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Ensuring Secure Banking with High-Tech Solutions
In the banking industry, data plays a very vital role. AI-based bots are powering almost every data-related operation.

By
Apac CIOOutlook | Friday, May 24, 2019
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FREMONT, CA: In the banking industry, data plays a very vital role. AI-based bots are powering almost every data-related operation. This in-return helps in enhancing operational capability and decreases risks. The impact of data is adequately highlighted by studying the advancements in consumer credit. Banks do prefer relying on credit scores, which were, traditionally, based on a narrow range of slow-moving data points. This approach can bring two significant constraints. Firstly, slow decision making as the banking sector does not have a complete view of the consumer's financial health. Secondly, the consequences can create thin files on customers who have an aversion to debt. Use of consumer credit has been solely contrary in many countries. To blacklist people who have made late payments, banks tend to use this model.
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Based on integrated data, banks are now basing their lending and risk management decisions. Debt repayment information is being combined with near real-time transactional and account balance data to get through risk, assessment models. Banks can access risk patterns from past behavior to sense future changes, instead of relying on the percentage of available credit used. Data can be practiced to tailor sales and marketing intercommunications. It helps the banks form a detailed view of the customer's worthiness. It helps in customizing sales messages and products for benefiting the increase in service-savvy customers.
The volume, velocity, and range of data types can technically exceed the capabilities of traditional technologies. Unstructured data are usually not suited to former IT approaches and first generation Big Data technologies. In order to overcome this situation, banks are now adopting machine learning, where predictive models uniformly train themselves based on streams of data. Machine learning helps in distinguishing nuanced details for improved results. Success will rely on cultural change. The central role of data brings new risks. Governing and organizing an analytically-driven business is what people need to understand. Certain risks might, however, be external. Rather than stealing the data, the hackers are now attempting to discredit an organization by corrupting it subtly. The banks need to ensure that the best security technology is at their disposal, to remain competitive. This includes authentication that can confirm a consumer's identity. With high-tech adoptions, banks can ensure that their tomorrow is secured.
See Also: Financial Services Review