we all know you’re a slave to money then you die; and today, we’re investigating how Business Intelligence (BI) can be harnessed and applied to the banking and finance sector to leave both customers and financial institutions with diamond studded smiles.
Research says finance sector to benefit from Business Intelligence
A recent Bank Systems and Technology report says that many U.S. banks and other financial institutions could benefit from implementing a BI solution.
“Banks want to use customer-level data on product holdings, channel activity and profitability to improve the targeting of online campaigns and make account application and funding processes more seamless and effective,” the report states.
By using a BI solution to analyze organizational data, banks can improve and streamline operational efficiencies to not only bolster sales and marketing strategies and better develop customer service programs, but also mitigate risk, by developing more appropriate risk management processes.
But how can this be achieved? How should a BI tool be applied to the operations of a bank – what are the key processes and metrics to consider?
Risk management
In a promptly changing and uncertain financial world, banking institutions need to rely more on fact-based actionable information, gleaned from ever-increasing data assets, to reduce risk wherever possible. The actionable information generated by a BI solution can mitigate risk in the banking sector by:
- Quickly and efficiently detecting and reducing incidents of fraudulent activity (eg: cases of credit card fraud) by tracking customer transaction history
- Calculating the probability that a customer will default on a loan and estimating the cost of recovery
- Accurately estimating the risk of customer loans based on:
- The financial assets and earning capacity of the borrower
- The prevailing economic climate
- Analyzing credit portfolios, enabling banks to quickly identify potential delinquency cases, and act early as a preventative measure. Data analysis can also analyze trends in customer delinquency, from which new policies can be developed, to reduce the rates of delinquency cases in the future.
- Ensuring compliance with statutory and regulatory requirements
Improve operational efficiencies and boost profits
Banks can reduce ongoing costs, and maximize existing resources and expertise, by analyzing operational processes and activities to:
- Generate massive internal efficiencies (eg: analyzing the performance of sales personnel, tellers and account managers)
- Understand growth patterns to maximize the chance of repeatability
- Track individual revenue streams to determine profitable and non-profitable services and products
- Set key benchmarks for crucial metrics such as the number of net new customers and their profitability, compare them against industry standards, and track them towards defined goals
- Develop more effective marketing and sales campaigns through detailed and accurate customer segmentation
- Analyze and serve customer segments according to costs, profits and services used
- Identify and actively retain and pursue profitable customers
Customer segmentation
A world-class BI solution allows banking institutions to accurately and efficiently segment their customer-based to:
- Effectively tailor products and services: Better understand customer needs and sentiments regarding banking, and as a consequence, develop, implement and offer new market-leading financial products and services to gain and maintain competitive advantage
- Effective customer profiling: Analyze the data stored in the core banking CRM based on a range of customer segmentations and geographies to uncover the ideal / most profitable customer profile. The customer base can be analyzed to determine profitability across branches and products, and identify and develop new cross-sell and up-sell opportunities and marketing campaigns accordingly. This is crucial, as research indicates that the cost of selling new banking products and services to an existing customer is five times lower than to a new customer. In addition, cross-selling strengthens customer relationships and loyalty.
Improve customer satisfaction through understanding and transparency
Banks can further increase customer satisfaction ratings by proactively harnessing data to give clients superior insight into their individual transitional operations, allowing them to more effectively manage their finances by having:
- Real-time understanding of payments
- Real-time understating of spending
This will enable customers to more easily manage finances by being able to track and analyze their spending and earning patterns.
In addition, analysis of customer point-of-contact data can help institutions understand customer sentiment and behaviours in order to:
- Effectively and efficiently satisfy customer needs and demands
- Win-over competitors customers
Securing existing customers and reducing churn rate
Data mining and analysis techniques can be used to effectively maintain customers by:
- Uncovering the reasons behind customers switching to a competing institution. New processes can then be implemented to reduce churn rates.
- Tracking changes in customer behaviour so products of services can be tailored accordingly
Conclusion: Get rich, but don’t die trying
Implementing an enterprise-wide self-service BI solution in modern banking institutions will eliminate siloed operations in the back-office and enable management to:
- Manage Risk
- Leverage customer insights to increase profitability and improve products/services
- Gain visibility into their business operations to increase profitability and improve products/services
So, whether you’re in the banking sector or not, crack open your piggy-bank, grab all the coinage floating aimlessly in the sneaky gap at the back of the sofa, and head down to your local branch because…
Yellowfin is making Business Intelligence for the banking and finance sector easy, and making everyone a little wealthier.