There comes a point in an industry's lifecycle when it is left with no choice but to either transform itself or dissolve into oblivion. While technology disrupts every sector, some sectors are impacted much more than others. Banking, Financial Services, and Insurance (or BFSI, as we know it better) is one such sector, which is at an inflection point right now.
Here's what the BFSI sector is facing currently:
- Increased demand for digital products and services
- A rapidly changing regulatory landscape
- Reduced entry barriers for related sectors, and
- A fragile global economy
As organizations evolve to adapt to a tech-savvy environment, legacy organizations are struggling to catch the bus. It is interesting to note that retail banks rank at nine out of ten industries in terms of customers' willingness to advocate for banking services. By the way, it’s no coincidence that the highest-scoring are digital-only players.
Ironically, the solution to the BFSI sector's troubles lies right within its problem. While most banks are on their digitalization journey, their endeavors are largely restricted to a single function, which often creates silos. In such a scenario, organizations need a more integrated approach to put their house in order and this is where hyperautomation brings value.
Cometh the situation, cometh the hyperautomation!
If automation can help you automate one single task at a time, hyperautomation automates multiple or entire business processes together. Hyperautomation solutions are cohesive groups of technologies such as artificial intelligence (AI), machine learning (ML), process mining, and intelligent business process management. In the BFSI sector, hyperautomation solutions can streamline most processes across functions.
Customer service: With machine vision, banks can complete the KYC process much more quickly. In some cases, AI-based visual inspection platforms can replace the manual verification process entirely. When customers open a bank account using a smartphone via a selfie or a video call, that’s machine vision at customer service!
Hyperautomation solutions can mine customer information, including text and images, and can map them to the relevant fields required for KYC. This increases accuracy and reduces processing time. It also aids customer convenience and helps banks by letting them deploy their human resources to more critical work. With Natural language Processing (NLP), banks can read and interpret the content of customer emails and messages to eliminate the activities that would need manual intervention. What’s more, NLP models can further identify the function responsible for the service sought by the customer and the type of service.
An ML-based solution can reduce the average handling time of document processing and error rate while extracting information from different sources. Such a solution can extract data from complex tables, images, and free text. It can then present this information through intelligent UX to a human agent for verification and validation. Banks can integrate hyperautomation solutions with their existing ecosystem to work seamlessly and more effectively across several IT platforms and interfaces.
Emails: HyperEmail automation solutions can extract the meaning and intent of emails received including reading the attachment details via OCR. Based on the email content, the platform can take necessary action without human intervention. Some areas of application include order management and service requests. And no, automation of emails doesn’t end just there; organizations can use it to stay in touch with current customers and convert prospective customers with relevant and consistent content. For personalized content, organizations can leverage AI and ML solutions to customize content for multiple customers.
Insurance: Hyperautomation applications can be extended to most parts of the insurance process - from customer acquisition to underwriting to servicing candidate claims settlement. Insurers can use AI-based underwriting systems for quicker decisions and ML-based algorithms to select the right product and price for customers as per their profile and historical analysis. Companies can utilize intelligent document processing to extract, segregate, process, and analyze the data accurately.
With machine vision, organizations can assess whether the damage was accidental or done fraudulently. Cameras can capture the defects visually, and the visual data can be converted and processed using specific software to understand the type and extent of the damage. For instance, when it comes to house property insurance, machine vision models can validate the current state of the house exteriors and paint jobs. When an insurance agent needs to provide a quotation, immediately viewing property features data might drastically improve quote speed and accuracy since the traditional method is to schedule physical inspections.
This helps the insurers to monitor client portfolios and test the accuracy of the information and data being shared by the clients. In some cases, machine vision models can eliminate the need for human inspectors, bringing down the costs and allowing them time for more strategic tasks.
Fraud: For verification requirements, banks can process details much more quickly, as data from the physical documents is extracted through ICR and OCR technologies. Customer risk profiles can be verified and consolidated from multiple sources with the help of ML-based solutions. These solutions pull details from various sources much faster, resulting in quicker turnaround time, adding speed-to-solution with banking services. Understanding the digital behavior of every customer helps relationship managers better acquaint themselves with their clients and reduces the overall risk component. Automation models further improve accuracy in processes such as loan underwriting analysis, thus eliminating any possible human bias. During mergers and acquisitions, hyperautomation models can bring harmony to ensure that the multiple legacy systems work in sync with each other, reducing the need for human intervention and minimizing the chances of errors. A possible hyperautomation model for preventing fraud in banks and insurance would look something like this:
- The proposed hyperautomation solution begins with data extraction from various sources, external or internal, with robotic process automation.
- Once extraction is complete, ML models can check for anomalies in customer profiles and transactions history.
- The model then uses core analytics for prescriptive and descriptive analysis of the information.
- Based on the analysis, it generates a notification to the compliance team. If the process requires additional documentation for completion, a bot sends a notification to the customer.
With a blend of multiple technologies, this solution streamlines the entire process and increases efficiency at a minimal cost.
Regulatory reporting: Regulatory reporting is another banking function with immense scope for automation. Banks can leverage automation and cognitive intelligence (CI) capabilities to increase process accuracy without burdening their resources. Automation can streamline activities such as data sourcing, cleansing, and validation. Organizations can use cognitive technologies such as NLP and natural language generation (NLG) beyond simply preparing reports to review tasks performed by quality assurance and audit teams.
While many banks and other financial institutions have already begun deploying automation for efficient regulatory reporting, most of the deployment has been ad-hoc. It is now time for these organizations to opt for a more integrated approach with hyperautomation.
No size fits all
Each technology, be it NLP, machine vision, or RPA, comes with its benefits. But what puts the ‘hyper’ in ‘hyperautomation’ is the integration of these technologies for a better outcome. It has immense scope in the BFSI sector, promising improved productivity, increased profits, and customer experience. But it is not a panacea that can fix all the problems with a magic wand. For any automation project to reap the desired results, the technological goals and business goals must be aligned well. Organizations must then choose the right technology from various products and educate employees and other stakeholders on the expected changes in the future, to avoid any reluctance or resistance later.
How can Nagarro help?
Organizations are automating many repetitive activities using RPA and related digital technologies. However, these technologies can only handle simple tasks. When we bring together AI, Machine Learning, Machine Vision, and Natural Languages Processing under the hyperautomation umbrella - a whole new set of complex activities can be automated bringing significant scale and speed to business workflows. Nagarro offers a set of hyperautomation solutions that use advanced AI technologies that are Cloud-enabled to automate and augment business processes.
Our Hyperautomation solutions include Document Mining Platforms, Defect Assessment Platforms, Process Mining Platforms, and many more that can bring a lot of cost savings and efficiencies for different types of businesses. We can help integrate these technologies through our hyperautomation solutions to address your organization's problems. For a tech partner that brings you technical expertise with a touch of CARING, reach out to us.