18 Use-Cases of IDP in Banking System (Boost Workflow 10X)

use cases of IDP in banking

As we know, the National and International Finance Market run on data finance runs on current data and Valid Documents. In the Financial world, you can’t work with any invalid document and fake data, if you do, you will dive your career and life in danger. 

Mainly, Financial institutes like banks are constantly inundated with compliance reports, Loan Documents, Account statements, and much more largely structured and unstructured documents. Managing these documents and with correct data of the documents manually can be time-consuming, costly, and prone to errors. 

If you are a bank employee, you can relate to the problem, how it is difficult to manually check the document, whether is it valid or not, and save the data of the document into the bank system and also generate the report or finalize the task with these data.

For Example, if any person came to the bank for a loan, As a bank manager you can trust the person to give him money. First, you have to verify identity proof, address proof, income proof, and many more things. It is a very time-consuming process. Then after verifying, you need to collect all data and proceed with the further process. I just exampling this for one person, but as Bank, it does not work for one personal loan agreement, there are other many people who have also this and another type of query. With 5 to 10 employees, it is a very challenging task to deal with.

So, As a Bank Manager or High Authority of the Bank, how can you automate these processes and save time and money, and, also improve the accuracy of these data?

Intelligent Document Processing(IDP) with OCR is a technology that uses artificial intelligence and machine learning to automate the extraction and classification of data from any type of unstructured document.

As a bank manager or High Authority of the Bank, you can adopt this Intelligent Document Processing technology to process the large amounts of data that need to be processed accurately and speed up this process 10x.

In this article, I am gonna show you the 18 Use cases of IDP in Banking Industry. And Why already many financial institutions moved manual data entry to Automatic Data Entry.

18 Benefits of Implementing IDP in Banking

1. Customer On-boarding

With the help of a Combination of IDP and RPA software like Docextractor, it automatically collects customer-related data from regulatory agencies and smooths the customer onboarding process with the compliance of banking regulations and policies. Verifying the customer’s identity to ensure compliance with KYC and AML, authenticating the customer’s identity, and continuously monitoring activities for suspicious activity.  It also integrates data with enterprise systems.

2. New Bank account opening

By using the IDP and OCR technology, you can automate the account opening process by extracting data from paper-based Application forms and Legal Documents of the Account Holder. It Automates the process of  Extracting data from documents and saving them into core systems. Update other related systems using robotic process automation and overcome swivel chair operations.

3. KYC and AML Verification

The IDP plays a very important role in this process by collecting and verifying the customer’s personal information and identifying documents such as government-issued IDs, passports, or utility bills. If there is any money laundering case or Fraud case in the Person’s Documents Data, IDP will automatically indicate a red flag. Once the customer’s identity is verified as per the KYC Documents,  IDP software with RPA will create a unique digital identity and proceed with the application for further process.

4. Financial instrument application processing

There are various products in BFSI units. By using Intelligent Document Technolgy, Auto-process application forms, and fast-track instrument processing for various products, and Improve productivity by 60%.

5. Fraud detection

IDP uses various techniques such as rule-based systems, statistical models, AI, machine learning algorithms, and behavioral analytics to detect and analyze data from Paper Documents and, conclude the, is it Fraud or Not. It Automatically extracts data from multi-structured documents and pumps it into fraud detection engines to get a 360-degree view of potential fraud cases.

6. Create customer risk-profiling

Automatic Capturing query of Customer, verification from various sources on the Internet, and then generating a risk score using intelligent document processing during KYC Verification and loan processing.

7. Cheque image processing

Cheque image processing refers to the process of capturing, storing, and analyzing images of cheques to facilitate cheque clearing and settlement. IDP with OCR (Optical Character Recognition) to extract Account Holder, Number, and Amount from the cheque image and save it into the system for further processing.

8. Initial Payment Fund

After receiving and verifying the paper application form, Intelligent document processing (IDP) and RPA, automatically gather data from the main banking system and generate a new account number. And, then, it is released for the customer kit.

9. Mortgage Document Processing

By using IDP software like Docextractor, extract data from mortgage application forms and supporting identity and Address Verification documents as well as update the core systems and databases by using intelligent data capture to initiate further processing.

10. Account Closing

Intelligent Document Processing Software automatically extracts data and further processes it from Account Closing forms.

11. Processing Refunds

If there is a payment transaction that happened to a customer. IDP and RPA speed up the refund request. Basically, first, it automatically validates and releases a refund to the customer.

12. Credit Card Processing

Credit card processing at banks typically involves verifying the cardholder’s identity, checking available credit and funds, and then approving or denying the transaction. By using intelligent document processing and RPA, it is fully automatic. Software like Docextractor, use OCR technology to identify and extract information from the data processor for further step. And, also with this combination of technology, It Retrieve blacklisted applicants from the credit bureau system, and using multiple logic, it verifies and indicates is it red or green flag for the user.

13. Regulatory reporting of customer data

IDP and RPA collect data from multiple sources and generate a report for the new registration of the customer for regulator reporting.

14. Data extraction from annual reports

You can use IDP Software like Docextractor to extract Data from annual reports of Banks by using its ML and AI algorithm and then save them into the required Storage.

15. Email updates

By using intelligent document processing(IDP) and OCR, you can extract customer email IDs from Excel files and integrate them with enterprise banking systems. Though you can do it manually, if there is a huge number of email, using this technology, it can be done in a few minutes.

16. Letter of credit advice

With the combination of IDP and RPA, it creates credit summerly letters by extracting data from the received attachment. It automatically improves the accuracy rate and speeds up the cycle time.

17. Data capture from promissory notes

IDP Automatically extracts data from promissory notes and integrates it with core systems.

18. Auditing 

From the main database, it downloads the documents, and then, using IDP, automatically extracts the data of the required fields, as per the rule, and generates a structured output using intelligent document processing. 

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