In today’s fast-paced data-driven world, data quality has become a buzzword for every industry. However, there is a strong correlation between data quality and the banking sector. Banks used to be all about deposits and loans, and everyone in the bank knew their customers by name. <\/p>\n\n\n\n
Now, banks do everything digitally, eliminating customers’ need to visit the bank. The banks only know their customers with the data. So, offering a good customer experience and developing mutual trust depends on a clean and validated database. According to Forbes<\/a>, 20% of the data is unstructured, increasing the likelihood of data drifts.<\/p>\n\n\n\n Poor data quality results in poor customer experiences affecting the bank’s reputation. For example, will the customer be satisfied if a customer’s database is not updated and a banker offers him a high-interest rate on loans without realizing that the cibil score is high? Certainly not! The customer will move on to the next bank with a lower interest rate. All primary and complex banking operations rely on data. One minor hiccup is all it takes to exacerbate customer trust. Whether a bank is large or small, data quality is critical for acquiring and retaining new customers.<\/p>\n\n\n\n Top banking players have already begun to invest in smart data quality tools to discover the infinite capabilities hidden in the massive volume of data. Some data quality tools necessitate extensive coding knowledge, thereby increasing the complexity. However, Freda<\/a>, an intuitive data quality platform, is a game changer in the banking industry. It empowers everyone to ensure trusted data, become AI-driven, and develop digital services.<\/p>\n\n\n\n Banks have an excellent opportunity to offer a good customer experience, multiply profits and drive innovation when precise data is analyzed. However, bankers are still hesitant when it comes to cleaning the database. Can you believe one of the bankers sent around $1 million to the wrong people? Yes, it happened, and the regulatory committee fined the bank $400 million for its long-standing internal data problems.<\/p>\n\n\n\n Banks deal with invalid or outdated data due to massive data sets, lack of standard data models, and manual data processes. Risk measurement and management are receiving a lot of attention, but they overlook that data used for the analysis requires a periodic refresh. Data breaches will cost banks millions of dollars and the customer’s trust. According to a study conducted by Accenture<\/a>, the decline in trust cost companies $180 billion in revenue over the previous two years. So, to benchmark and thrive in this competitive world, banks need a high-quality database.<\/p>\n\n\n\n The banking industry faces enormous challenges due to increased regulations, compliance issues, and changing customer demands. Trusted data is the ideal solution to address these and many other challenges.<\/p>\n\n\n\n Let’s look at how data quality can benefit the banking industry.<\/p>\n\n\n\n Banking is a competitive and challenging industry. Customers anticipate a personalized experience. Millennials account for more than 40% of mobile banking users in today’s digital world. However, bankers must also deal with customers from other generations who value human interaction and visiting physical branches. Understanding every customer and providing unique experiences is the ideal solution.<\/p>\n\n\n\n AI and ML technology advances are opening new doors to address every generation’s challenges. But, the only catch is the data fed to these models should be accurate and up-to-date to derive insightful solutions. Customers no longer accept bad experiences; they jump to the plethora of options available. So, maintaining a trusted database is one of the keys to retaining your customers. <\/p>\n\n\n\n Banks deal with massive amounts of private and third-party information in this digital era. A single data breach will cost the bank its reputation and millions of dollars in fines. Banks must comply with regulations<\/a> such as CARD Act, Community Reinvestment Act, and Fair Credit Reporting Act. <\/p>\n\n\n\n Measuring the data’s completeness, accuracy, and validity is essential to mitigate risks. However, banks have difficulty locating and resolving all data quality issues caused by siloed data. Freda, a powerful data quality platform<\/a>, eliminates the risk of silos, ensures validity, and instantly delivers trusted data.<\/p>\n\n\n\n In the banking industry, digitization is now the norm. Digitization is significant in everything from understanding customer journey analytics to providing personalized experiences, reducing financial fraud, and improving AI and ML infrastructure. But digitization does not work in a vacuum. High-quality data is critical for digitization. However, only 17% of organizations have high-quality data, according to a survey <\/a>conducted by digital banking report.<\/p>\n\n\n\n You cannot provide the desired experience with a piece of false information about the customer. Also, customers no longer expect but demand personalized experiences. As a result, implementing data quality tools to ensure the database’s validity and reliability is trivial in this data-driven world.<\/p>\n\n\n\n Poor quality data can disrupt your business. So, despite the size of the bank, it is essential to regularly ensure the database’s quality. We have you covered if you are looking for a perfect data quality tool with zero coding. Take a free demo<\/a> with us today to see how Freda<\/a> can simplify your data quality process.<\/p>\n","protected":false},"excerpt":{"rendered":" In today’s fast-paced data-driven world, data quality has become a buzzword for every industry. However, there is a strong correlation between data quality and the banking sector. Banks used to be all about deposits and loans, and everyone in the bank knew their customers by name. Now, banks do everything digitally, eliminating customers’ need to<\/p>\n","protected":false},"author":31,"featured_media":5108,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[265,72],"tags":[263,294],"yoast_head":"\n<\/span>Why is data quality crucial for banks?<\/strong><\/span><\/h2>\n\n\n\n
<\/span>Role of data quality in the banking sector<\/strong><\/span><\/h2>\n\n\n\n
Increase customer retention<\/strong><\/h3>\n\n\n\n
Ensure compliance and mitigate risks <\/strong><\/h3>\n\n\n\n
Enable rapid digitization<\/strong><\/h3>\n\n\n\n
<\/span>Offer great banking experiences with trusted data<\/strong><\/span><\/h2>\n\n\n\n