How Banking Automation is Transforming Financial Services Hitachi Solutions

Banks struggle to raise the right invoices in the client-required formats on a timely basis as a customer-centric organization. Furthermore, the approval matrix and procedure may result in a significant amount of rework in terms of correcting formats and data. Truth in Lending Regulation Z, Federal Trade Commission guidelines, the Beneficial Ownership Rule… The list goes on. With a dizzying number of rules and regulations to comply with, banks can easily find themselves in over their heads. Consequently, leaders would receive a deferred analysis of the organization’s performance. This would also put the organization out of touch with the ground reality of its market.

• You resolve this problem quickly with sales automation platforms that give you end-to-end call center management capabilities.
• Thanks to automating the checks, history, employment status, and other required documents, the processing time is significantly reduced and delivers a better customer experience.
• Radius Financial Group relied on RPA in banking to accelerate mortgage processing.
• By supporting your teams, bridging system gaps and assisting patients, our Emerging Technology Pods can deliver high-impact solutions for provider groups, treatment networks, and third-party revenue cycle managers.

For instance, LeadSquared allows you to integrate with multiple IVR tools and contact centers. The automation will funnel leads to your sales reps for instant calling upon integration. By bucketing your inquiries based on their attributes, reps can place calls, set up follow-ups, prioritize leads, and complete tasks from a dashboard called SmartViews. New automation initiatives such as 100% paperless journeys, e-KYC services, and e-sign have benefitted all parties significantly.

Infosys BPM approach to RPA in banking

The applications of banking automation span from optimizing daily operations to completely reshaping customer experiences and product offerings. This technology empowers financial institutions to maintain their competitive edge, improve services, and adapt to the evolving demands of the modern financial landscape. In the realm of data analysis, banking automation extracts actionable insights from extensive datasets, aiding in risk assessment and fraud detection.

A few years ago, customer waiting times would be very long due to a shortage of reps to address their queries. Today, by deploying an intuitive IVR platform and voice-based solutions, calls can be received, engaged, and questions answered without needing agents. With LeadSquared, we could bring together all our processes and teams into a single enterprise-wide solution.

Banking: Artificial Intelligence and Automation

Instead of several days or weeks being allocated to a portion of the financial close, the turnaround for reconciliations is accelerated, keeping all financial employees on top of the close. There will be a greater need for RPA tools in an organization that relies heavily on automation. Role-based security features are an option in RPA software, allowing users to grant access to only those functions for which they have given authority. In addition, to prevent unauthorized interference, all bot-accessible information, audits, and instructions are encrypted.

This process requires compiling and analyzing copious amounts of data, which is a time-intensive and potentially error-prone process. We are building a cutting-edge solution, leveraging cloud-based APIs, that automates loan covenant checks and provides early warning indicators so clients can better manage risk if a covenant is breached. Robotic process automation transforms business processes across multiple industries and business functions.

Future of Intelligent Automation in Financial Firms

The financial industry has seen a sort of technological renaissance in the past couple of years. 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. With IA, your digital workers can even help your financial staff with speedier decision-making, such as those in the asset management business covering numerous portfolios. Digital workers can also reduce cyber threats by using machine learning technology to conduct near real-time threat analysis and alerts. They conduct work requiring security, and implementing automation into those systems may seem daunting at first glance. Plus, with lower overhead costs for automation, and reskilling existing staff rather than hiring more people, you’re increasing the level of your return on investment (ROI).

It is tedious to process all this manually and validate if the provided information is consistent with the bank’s statements. Big data is both a requirement and an impediment for financial services companies. Since a large amount of data is generated by various sources, big data is growing. These legacy data structures can’t accommodate the amount of data coming in because it’s structured and unstructured.By 2021, according to an EMC report, there will be 44 zettabytes of digital data. Financial service providers face sorting through their data to decide what is useful and what isn’t.

For example, they can use automated systems to track and monitor transactions to ensure compliance with anti-money laundering (AML) rules. Simply put, automation refers to using technology to perform tasks that humans would otherwise do. It can include everything from software that handles routine tasks like data entry and account management to robots that perform physical tasks like sorting and counting money. Many financial institutions rely on legacy systems and tools, which may not be compatible with the RPA solution.

KYC is a time-consuming process that banks need to perform for every customer. It can eat up to 1000 full-time equivalent (FTE) hours and $384 million per year to perform this process in a compliant manner. Alert investigation is also time-consuming, while up to 85% of daily alerts are false positives, and around 25% need to be reviewed by level-two senior analysts.

Success lies in automating processes

One of the most valuable uses for RPA in financial services is ensuring regulatory compliance. Over the last ten years, banks and financial institutions have spent over $320 billion on compliance and fines and attribute approximately 10% of their operating costs to compliance. If there are no discrepancies post the automated matching, the data is automatically entered into the customer management portal. RPA automation in customer onboarding not only helps in avoiding manual errors but also saves a lot of time and effort put in by the employees. O’Reilly has found that many banking institutions struggle with where they can initiate their intelligent automation strategy even when they understand the benefits.

Depending on the organization, the business may need to conduct significant modernization efforts to enable RPA in various downstream functions. As with report generation, RPA can also be used to support and strengthen regulatory compliance efforts. The system can also flag potential instances of non-compliance, which can then be reviewed and resolved manually by a compliance officer. With the help of RPA bots, fraudulent patterns can be identified earlier in the cycle and flagged to the bank’s fraud and risk management teams in real-time.

For these reasons, many financial institutions have been investing in Robotic Process Automation (RPA) to reduce costs and improve compliance. At UpScale, we are committed to delivering high-quality, reliable solutions that meet the unique needs of each client. We work closely with our clients to understand their business processes, identify areas for improvement, and develop customized solutions that align with their goals and objectives.

In the face of increased AML and KYC regulatory scrutiny, organizations can apply automation and AI to combat fraud and improve transaction monitoring and investigation. With Axon Ivy, you exceed customers’ expectations while drastically reducing your costs of service and mitigating risks. Process management can be time-consuming for finance teams, especially regarding issuing and processing invoices, keeping track of budgets, and creating contracts. This allows for all critical processes to be executed by bots at the appropriate volume and allows for flexibility in providing all of your employees with a digital assistant (attended) bot to help them with daily functions. Attended or “desktop” (RDA) bots act as digital assistants helping employees carry out customer-facing functions, like call center tasks, while providing real-time information to help your employees work more efficiently. Discover which banking processes can be atomated and some basic techniques based on real case studies.

With self-serve portals and chatbots, finance companies are able to reduce the response time and handle grievances better. These could be offers about the different range of cards, benefits of using the credit card, intimation of pre-approved cards, etc. Although RPA solutions are relatively easy to implement and configure, the IT department will still need to formulate a deployment plan. In some cases, such tasks may require specialized skills which the internal team will need to develop or otherwise acquire to ensure the investment is optimized. You can read more about how we won the NASSCOM Customer Excellence Award 2018 by overcoming the challenges for the client on the ‘Big Day’. Contact us to discover our platform and technology-agnostic approach to Robotic Process Automation Services that focuses on ensuring metrics improvement, savings, and ROI.

Intelligent robotic automation allowed Radius to thrive even in the COVID era. The firm registered 30% more loan production revenue than the rest of the industry compared to the Mortgage Bankers Association average. The company also had about 50% more net income than average in the banking sector. Radius Financial Group relied on RPA in banking to accelerate mortgage processing.

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