The Banking Sector Is Plagued With Big Data Issues
Tue, April 20, 2021

The Banking Sector Is Plagued With Big Data Issues

Per Accenture’s Banking Technology Vision 2018, a survey of about 800 bankers found that 84% of them leverage data to enable critical and automated decision-making processes / Photo by: goodluz via Shutterstock

 

Bank CEOs nowadays are used to being summoned to congressional and parliamentary committees to explain themselves and empathize with the recent congressional testimonies from tech firms, said Alan McIntyre of business news magazine Forbes. Like any other sector, banking sees data as oil, a valuable resource that will make a clear distinction between winners and losers. 

Per Accenture’s Banking Technology Vision 2018, a survey of about 800 bankers found that 84% of them leverage data to enable critical and automated decision-making processes. Additionally, 94% of respondents said they are confident in the data’s integrity when it is sourced internally. 

But the problem here is that banks are utilizing data from third parties to enhance their internal data when it comes to deciding on matters such as pricing, cross-selling, and even whom to lend.

 

Statistics On Data and Banking 

Securing, maintaining, and validating data are important for banks because they are the epicenter of most commercial activity, enabling them to have wide access to a variety of customer data. That data will grow in the future considering that open banking increases the amount of data collected from each customer. But there’s good news for banks. Customers are willing to share data to drive innovation. In fact, the survey conducted by Accenture—a multinational professional services company that provides services in strategy, consulting, digital, technology, and operations—showed that four out of five customers will share their personal information with their bank, expecting it to offer faster, improved services. 

However, the survey also found a dissonance between the “desire to ingest” and using a varied set of data to support decisions versus the accuracy of that data. About 78% of bankers believed that automating decision-making processes elevates the risk from fake data, inherent bias, and external data manipulation. 

Further, 77% said their bank is not well-equipped to handle such issues while half of the respondents stated that they are not investing enough to verify that data to make informed business decisions. Eleven percent of those respondents trusted their data to be reliable but not validated, 16% found ways to validate data but cannot assure its quality, and 25% validated it but acknowledged that they should do more to ensure the data’s quality. Besides, relying on inaccurate, unverified data leaves banks susceptible to false business insights, leading them to make bad decisions. 

Information Is Power 

The rapid development of new goods and services is rooted in the banking sector’s increased use of big data, as noted by Rep. Tom Emmer, R-Minn., the ranking member of the task force, as quoted by Henry Kenyon of political news portal Roll Call. This development generates “immense” amounts of data, with 90% of the world’s data created in just two years. And when banks generate this amount of data, owners and possessors may gain power, which may come with increased responsibility. This imposes an unwritten duty to use that data ethically, Emmer explained. 

Data aggregation tools are utilized to access consumer bank account transaction information and other data related to financial products and services, according to Lauren Saunders, associate director of the National Consumer Law Center. These tools have the potential to create more beneficial goods and services as well as leverage cash-flow data to enable improved access to affordable forms of credit, products encouraging savings, and services to aid consumers in managing their finances, Saunders explained. 

However, detailed and sensitive data contained in a customer’s bank accounts can be exploited to less beneficial purposes such as lending assistance to predatory leaders, who fine-tune their tactics or permit others to discriminate against someone based on the biased data fed into machine learning algorithms, Saunders warned. Consumers are not confident about banks using big data tools unless there are industry-wide regulations. 

Data aggregation tools are utilized to access consumer bank account transaction information and other data related to financial products and services, according to Lauren Saunders, associate director of the National Consumer Law Center / Photo by: GaudiLab via Shutterstock

 

Addressing Big Data Issues 

Banks should stay away from fintech applications that employ outdated approaches like screen scraping. Rather, they should start embracing APIs (application programming interface), as recommended by Don Cardinal, managing director of Financial Data Exchange. Seny Kamara, an associate professor at Brown University’s Department of Computer Science, said APIs refer to “standardized interfaces between applications that allow for better interoperability and improved security.” API-based designs take advantage of a user-approved digital token to identify “what pieces of data can be accessed and for how long,” he said. 

Moreover, banks should create a “data intelligence” function to draw on data science and cybersecurity tools to avoid the likelihood of anyone tampering with data for their self-interests. The purpose of this is to “grade the truth within data by establishing, implementing, and enforcing standards for data provenance, context, and integrity.” Banks should remember that not all bad data originate from an individual with malicious intent. Instead, it can be a sign that a process isn’t working out, prompting banks to address it. 

Most importantly, banks should learn to balance using data to improve services and safeguarding it from breaches. Banks should ensure they are not making bad decisions caused by using flawed or malicious inputs. In the words of Benjamin Franklin, “By failing to prepare, you are preparing to fail,” as mentioned by McIntyre. 

Data is the bread and butter of the banking sector. Banks can use it to improve their services or draw valuable insights. However, it might be difficult for customers to trust how banks will use or store data. One way is to set up security measures using updated fintech tools to protect their data from malicious entities. It’s challenging but at least banks are setting themselves up for long-term success.