Although Banking seems to go through a phase of unprecedented innovation, for most of the institutions, Online Banking is still the most widely used (sometimes the only) Digital touch point. Digital disruption is attacking the traditional banking’s operational inefficiencies. New entrants like digital-born Fintech start-ups are making it more difficult for old-fashioned bankers to survive. Most players are already on a mission to rapidly alter the business models and find a more competitive landscape to spread globally. But investing a lot of manpower in day-to-day tasks will only make it less-digital and less-future-ready. Introducing RPA in banking is the safest first step towards Artificial Intelligence adoption as the basic Robotic Process Automation applications start with mimicking the mouse clicks, keystrokes, and web scraping to execute system-based work.
Many other industries have already dipped their toes in the waters of automation for their business functions and banking on its benefits. But RPA in Banking is yet to kickstart as half of the banking community is still skeptical about implementing automation and where to start. Here we are, presenting a brief list of actions that are identified to be automated across banking functionalities without risking the security.
Customer Service | Compliance | Accounts Payable |
Credit Card Processing | Mortgage Processing | Fraud Detection |
KYC | General Ledger | Report Automation |
Account Closure Process | Account Orientation & Receivable | Data Entry |
Collection | Underwriter Support | Deposits & more… |
RPA in Banking - Why should you consider?
Because this is probably the only way to do-more-with-less in what feels like the slowest phase of economy. Robotic Process Automation gives you a chance to stand out in the monotonous banking sector by offering speed, quality, and unique value to your customers. Here are some of the common benefits and business outcomes witnessed by banking institutions after trying their hands on Business and Robotic Process Automation.
Scalability: This is probably the most inaccurate assumption of RPA that the bots are not scalable, and they are limited to small term processes. The truth is soft bots that are built for automation are customizable and those who have been using them for a while often take their implementation partner’s help to re-purpose the bots to support various business functions.
Improved Compliance: No matter from which country you operate, adopting an RPA bot ensures there is a clear audit trail behind each transaction and your process is always fully compliant. RPA in banking reinforces governance of automation across all processes, controls data access, ensures security, as well as administration of the environment.
Low-code and No-code: Anyone in the organization with minimum to no coding knowledge can handle an RPA bot, work with it, and monitor its performance. Unless you want to tweak the automation workflow to customize its functionality, you wouldn’t need coding. Robotic Process Automation is one of the tech mechanisms that empowers citizen developers.
Customer Experience: Unlike humans, the bots can work round the clock without getting tired. Employing a well-trained RPA bot in your customer-facing front lines of communication ensures your customer is never unanswered. When it comes to money, a customer who is well-informed and gets faster response is the happy customer.
Significant Savings: Robotic Process Automation is a great accelerator to human efforts. Recent studies and our SOPs have proved that implementation of RPA in banking can cut down the operational cost and processing time by 27% to 50% at least. Additionally, employing bots for repetitive, mundane tasks spare more time for humans to work on new innovations and tasks that require decision-making.
We were skeptical at first but when we have witnessed the turnaround time of re-pricing loans being reduced from 45 minutes to a minute, it is tough to not to love it. I guess that is one of the perks for having a technology partner who understand the limitations and ambitions too!
- Digital Automation Leader, an American-based Multinational Bank
Business Intelligence: A human might not pay attention, but a bot remembers each and every task it completed, documents it, draw patterns and recognize irregularities. So, not just completing the tasks faster without making mistakes, the RPA bots can contribute to your business intelligence.
The Qentelli way
Anyone who had a chance to associate with Qentelli would know that we have our own distinct way of engaging with our clients. Sometimes the business representatives do come with very specific solution that they want us to implement. Yet we always start the interaction with a deep assessment of the situation, identification of the apt solution, technologies that’ll support it, drafting an implementation strategy and then getting into action while monitoring the performance of the implemented solution throughout. That is probably why we have a 90%+ client retention rate since the day of inception.
Being strong believers of the efficiency that multi-functional teams bring for new tech implementations, our take on Robotic Process Integration (RPA) integration coincides with DevOps pipeline. Here’s how we approach the implementation of RPA in Banking:
Plan – Employing RPA is a bespoke program at Qentelli, and it starts with assessment and series of discussions with all the stakeholders to identify the right process to be automated. Once the predictable, automatable process is identified, it is time to assess the benefits and expected ROI from the implementation.
Design – Here is when we determine whether the selected process requires attended or unattended bot to perform the tasks. Some of the processes would just require a bot with single layer design based on its complexity and demands. Some of them would need multi-layer design architecture with various functions overlapped.
Develop – There are plethora of platforms and RPA vendors out there that offers off-the-rack solutions for many standard business processes. But when we need to roll up our sleeves to build one for a client, we follow Agile development approach with a baseline process workflow. We ensure re-usability of the automation components and top-class coding standards.
Test – We swear by Continuous Testing. To build an antifragile and change resilient bot, we execute performance and exploratory testing. We test for security, user, and operational acceptance too.
Release – The bot is automatically sent to a testing environment for user and process acceptance. This is where the team identify any bugs or issues that may arise in the targeted environment. Source code management ensures the re-usability, traceability, and customizability of the bot.
Deploy – Since bots use multiple APIs to mimic the human actions, in this stage, we create schedules, queued, or event-based triggers for specifying payload and webhook. As the bot enters the targeted environment, we set notifications for incidents and create custom alerts. In this stage we determine and set up the access control and define the users and roles.
Run – As we launch the pilot, we monitor the execution to see if it is delivering the promised speed and accuracy. We list out the identified manual exceptions and bring the decision-making personnel into the loop to create collaboration between the bot and human. We establish the real-time monitoring to evaluate pilot results.
Optimize – As the bot starts executing tasks, the results and observations are analyzed via pre-defined statistics to derive detailed reports on performance, ROI, and other metrics. Through continuous monitoring, every learning is sent back to the Planning stage which will be used for further enhancements.
The bots are ready. But are you?
When the financial chatbot specialist Unblu interviewed their customers and prospects last year, over 60% of them said that their customers are not ready for AI bots. Doesn’t it sound strange? Customers of digital age are demanding more seamless omni channel experiences from brands. Then, why would they decline a digital conversational channel that can answer the queries quicker and almost instantly? Our guess is those bots are lacking human touch. Any technological advancement to succeed, you must ensure that your intention meets your customers’ expectation.
What's ahead for RPA in Banking?
Immediate future:
- Not only large and digital-native banks but also the local and traditional banking institutions will start collaborating with technical partners and create Digital Ecosystems to offer automated and personalized solutions to each customer. Customer Categorization will become old school. Predictive Analysis will be a part of every solution strategy.
- Robotic Process Automation and Machine Learning will become crucial in know-your-customer (KYC) practices to detect fraudulent activities, mitigate compliance risks and money laundering.
- Digital Banking Innovators are most likely to create easy, effective, and emotionally rewarding digital experiences such as digital onboarding, enhanced self-service, and automated money management tools.
- RPA-powered Big Data will pick up pace in Banking. Many leading institutions are most likely to adopt dedicated Data analytics and management infrastructure which will eventually need them to build data-proficient teams. Naturally, internal decisions will be more insight driven.
RPA in Banking will have more pronounced effects in the long run. They may include:
- They might not be able to achieve it overnight, but banks are slowly moving towards Zero back-office target.
- As online banking remains one of the primary business-customer engagement channel, Mobile Banking and other digital touch points will rise their popularity to increase end-user convenience.
- Physical branches and ATMs may find some decline as the digital payment methods are climbing their way up.
- With Big Data becoming an essential practice, identifying exceptional cases, validations, and tailored solutions for each customer won’t be exhausting.
- Automation might substitute human labor, but digital elites and resources with cross-domain expertise would find their future bright.
Common challenges while implementing RPA in Banking:
The key drivers of successful implementation of RPA in Banking or any other industry are – clarity on current processes, finding the apt tool/bot, finding a committed implementation partner, and a well-documented Change Management in place. But will having all the above ensure success? I wish I can say Yes. There are a few aspects that are often underestimated but play a crucial role in determining the result of not just Robotic Process Automation but any technology adoption.
We understand that the banking industry is highly data intensive and requires a controlled and regulated environment to operate. Security is one of the biggest pitfalls for many Banking institutions to explore the technologies because there is just too much at stake. Working with one of America’s biggest multinational bank and many other organizations globally, we learnt so much about balancing the speed, efficiency, innovation while keeping security and customer experience as the main focus. It is always wise to know more before you take a call on who is the best partner for you while you take your next step of Business Transformation. If that next step is Robotic Process Automation (RPA) in your bank, you might want to have a conversation with our experts. [email protected]
