The financial services companies differentiate themselves from competition by providing speed, ease and variety to their customers. Some of the key challenges the industry faces include complying with regulations, preventing data breaches, delighting consumers, surpassing competition, digitalizing operations, leveraging AI and data, and creating an effective digital marketing strategy.
While data analytics services play a key part in identifying areas of improvements and strengths, unstructured data provides a wealth of information, tapping into which the financial companies can accelerate growth and increase customer delight.
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For instance, a financial services company that provides Credit Score Ratings to its customers and helps many banks assess their customers’ credit scores wanted to improve its Know Your Customer process. The company had to process thousands of scanned bank statements to fulfill the KYC requirements for the applicants. The data had to be extracted from scanned images and digital PDFs.
Indium Software built a text extraction model employing its IP-based teX.ai product on 2000 bank statements. It created a scalable pipeline that could handle a large inflow of documents daily. As a result of the automation of the workflow, the processing of a single file took less than a minute, and the company experienced an 80% increase over the method the company employed previously. The accuracy also was nearly 90%.
In another instance, a leading holding conglomerate that capitalizes on fintech and provides financial services to the under-served in Southeast Asia required predictive analytics to be performed to evaluate the creditworthiness and loan eligibility of its customers. The data related to the loan information of the customer and their geographic details were stored in two separate PDFs for each customer, which needed to be merged. In case the customer had taken multiple loans, it had to be summarized at a row level
using business logic and Power BI used to create dashboards to get an overview of the kind of loans, repayment rates, customer churn rate, sales rep performance, and so on.
To predict whether a loan could be offered to a target customer, Indium leveraged tex.ai to extract customer-related loans and geographic details at the row level. This was used to custom-build business logic and summarize the customer-related information at the row level. As a result,
● The pull-through rate increased by 40%
● The loan cycle time decreased by 30%
● The customer acquisition rate went up by 25% within three months
● Application approval rate went up by 40%
● The cost of customer acquisition came down by 20%
Tex.Ai–For Insights from Unstructured Data
Financial services companies have access to many unstructured forms and information. This limits its use in data analytics and reduces efficiency unless it can be accessed in a format where analytics can be run on it to draw insights.
Indium Software’s Tex.ai is a trademark solution that enables customized text analytics by leveraging the ‘organization’s unstructured data such as emails, chats, social media posts, product reviews, images, videos, audio and so on to drive the business forward. It helps to extract data from text, summarize information, and classify content by selecting relevant text data and processing it quickly and efficiently to generate structured data, metadata, and insights.
These insights help to improve:
● Operational agility
● Speed of decision making
● Gaining customer insights
Secure Redaction and Automation
For the financial services industry, Tex.ai’s ability to identify text genres using the intelligent, customizable linguistic application and group similar content helps wade through millions of forms quickly and categorize them with ease. It helps to automate the extraction process, thereby increasing efficiency and accuracy. Tex.ai can also create concise summaries, enabling business teams to obtain the correct context from the right text and improve the quality of insights and decision-making.
Financial services is a sensitive industry regulated by privacy laws. Tex.ai’s redaction tool helps to extract relevant information while masking personal information to ensure security and privacy by masking all personal data.
Check this out: The Critical Need For Data Security And The Role Of Redaction
Tex.ai can also be used to extract insights from chatter and reviews, thereby helping financial institutions create customized products and services and focused promotions to improve conversions and enhance overall customer experience. It can help with fraud detection by analyzing past financial behavior and detecting anomalies, thereby establishing the credibility of the customers. This is especially important for processing loan and credit applications. An added advantage is the software’s ability to support several languages such as English, Japanese, Mandarin, all Latin languages, Thai, Arabic, and so on.
Further, teX.ai provides customizable dashboards and parameters that allow viewing and managing processed documents of customers. An interactive dashboard facilitates monitoring and improvement of processes by identifying and mitigating risks.
Using ok Indium’s Tex.ai solution can help financial services companies to deepen their customer insights, understand their requirements better, and provide bespoke solutions. This will help expand product base, customer base, and revenues while ensuring data privacy and security.
Indium’s team of data analytics experts can also help with customizing the solution to meet the unique needs of our customers.