How Banking Automation is Transforming Financial Services Hitachi Solutions

automation in banking examples

For example, AI, natural language processing (NLP), and machine learning have become increasingly popular in the banking and financial industries. In the future, these technologies may offer customers more personalized service without the need for a human. Banks, lenders, and other financial institutions may collaborate with different industries to expand the scope of their products and services.

  • Based on the business objectives and client expectations, bringing them all into a uniform processing format may not be practicable.
  • Apart from these it is also recommended to follow the RPA best practices in the financial services to ensure that you get the desired results after implementing the strategy.
  • That’s why digitization with the help of modern and secure solutions is so important for building a competitive advantage.
  • Indeed though RPA was developed in the 2000s, it positively started entering the market only after 2015.
  • Rather than spending valuable time gathering data, employees can apply their cognitive abilities where they are truly needed.
  • Receive a signature audit trail for each document so you can see who signed a document and exactly when they signed it.

Being an iterative process, the implementation of AI for finance requires close collaboration between technology experts, domain specialists, and business stakeholders to achieve the desired outcomes. Consider contacting Django Stars if you would like to involve a reliable tech partner that can provide valuable expertise and guidance throughout the implementation process. There are high hopes for increased transactional and account security, especially as the adoption of blockchains and cryptocurrency expands. In turn, this might drastically reduce or eliminate transaction fees due to the lack of an intermediary. Aggregators like Plaid (which works with financial giants like CITI, Goldman Sachs and American Express) take pride in their fraud-detection capabilities.

Steps to Deploy RPA in Banking and Finance

But this has also lead to a complex scenario where the problem has to be addressed from a global perspective; otherwise there arises the risk of running into an operational and technological chaos. Anti-Money Laundering (AML) regulations, Know Your Customer (KYC) guidelines, GDPR and other regulatory elements demand accurate data to prove compliance. Improve quality and manage risk by automating data collection and reporting. Through a 100% automation of data migration and report updates, our program freed 3 FTEs from repetitive, robotic tasks.

What are examples of automation?

Automation includes using various equipment and control systems such as factory processes, machinery, boilers, heat-treating ovens, steering, etc. Examples of automation range from a household thermostat to a large industrial control system, self-driven vehicles, and warehousing robots.

AI can bolster private banks’ ability to manage and scrutinise data in a way which ensures higher levels of compliance and reduced margin for human error. It can also predict risk and detect unusual transactions with a level of accurate efficiency unattainable by an analyst in New York, London or Hong Kong. Banks offer personal, business, home, auto and boat, and home equity loans. The loan processing and approval process eats up the productive hours of the banking personnel. AI and RPA-powered automation can help make decisions about timing marketing campaigns, redesigning workflows, and tailor-making products for your target audience. As a result, you improve the campaign’s effectiveness, process efficiency, and customer experience.

Improvements from Start-to-Finish

When they could not process the amount of loans using conventional methods of loan request processing, UBS turned to RPA. In collaboration with Automation Anywhere, the bank implemented RPA just in 6 days, resulting in a reduction of request processing time from minutes to 5-6 minutes. Banks have vast amounts of customer data that are highly sensitive and vulnerable to cyberattacks.

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For example, a bot may log into an IT system, copy or insert records, and execute other tasks that are typically handled by people. The result is that with the use of these data tools in robotic process automation, firms may not only save money, but also increase the productivity of their workers. Due to COVID-19, cost savings initiatives are a major focus for banks in order to be competitive and provide better services.

How can businesses get started with RPA?

This is how organizations provide the best products and services in areas ranging from wealth management to investment advisory. By using robotic advisors, banks can interact with customers promptly and provide high-quality assistance even in the most complex issues. Automation improves efficiency, accelerates processes, and eliminates the risk of human error.

What are 4 examples of automation?

Common examples include household thermostats controlling boilers, the earliest automatic telephone switchboards, electronic navigation systems, or the most advanced algorithms behind self-driving cars.

Its simple, unique, intelligent, and powerful features have managed to create a loyal customer base of more than 6 million users across Europe within a short time, and it’s gained a competitive advantage. With newer digital banking products and services, customers are now more exposed to the threat of losing money. Cybersecurity is now becoming a major consumer demand for any digital bank. They are FDIC insured just like traditional banks, so depositors don’t have to worry about the safety of their money. Online Banking also offers several different security measures, including two-factor authentication and alerts if activity on your account is suspicious.


The process of booking loans and verifying SOX compliance was high in volume, repetitive, and highly manual, requiring analysts to key 80+ data fields into a system. At Evolvous, we offer a specialized approach to RPA in financial services. We have a group of skilled RPA consultants who are knowledgeable about the most recent RPA tools and technologies.

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For instance, a US bank11 leveraged RPA for optimizing anti-money laundering processes for due diligence on prospects, clients for periodic review, and subjects of suspicious activity monitoring. The outcome of the automation project was that the RPA bot boosted regulatory compliance and generated a 75% saving on current due-diligence costs. So then, what are the next steps for banks interested in using intelligent automation. First, it is crucial to identify the appropriate use cases such as repeatable and structured processes then prioritizing these based on alignment with business objectives.

More in Banking Automation

Changes can be done to improve and fix existing business techniques and processes. Some of the most obvious benefits of RPA in finance for PO processing are that it is simple, effective, rapid, and cost-efficient. Invoice processing is sometimes a tiresome and time-consuming task, especially if invoices are received or prepared in a variety of forms. Human mistake is more likely in manual data processing, especially when dealing with numbers.

automation in banking examples

Likewise, bots continue working 24/7 to take care of data entry, payroll, and other mundane tasks, allowing humans to focus on more strategic or creative work. The impact of the COVID-19 pandemic has spread all over the world and it has affected voluminously everyday lives of billions. Social consequences and virus spread that needs to be addressed to take proper action to resolve the challenges faced during this pandemic period. The pandemic needs proper surveillance, monitoring, diagnosis, and identification of infected patients. Most researchers continue to give ways to detect and control the pandemic diseases of this type. Pandemic has made researchers from all areas and virologists consider cross-disciplinary approaches to combat with COVID-19.

Business process automation vs. Robotic process automation

Ultimately, companies will accelerate task completion and drive customer satisfaction. Financial institutions and banks can streamline the loan application process through RPA. Typically, loan and appraisal requests take the form of huge chunks of documents when accumulated. The teams must extract data from those applications, verify them against numerous identity documents, and manually evaluate creditworthiness. AI-enabled RPA solutions can automate a range of these procedures, if not all of them. One great option for implementing RPA into your financial services operations is to use the “a la carte” RPA mapping offered by our team at The Lab.

automation in banking examples

Banks have a lot of internal back-office processes that benefit from automation. For our customer POP Bank we have automated processes regarding reconciling data, confirming and archiving interbank transactions and processes related to the bank’s internal control, like confirmations and reports. Most of these are time-consuming, tedious legislative processes that create little value.

Bank Guarantee Closures

Banks employ hundreds of FTEs to validate the accuracy of customer information. Now RPA allows banks to collect, screen, and validate customer information automatically. As a result, banks are able to complete this process faster and for less money, while also reducing the potential for human error. More and more people are using digital banking, cryptocurrency, and mobile payments. These Digital transformation projects remain at the top of the list for many banks and will continue to drive the overall technological growth of the banking process.

How do you automate a bank account?

  1. Setting Up Direct Deposit.
  2. Earmarking Money for Each Goal.
  3. Choosing a High-Interest Account.
  4. Taking Advantage of Employer Programs.
  5. Paying Bills Automatically.
  6. Monitoring Financial Insights.
  7. Increasing Deposits Over Time.
  8. Use a Cash-Back Card.

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