You don’t usually associate “big data,” the generation and analysis of huge chunks of information, with financial inclusion. But bank big data helps institutions assess risk and better serve people who benefit from financial inclusion.
How Banks Use Big Data to Help Customers
The analysis of big data for banking has the potential to take financial inclusion to the next level. It can improve products, decrease costs, reform policies and better the overall operations of financial services providers. By knowing more about their customers, banks become more effective in designing their products for target markets. These changes set the stage for inclusive services with lower fees.
- Credit Scoring: Big Data enables credit decisions. For example, traditional FICO scores are based on consumer financial data. What if a new credit scoring system leveraged alternative information that helps lenders make equally effective lending decisions? Some financial inclusion companies, in fact, use utility and mobile phone bills—even social media behavior—to predict loan risk for people at the bottom of the pyramid.
- Decreases Costs: Behavioral data helps providers predict customer habits—average daily balance, willingness to pay debts and savings commitments. In developing countries, Know Your Customer (KYC) requirements erect a barrier to entry for the unbanked and are an additional expense for banks and microfinance institutions. The use of public domain data to confirm an individual’s identity (when official documents are missing) greatly decreases costs.
- Policy Changes: To strengthen financial inclusion policy, systems are needed to accurately gather data. Various organizations are already taking steps in the right direction. The Alliance for Financial Inclusion has created a group focused on exploring how countries can be more efficient when gathering demand-side and usage information. The World Bank’s Financial Inclusion Index (FINDEX) provides data from over 150 countries relevant to financial inclusion. Results from these efforts can help drive policy reform, regulation, and national strategies for inclusion.
Bank Big Data Adoption Challenges
Banks have been slow to make use of Big Data because it is fragmented. Superbanks have a ton of data, but it tends to reside in compartmentalized departments or silos and is difficult to access across firewalls. Also, contracts with networks like Visa may limit the use of information, while regulations and consumer agreements may restrict it even more. These are obstacles, but can be overcome by changes in policy and with a new era of financial services providers who create customized solutions for a target market.
Consumer Protection Against Data Overuse
Client protection issues arise with the use of bank big data—namely around privacy of information. What are the limits to which information is appropriate for providers to use? How will this data remain secure and only used for intended and legally-approved purposes? As financial services companies expand their use of big data to improve operations and services, questions surrounding consumer protection will need to be simultaneously addressed.
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