Blue Prism: How Can Banks Harness Automation to Its Fullest Value?

Top 5 financial services that are ripe for automation

automation in banking sector

The firm doubled processing speed with 50% fewer data keyers required, quadrupling throughput in less than four weeks. TD Ameritrade completed the overall compliance exercise in one-third of the amount of time originally budgeted. There is some disagreement over whether RPA counts as AI, largely because most of its use cases don’t demonstrate true ‘intelligence’.

automation in banking sector

Whether you’re a Retail Bank, a Digital Lender or a Leasing Company, we have the data-driven services that will help your organization accelerate growth. As a result, RPA use cases spread across multiple sectors, including banking, healthcare, and telecom, and business functions, such as RPA in HR and accounting. Fortunately, things are changing thanks to the skyrocketing adoption of robotic process automation (RPA) across various industries.

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Through analysis of customer data, banks can design tailored products and services to meet unique client requirements. Furthermore, data analytics optimizes banks’ marketing and sales strategies with targeted promotions and personalized offers based on specific customer segments. Another advantage of digitalization in banks is the noticeable amount of cost efficiency which benefits both financial institutions and customers. As there are new means of payment and quick cashless transactions introduced, this has cut down so many intermediary fees and people can now save up on so many fronts via paperless payments. The automation of compliance tasks using AI brings about enhanced efficiency and accuracy in regulatory reporting for the banking industry.

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These help to build effective chatbots and virtual assistants like Chat GPT that can improve customer service. According to the survey, financial services professionals have witnessed a significant 20% reduction in the total cost of ownership by leveraging AI, particularly in the context of AI for banking. By adopting AI-driven compliance solutions, banks can automate labour-intensive tasks, leading to improved accuracy and efficiency automation in banking sector in regulatory reporting while minimising operational costs. In this sector, timely and accurate data analysis is crucial due to market volatility and complexity. Intelligent automation can automate data gathering from multiple sources using AI and machine learning, saving hours of work. AI-powered algorithms can track market trends, historical data and news events to optimise investment strategies and manage portfolios dynamically.

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At CACI, our specialists are used to helping financial institutions to optimise their network infrastructure. And we see every day how smart, tactical use of network automation can play a role in meeting the challenge by reducing workloads, improving quality, and meeting regulatory standards. The platform supports regulatory compliance by providing real time automation in banking sector information on your partner’s cash position. Financial services are still heavily dependent on the age-old system of getting manual signatures, with an estimated 94% of firms in that sector printing documents to be signed by pen. However, by adopting a Digital Signature, paper costs not only fell but time required to complete documentation fell too.

automation in banking sector

Join our panel of banking experts as they discuss how AI-driven decisioning and automation provide the tools to stay ahead of the competition. AI algorithms paired with intelligent automation can analyse vast amounts of transactional data in real time, identifying patterns that indicate fraudulent activities, as well as aiding in Know Your Customer (KYC) processes. Intelligent automation minimises human error and as such, the risk of expensive mistakes. Operating with enhanced data accuracy, intelligent automation ensures compliance with regulatory requirements in the Financial Services industry. This goes to show how technology can help maintain and improve customer experience and access to services, and how organisations may wish to adapt for the post-pandemic normal. When looking at the potential use cases for Robotic Process Automation in financial services, like with other industries and organisations, it is important to not just follow what others are doing.

For instance, very high levels of risk detection can be ensured via a solid and transparent rules-based approach, with the power of artificial intelligence being utilised in post-processes. Many firms may overlook the reality that a rules-based system still has considerable advantages because so much of the current industry hoopla is about artificial intelligence. After all, rules-based technology continues to be a cutting-edge area of data science where significant research and development are being done.

What is the purpose of automation?

With automation, we can reduce costs, time, and waste as well as increase productivity, reduce mistakes, and control all the processes of the business in real time. You can replace manual activities with automated ones or reuse the software and systems to support numerous other tasks.

More than half (53%) of organisations are already beginning to implement RPA, and Deloitte predicts the technology will have near-universal adoption by 2023. A successful digital platform required both a flexible and knowledge base which, with strong governance and disciplined behaviours, forms part of the enablement platform and accelerates strategic use of automation technologies. Embracing a strategic mindset in utilising intelligent automation is critical in capturing maximum value. The bank has already realised an estimated 30 per cent additional enablement value to date from its more than 500 digital workers. This enabled the bank to rapidly develop and deploy processes giving customers access to government pandemic aid and relief funds.

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In this context, the article analyses the evolution of artificial intelligence in Russia with emphasis on robotics and automated mechanisms implemented in the financial firms. It also provides an overview of the initiatives of the Central Bank of Russia and their main effects in the payment system. The implications of machine learning and automation are discussed in terms

of monetary policy, prudential regulation and investor protection. Barely a day goes by without the launch of a new report extolling the potential benefits of artificial intelligence (AI) and automation in the financial services industry. These reports often refer to the potential for cost reduction, increased operational efficiency, improved customer experience and, ultimately, bottom-line growth.

  • With that in mind, here are five processes within the financial services sector that are ripe for automation.
  • The firm doubled processing speed with 50% fewer data keyers required, quadrupling throughput in less than four weeks.
  • These automation solutions cater to two distinct categories; attended & unattended Robotic Process Automation (RPA).
  • AI is expected to increase annual revenue by at least 10% for nearly half of the surveyed financial institutions, specifically in the field of AI for banking.
  • Customers can have conversations in natural language, and chatbots can reply when they have something important to tell.
  • It’s very difficult for the financial institutions to struggle except the customers are agreed upon certain services which are only possible with high-tech arrangements.

While chatbots are providing customer service management, understand a problem and give recommendations, they are not developed enough to provide services fully unassisted yet. The financial services sector has undergone seismic change – even well-established institutions are feeling the pressure from leaner margins and agile new competitors. In response, they’re hungry for new ways to drive efficiency, create revenue streams, and offer enhanced value to customers. Banking activities can be streamlined, further saving on the  time spent within the legacy systems.

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This has transformed banking into something much more desirable and efficient making the digitalization in the banking sector trailblazing. Within the banking and financial services sector, processes that affect customers and the business itself can be automated. Whether they be customer or business-facing, automating business processes can help organisations save money and achieve significant operational efficiency.

Chatbot technology, which carries out complex calculations instantaneously, allowing customers to check their finances, evaluate their spending habits and monitor their credit score, is also having a big impact. The speed and efficiency of core business processes received a significant boost from the chatbot innovation. Whether the displacement of human labour by automation is, as is often depicted, another nail in the manual coffin seems a moot assertion. But what cannot be denied is its increasing role across the financial services (FS) sector, with some players even seeing automated environments as a panacea. A business process management (BPM) solution is an integrated platform brining real-time process monitoring, modelling and optimization together onto one system. By providing real-time insights, banks can foresee process issues and take corrective action very quickly.

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The firm found only 11% of people would not consider upskilling or completely retraining if required. Sadly, 51% of workers claim they are offered no opportunities to train or upskill at all. AI and automation are likely to have a similar impact on jobs across all education levels in the early 2020s, but those who have higher education qualifications will be less at risk over the long term. According to PwC, 47% of jobs held by people with GCSEs or lower could be at risk by the mid-2030s, compared with just 12% of graduates. Across the pond, robots could replace up to 1.3 million Wall Street jobs by 2030, according to recent figures from IHS Markit.

What are the banking strategies for 2023?

Customer Growth and Generative AI Are Top Priorities

Banks will seek new ways to drive customer acquisitions. M&As will offer a path to customer growth. Banks will target areas where genAI is ready for primetime. Banks face an intensifying battle for deposits and squeezed margins in H2 2023.