How to streamline banking and finance services Blog

The automation that comes from NLP and NLU also helps banks to save time and reduce human error. Generating compliance reports for fraudulent transactions in the form of suspicious activity reports or SARs is a regular requirement at banks and financial institutions. Conventionally, compliance officers are supposed to read all the reports manually and fill in the necessary details in the SAR form.

• 24/7 availability, personalised services and instant communication are considered essential by today’s banking and finance customers.
• By embracing RPA, banks can improve the customer experience while reducing costs and improving efficiency.
• The bank automation market size is projected to grow from USD 3.1 billion in 2022 to USD 8.2 billion by 2027, at a CAGR of 21.8% during the forecast period.
• Intelligent process automation demands more than the simple rule-based systems of RPA.
• The results in the elimination of an error-prone, time-consuming, manual data entry process, and a sharp reduction in TAT while, at the same time, maintaining complete operational accuracy and mitigated costs.
• 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.

Largely powered by pre-programmed scripts and APIs, RPA tools can perform repetitive manipulations or process structured data inputs. However, even the most basic RPA solutions can save teams a tremendous amount of time and effort. For instance, automating three business processes with the help of RPA led to a 63% reduction in working hours for one bank.

Credit Application Processing

A report by Business Insider suggests that nearly  80% of banks are aware of the potential benefits that AI presents to their sector. Another report suggests that by 2023, banks are projected to save $447 billion by using AI apps. These numbers indicate that the banking and finance sector is swiftly moving towards AI to improve efficiency, service, productivity, and reduce costs.

Using WeChat wallet, users can pay for a range of goods and services — both online and in real life. What’s even better, you often do not need to leave the app to get the thing you need. The number of account closure requests that banks have to deal with monthly is enormous. One reason is the non-compliance on the part of the clients in the submission of mandatory documents. Although the bank has automated the process to a certain extent, RPA further accelerates it and brings it down to a record 10–15 minutes for processing. Another benefit of RPA in mortgage lending deals with unburdening the employees from doing manual tasks so that they can focus on more high-value tasks for better productivity.

Robotic process automation:

Deep learning in finance and banking enables virtual assistants to answer questions, automate common actions and suggest products for specific customers. It can reduce costs by quickly identifying suspicious transactions and can use unstructured data, such as Google Street View images, to check that a business exists or to perform other compliance checks. There is an impressive amount of power and potential to deep learning algorithms; the technology is even helping banks to assess credit risks and loan requests. To further enhance RPA, banks implement intelligent automation by adding artificial intelligence technologies, such as machine learning and natural language processing capabilities. This enables RPA software to handle complex processes, understand human language, recognize emotions, and adapt to real-time data.

Of all reconciliations that occur in banks, these are typically the most advanced, the most automated, and tend to be more centralized. A reconciliation in the banking industry is defined as the process of comparing and matching transactional data between different banking systems on a daily, weekly, quarterly, or annual basis. Routine reconciliation tasks are often perceived as required drudgery and the cost of doing business to make sure all business information is aligned. While that might be true, there are ways to reduce the manual labor required to constantly compare and “balance” information between multiple business systems. Upon assessment, the next work is the calculation of cost and efficiency gains you can get via RPA implementation.

Order-To-Cash From A Customer’s Perspective: It’s Not About Orders, It’s About Customers

In banking and finance, Robotic Process Automation is a continuous process. You can’t automate everything at once, so picking a starting point thoughtfully is a good idea. RPA can also assist banks in closing accounts in unusual circumstances, such as when customers fail to present KYC documentation. While RPA systems give data in various formats, they may also draft reports by auto-filling the available report format, resulting in error-free reports and taking the least amount of time.

When it comes to RPA in finance, the top three vendors of enterprise-ready solutions with enhanced finance controls and automation are UiPath, Automation Anywhere, and Blue Prism. Their solutions ensure regulatory compliance, effective risk prevention, rapid ROI, and more. Meanwhile, by integrating metadialog.com RPA into front office operations, banks cover more communication channels to reach consumers promptly and effectively. It results in fewer complaints and better loyalty rates thanks to superior customer experience (CX). Additionally, users can set up automatic bill payment and invoice processing.

Why OCR Is Incompatible with True Digital Transformation

Today’s complex, resource constrained and demanding business environment demands excellence in F&A risk management while constantly challenging teams to “do more with less”. This is complicated by the critical nature of risks such as fraud that can affect an organization’s bottom-line and dent its corporate reputation. Whatever the role a financial institution decides to play in the emerging banking ecosystem, success will require an openness to new ideas and experimentation.

Decide what worked well, which ideas didn’t perform as well as you hoped, and look for ways to improve future banking automation implementation strategies. Timesheets, vacation requests, training, new employee onboarding, and many HR processes are now commonly automated with banking scripts, algorithms, and applications. Lenders rely on banking automation to increase efficiency throughout the process, including loan origination and task assignment. Traditional software programs often include several limitations, making it difficult to scale and adapt as the business grows. For example, professionals once spent hours sourcing and scanning documents necessary to spot market trends. Today, multiple use cases have demonstrated how banking automation and document AI remove these barriers.

Differences Between Digital Banks and Traditional Banks

Remember that not all RPA vendors fit the specific requirements of an organization. Choosing the accurate RPA tool and implementation partner can be instrumental in impacting the outcomes of the project. First and foremost, it is crucial to conduct a thorough assessment and detailed analysis to shortlist the processes that are suitable for RPA implementation. Make a list of the main operational issues that can be addressed and resolved through RPA, followed by assessing their impact & feasibility.

How we brought resiliency to our leading FinTech client’s operations, transforming their business processes and driving efficiencies to enhance the overall customer experience. Based on our experience of integrating bots for the BFSI sector, we’d like to encourage you to give it a try. For a more accurate answer, RPA experts should make a thorough analysis of your business processes. If you don’t know what kind of automation will work best, we recommend hiring a reputed RPA partner to save you from unnecessary expenses and wrong choices. But we hope now you’ll know the answer when you hear a question like ‘what is the cognitive part of Automation Anywhere, UiPath, or any other tool? After all, the ongoing revolution of RPA in banking is no longer a scene from a computer game or sci-fi movie.

Zero infrastructure cost

That’s why the best digital transformation strategies are holistic and overarching processes that take into account the limits in the value of legacy infrastructure. The root of the problem is the traditional separation of IT and business departments handling different operations. To integrate RPA solutions successfully, it’s essential to come up with a new distribution of those responsibilities and create an alignment between the teams. Make sure that your partner can provide you professional implementation services starting from idea definition and requirements gathering, through planning and execution, to support and maintenance. Fraudulent transactions are one of the biggest headaches for banks, and monitoring every single transaction manually to identify fraud patterns is increasingly challenging.

Grab also automated their employee onboarding process, to further accelerate time to value. They can now auto-provision Windows machines for new employees, pre-loaded with the appropriate applications, in under 20 minutes. Mosaic also uses automation in their support workflow to move support ticket data securely from Zendesk to their CRM, which was created using Quick Base. Now, instead of downloading reports and uploading them into a different application manually, they use automation to reduce data silos at their organization. Now that we have looked into the real-world examples of artificial intelligence in banking, let’s dive into the challenges that exist for banks using this emerging technology. For many years, the banking industry has been working on transforming itself from a people-centric business to a customer-centric one.