Expectations, Competition, and a Case for Urgency

The next wave of automation in banking has been brewing for several years and COVID-19 has accelerated the focus in many areas, particularly in AI, e-identity, contactless payments, RPA and conversational solutions. Deloitte suggests the post-pandemic bank will emerge as a much different one, with greater attention on the digitization of operations and customer service automation.

The case for AI automation technologies for customer service is a strong one: improved productivity, customer satisfaction and cost savings. However, many banking decisions and processes can still be slow and manual. Complex layers impact turnaround times for core procedures from credit checks to employment verification. Mortgage and lending processes, for example, can take up to two months. Manual processing can create such delays, lead to error rates as high as 30%, and increase rework volumes due to employee fatigue and poor training.

While the value of customer service automation may be understood, and most are likely working towards implementing automation in some capacity, competition is fiercely heating up and customers are hot on the hunt for better options and better experiences. In many ways, an automation-first approach—one where automation handles all contact initially—may be the only way to drive customer service forward.

Looking at customer service differently

Banking contact centers and customer service teams face unprecedented, heightened consumer expectations. Not only do consumers today want the best rates from their banks, but they demand excellent service as well—meaning quick resolutions with 24/7 availability across all possible communication channels. Human labor and human management related challenges can be aided through automation, which is why businesses are looking at different ways to bring automation to the contact center and customer service processes.

This means automating the back and forth for both electronic and document-centric processes and then providing a customer facing interface to these processes. If a customer wants to apply for a loan, for example, they should be able to start the process online and then get status updates and information requests through their channel of choice. Traditionally, this is either done by calling in repeatedly or sending emails back and forth with whomever is helping with a loan, resulting in unnecessary manual effort that creates delays in responding to customers.

By automating the experience, the process can be accomplished through self-service. With conversational AI, customers are able to communicate through text or voice channels and interact with chatbots or voice bots using natural language. Instead of pressing a number to get to an operator, customers can simply ask for what they want and get assistance with what they need immediately without waiting on hold.

Dialogues with customers on any channel in an assisted, automated way also create a joint benefit of freeing up time for human agents, reducing the time they spend on basic status updates or requests for information.

Competing for customers beyond digital transformation

Newer banks entering the marketplace are providing innovative, self-service options as well as a myriad of other attractive features to compete with and disrupt traditional and large banks.

Many banks have built up complex systems of legacy tools, which have been deeply rooted into operational structures that aren’t flexible enough to interact with modern systems. With new Fintech and bank challengers crowding the market—cloud-based and mobile-first, digitally enabled—the tug-of-war for market share has intensified.

Challenger banks have the luxury of offering high-interest savings accounts and low-interest loan packages with little unease about funding issues long-term. They can also onboard loans that might be considered too risky for a community bank or credit union and reap the financial benefits of those loan packages.

Combined with consumer expectations, traditional banks are pressured even further. Take mortgage loan processing for example. As one of the biggest drivers for revenue at a bank, if a bank takes too long to process steps, isn’t available on the weekends or evenings, has long phone wait times, has high fees and high interest rates, this overall poor package will prompt consumers to shop around.

Conversational AI + RPA

On the customer service automation side of digital transformation, two technologies aiding banks and financial institutions are conversational AI and robotic process automation (RPA). In just the last few years, banks have found significant value in this convergence. Both employ artificial intelligence to do their job, are available 24/7/365 and add a virtual workforce to an organization that work alongside the human process owners.

Historically, automation technologies have been back-office technologies used to help with things like month-end closings. Today, automation technology is being brought into the contact center, IT, HR and other departments to automate human-to-human interactions and provide faster customer service.

RPA is used to speed up the execution of previously manual business processes. In banking, automation technologies extract or approve all the relevant loan data in seconds, validating customers from multiple sources. And for mortgage applications, data from multiple sources could be simultaneously and automatically validated to reduce delays.

Conversational AI connects people to the systems and data they need to access through a natural language interface. By speaking in their own terms, customers can ask questions without having to navigate hierarchical menus in IVR systems.

When combined, the two technologies make a compelling proposition to slim down operational costs, and drive increased profitability and customer satisfaction.

By offering self-service, Axis Bank, for example, has been able to reduce the turn-around time on savings account opening by about 90% using RPA. Citigroup, Capital One and JPMorgan Chase are currently using AI-based automation to improve efficiency like validating customer data and tracking audit trails for compliance. In 18 months, one of the largest American banks, Bank of America, was able to successfully deploy 22 robots across its front, middle, and back offices, saving the financial institution an early $100,000 per code request in operational costs.

Making an impact with automation

In the last few years there is much commonality in the use cases that are being deployed at banks and financial institutions. Banks, like most companies, are looking to automate their contact centers to improve the experience for the customer, be it with voice, web chat, SMS or a mobile application.

A recent Accenture study found that, despite digital acceleration, banks still lack the ability to achieve peak productivity from technology investments, and they must scale for future readiness. Banking executives expect AI-based technologies will not only transform their industry but will also add net gains in jobs.

As competition in banking continues to fire up, the pressure for better customer service and customer experiences only grows. Automation technologies from process automation to conversation automation can be applied in the back-office and front-office operations to enable and accelerate the future of customer service.

To learn how Roth Automation can help your bank benefit from AI automation, speak with our expert consultants today.

A Bigger Bang: Combining Conversational AI and RPA- Hyperautomation

As automation technologies mature, powerful new synergies are emerging as automation technologies are combined. This is the case with conversational AI and robotic process automation (RPA).

Extending business process automation beyond the confines of individual processes is called Hyperautomation. Combining conversational AI with RPA is one of the most promising avenues of Hyperautomation and is applicable to a wide range of business use cases that can yield dramatic results.

As Forbes notes, “Conversational AI sets the stage for a groundbreaking advance— namely the ability to leverage back-end RPA tools, applying AI and machine learning (ML) to service-oriented functions in a natural language dialog flow through the omnichannel.”

Wider Scope

To date, conversational AI has been deployed mostly in the form of chatbots on web sites for customer service applications, while RPA’s main use has been to automate repetitive back-office tasks.

Moving forward, the scope of these technologies is widening as conversational AI and RPA are combined to automate more varied and complex business processes across all areas of a business—including HR, accounting, supply chain, manufacturing, financial planning, and customer service.

How It Works

A combined conversational AI and RPA system uses speech and text recognition to trigger actions. The AI component can use natural language processing (NLP) and optical character recognition (OCR) to recognize, parse, classify, and understand meaning and sentiment in speech or text, then pass a required action to an RPA system for execution.

Intelligent process orchestration can be employed to create workflows and collaborative solutions among systems and workers. Dashboards can be created that give knowledge workers business intelligence and robotic assistants at their fingertips to surface information, analyze data, assist in decision-making, and trigger automated actions.

For example, a customer service agent at a dashboard can pull up customer information and trigger RPA bots to perform routine tasks such as mailing forms, approving claims, and sending refunds. A financial planner can use conversational AI and an RPA assistant to search for information, organize reports, test various planning scenarios, and collaborate with colleagues.

Self-Learning Systems Add Value

An advantage of AI systems is their ability to monitor, analyze, and discover further process improvements over time. Besides increasing efficiency and reducing costs, AI-based systems will work tirelessly on your behalf to discover ways to improve operations.

One way in which an AI-based RPA system can discover opportunities for improvement is by creating a digital twin of your organization. A digital twin can surface and make visible previously unseen interactions between processes, enabling new processes and workflows to be established and further efficiencies to be gained.

A Galaxy of Applications

Conversational AI and RPA systems can take many forms. Besides applications like HR and financial planning that span all industries, the use cases for combined conversational AI and RPA include industry-specific applications, such as:

• Financial services—Transfers, trades, loan origination, card activation, payment processing, fraud claims discovery.
• Healthcare—Billing, record administration, pre-op and post-op monitoring, report automation, system reconciliation.
• Insurance—Claims processing, eligibility verification, remittance, reporting.
• Manufacturing—Process control, supply-chain management, material and component acquisition, inventory management, order reconciliation, transportation, invoicing.
• Public sector—Permits, licenses, benefits applications, report generation.
• Telecommunications—Billing, installation, service, maintenance.
• Energy and utilities – Customer engagement, billing, outage response, change management.
• Retail—Customer assistance, product selection, gift recommendations, how-to information, returns, refunds, reward programs, specials planning and execution, analyze trends, reduce inventory, maximize sales.
• Life sciences—Drug and medical device R&D, application preparation, trial analysis, compliance management.

A Plethora of Benefits

A combined conversational AI and RPA system can speed operations, reduce error, eliminate manual labor, and lower costs. Added benefits are 24x7 availability in all geographies and elimination of time-consuming and expensive training of human agents.

Other benefits of combined conversational AI and RPA include the ability to:

• Eliminate barriers and bottlenecks—Working together, conversational AI and RPA can search, analyze, cross-check, and process data among disparate systems and enable the integration of systems and processes.
• Process complex data—Intelligent automation tools capture, store, manipulate, and retrieve records from unstructured sources.
• Eliminate errors—AI bots can analyze processes to maximize accuracy and reduce the number of exceptions.
• Bolster security—AI bots can monitor networks, assess threats, transmit alerts, and trigger responses to attacks and security breaches.
• Enforce compliance—Ensure adherence to government regulations, industry standards, and best practices.
• Increase customer satisfaction—When used together, conversational AI and RPA systems can enhance the ability to resolve queries and problems, assist in buying decisions, upsell and cross-sell, and personalize engagements.
• Free employees from repetitive and tedious tasks –Enable employees to devote time and energy to higher-value business activities.

Hyperautomation Foundation

As Gartner reports, combining RPA and AI technologies enables your organization to break new ground by automating undocumented processes that rely on unstructured data inputs. Through the deployment of conversational AI and RPA, you can establish the skill base and Hyperautomation foundation that will position your organization to reap the benefits of further integration of automation technologies going forward.

Why Roth Automation for Conversational AI and RPA Hyperautomation?

Roth Automation’s expert consultants and engineers have years of experience designing, deploying, and optimizing business automation processes. Our uniquely qualified specialists can assist you in accruing the maximum efficiency and cost-reduction benefits that can be gained by combining conversational AI and RPA.

To learn how your organization can benefit from conversational AI and RPA Hyperautomation, speak with our expert consultants today.

New Remedies for Healthcare Insurance Claims Processing Woes

While the first wave of document management technologies enabled healthcare insurance companies to make great strides in eliminating inefficiency in the processing of claims, these technologies could do little to alleviate the thorny problem of erroneous billing.

The new generation of advanced technologies offers new ways for healthcare insurers to overcome this costly problem by applying Intelligent Process Automation in the form of artificial intelligence (AI), machine learning, process orchestration, robotic process automation (RPA), cloud-based solutions, and more.

Massive Losses

How big is the problem of erroneous billing? Studies by Medical Billing Advocates of America, Medliminal Health Solutions, independent auditors, and other researchers found that billing errors appeared in 80% to 90% of the hospital bills.

Overbilling costs healthcare insurers an estimated $750 billion in losses annually, which amounts to about one-third of every medical dollar spent, according to an Institute of Medicine study.

Claims Processing Impediments

The inability of health insurers to catch so many overcharges stems from the large volume of complex claims and corresponding medical records that must be processed within a small window of time.

A mid-sized insurer, for example, has more than 1.5 million members and receives more than 700,000 claims from hospitals every year. Verifying whether the claims are correct requires several hundred employees sifting through claims manually to compare the medical records to the bills received.

A majority of U.S. states have “prompt pay” regulations that require payment within a specified period of time, which can be as little as 10 days. These time constraints make it impossible for auditors to catch the numerous overcharges within the thousands of claims that arrive weekly.

Because clerical workers cannot comb through the avalanche of bills and medical records fast enough to catch the majority of overcharges, they are forced to focus only on the largest claims.

Gaming the System

Knowing that insurers are forced to scrutinize only the larger expenses enables hospitals to get away with overcharging for thousands of smaller items like medicines, bandages, instruments, and ice packs.

Other billing practices that are used to inflate charges include upcoding (changing a less expensive medical code for a procedure to a more severe procedure and expensive code), unbundling (separating charges that fall under a single billing code and charging as two separate procedures), and duplicate charges (billing for procedures multiple times).

Intelligent Process Automation to the Rescue

By accelerating the speed of processing while reducing the cost, the new generation of Intelligent Process Automation technologies gives insurers the means to significantly reduce the number of billing errors that have been able to elude them because of the constraints of manual processing.

Once hospital records and claims are digitized and made machine readable, AI and advanced analytics can be applied to cross-check bills and medical records to root out billing errors in a fraction of the time it takes human workers to do so.

An AI system can be trained to identify common procedures, services, and products that are overbilled, and to compare the charges to the acceptable range of pricing for those line items.

Repetitive and tedious manual claims processing tasks can be automated with RPA technology to speed up and streamline the claims management process and eliminate clerical errors.

Automated Adjudication

Automating the adjudication process is another way for healthcare insurers to streamline and reduce the cost of claims processing. Automated adjudication systems are programmed with the appropriate rules and parameters for determining whether a claim should be paid, denied, or negotiated.

Automated adjudication systems can enable health insurers to reduce the need for human intervention by 90% or more. Claims can be processed more quickly and accurately, and the parameters can be adjusted and refined to achieve optimal results.

Gaining an AI Edge

As McKinsey & Company notes, while the benefits of automating healthcare claims processing can be significant, building an AI system is a complex undertaking that requires organizational readiness and specialized skills.

Automating health claims processing involves creating customized dictionaries and ontologies to recognize and extract information in medical records and the corresponding bills. The systems must be configured to recognize, extract, compare, and analyze information within a variety of forms, including UB-04 and CMS-1500 forms, and to recognize data such as CPT codes, ICD codes, drugs, dosages, procedures, and medical tests.

In addition, workflows, process orchestration, and integrations with various business systems must be configured, including mailroom systems, ERP systems, and any number of business planning, accounting, and financial systems.

Why Roth Automation for Healthcare Insurance Claims Automation?

Roth Automation is partnering with best of breed providers to create healthcare insurance claims automation solutions based on Conversational AI and Digital Intelligence solutions. These claims automation solutions can help insurers reduce costs up to three times lower per claim. Roth Automation’s expert consultants and developers can help you gain all the benefits in efficiency and cost-reduction that can be obtained through automated health claims processing.

To learn how your organization can benefit from healthcare insurance claims automation, speak with our expert consultants today.

Invoice Processing Efficiency  

While the business case for automating invoice processing is well-established, advanced technologies like artificial intelligence (AI), machine learning, robotic process automation (RPA), and the cloud have made the business case even more compelling.

Invoice processing is automated using Intelligent Process Automation technologies that eliminate laborious and time-consuming business processes while providing a host of productivity and cost-reduction benefits, as well as analytical insights that can inform strategic decision-making, discover market opportunities, and increase profits.

Dysfunctional Invoice Processing Takes Its Toll

The manual, unautomated method of invoice processing is a labor-intensive process that involves entering invoice data, creating paper invoices, matching purchase orders, and performing endless rounds of manual filing, routing, and storage. These manual processes tend to be wasteful, underperforming, error-prone, and incur too high a cost.

Manual invoice processing can cause delays, late fees, cash flow problems, and lost opportunities that drain resources and erode profits. Businesses also miss out on benefits that could be derived from the ability to easily analyze cash flow, follow an audit trail, cross-reference documents, and share information.

Automation a No-Brainer

The increased efficiency, productivity, and cost-saving power of invoice automation is so strong that, as Wikipedia notes, “Invoice processing software has produced tremendous labor savings to the extent that many companies have begun to consider it an essential piece of their technology, much like word processing software.”

Automating invoice processing has produced impressive results across all industries, including financial services, insurance, manufacturing, health care, utilities, retail, and transportation. Invoice processing automation has proven to be a low-risk, high-value investment, with many companies realizing immediate and long-term productivity and ROI benefits.

How Invoice Automation Works

Invoice processing automation involves transforming paper invoices into electronic formats by using scanners that digitize the paper documents and apply optical character recognition (OCR) to enable the digital documents to be read, routed, manipulated, approved, and stored electronically.

Invoice automation systems can handle paper, email, fax, and EDI formats and merge the electronic documents in a central repository. A typical invoice automation system involves the following steps:

• Invoice input (paper, email, fax, EDI)
• Document classification
• Data extraction and validation
• Workflow-driven data review, invoice routing, and approval
• ERP export, integration, and storage

The Cloud Drives Digital Transformation

The cloud is a key element of digital transformation, providing agility, flexibility, scalability, and on-demand availability to enterprise applications and data from anywhere at any time.

Although cloud platforms offer great value, some organizations might be hesitant to move particular applications and data to the cloud because of regulatory and security concerns and the need for higher quality of service levels.

Hybrid cloud strategies have emerged as a way for applications to be deployed via a mixture of private and public cloud platforms with integrated applications and data that remain on-premises.

For organizations that have yet to automate their invoice process, the maturation of the cloud and associated technologies like virtualization, containers, AI, and microservices make this an ideal time to automate invoice processing. For organizations that automated invoice processing during the first wave of solutions, migrating to the cloud offers an opportunity to up their game.

No One-Size-Fits-All Solution

Because no two businesses or business processes are exactly alike, there is no single cookie-cutter solution that can handle all the variations and address the unique needs of each organization. The number of people and steps involved, as well as the business rules that apply to the processing of documents can be staggeringly complex.

Some organizations require folders in which groups of associated documents, images, and videos can be aggregated. Some require custom document storage, presentation, access, and retrieval schemes. Still others require collaboration capabilities for documents or customer account reviews, all of which can differ in numerous ways. Invoicing operations can involve single currencies and countries, while others must be able to handle multiple nationalities and currencies.

The volume of documents and the number and different roles of people requiring access, as well as routing requirements and workflow configurations are all variables that must be addressed. Invoice indexing methods can differ, as well as the type and number of keywords used for document classification. Requirements can differ for integration with ERP systems, accounting systems, financial planning systems, and other installed systems and repositories.

Keys to Success

Choosing the right mix of components and configuring those components to match your unique business requirements is the key to achieving optimal results. Achieving the best results requires in-depth discovery to obtain the proper understanding of your business forms, routing routines, approval processes, storage requirements, and the degree of information sharing among systems.

This is why choosing the right automation solution provider is critical to success. A knowledgeable and experienced automation specialist can lead the discovery process and identify the best deployment options for your organization.

Why Roth Automation?

What sets Roth Automation apart is decades of experience in designing and deploying intelligent process automation solutions.  Our consultants and developers are experts in performing the in-depth discovery that is required to choose the best components and determine the optimal configurations for your organizations’ unique invoice processing automation needs.

To learn how your business can benefit from invoice automation, speak with our expert consultants today.

How Chatbots Speak to Thee: Let Us Count the Ways

Although many business processes can benefit from automation, the range of benefits that Conversational AI can bring to an organization is unique. At the end of the day, quality customer service is the key to retention.  A satisfied prospect or client doesn’t feel the same need to look elsewhere.  Communication and availability are the caveat to so much of this relationship.  Virtual voice agents and chatbots, ironically, can bring this relationship to life.  Benefits range from cost reduction and improved customer satisfaction to sales lead conversion increases as high as 500% to 700%.

Conversational AI can open up a wealth of game-changing opportunities in call centers, on corporate websites, and in social media presences.

New Vistas for the Call Center

Conversational AI can invigorate the call center by reducing costs and making the call center an intelligence gatherer and revenue generator rather than the cost center it has been in the past.

Unlike human agents, conversational AI agents are available 24x7 and never take time off. Customers receive immediate help rather than waiting for customer reps to be available. Conversational AI agents can supplement human agents or free them to perform higher-value tasks.

Training new human agents can be costly. Conversational AI agents can handle routine tasks such as providing product information, prices, and current specials, and can serve hundreds or thousands of customers at the same time with no wait time. For holidays, product launches, and promotions, companies can easily scale their conversational AI automation at little cost..

Because Conversational AI agents can be trained to speak any language, multi-language support can be made available round the clock, across all geographies and time zones, at scale, at far lower cost than would be required to employ geographically dispersed units of multilingual human agents.

Erasing the Bot Stigma

Through natural language understanding (NLU) and machine learning (ML), Conversational AI has become just that, a conversation.  Businesses can say goodbye to the dial in menu and allow end users to simply speak. Key word recognition becomes as seamless as speaking to a live agent.

The bot can also allow for a more satisfying handoff to a human agent.  Imagine the bot handing off your shared information to the agent to avoid the wasted time of repetition.  Workflows can be created that allow for access to necessary files, documents and data, all provided to the live agent without losing a beat.

Conversational AI is not just a solution for the enterprise.  Even smaller volume call centers can share in the benefits, creating a scalable solution for growth.  In addition, putting a quality Conversational AI platform in place does not have to break the bank.  Expenses too can scale with the effort.

Deep Savings

As Juniper Research reported,  chatbots will be responsible for saving businesses more than $8 billion annually by 2022, up from $20 million in 2017.

In the banking industry alone, Juniper Research found that the operational cost savings from using chatbots in banking will reach $7.3 billion globally by 2023.

As Forbes reported, surveys showed that business leaders saved an average of $300,000 from their chatbots, with the greatest impact occurring across support and sales teams.

Intelligence Boosts Revenues

Besides speeding up response times and increasing customer satisfaction, businesses reported that chatbots increased sales by an average of 67%.

Conversational AI agents have the ability to gather customer intelligence, personalize customer information, and apply the personalized information in customer engagements.

Intelligence gathered via chatbot engagement with customers can help businesses better understand and meet their customers’ needs, as well as reveal new product and revenue opportunities.

Conversational AI also gives businesses the opportunity to create new revenue streams by deploying customer service bots within social media messaging applications.

Customer Experience Is Key

As PwC reports, “Give customers a great experience, and they’ll buy more, be more loyal, and share their experience with friends.”

Conversational AI is a way to provide experiences that will attract and retain customers. Chatbots can provide consistently helpful information, recommendations, and advice, and can be programmed with engaging personalities that make interacting with the chatbot enjoyable for customers.

Customers increasingly are performing searches themselves, and many customers prefer self-service to phone calls and emails. AI chatbots can be engaged immediately through text messaging or speech.

Studies show that it is cheaper and more profitable to retain customers than to find and convert new customers. By increasing customer satisfaction, conversational AI can reduce churn rates and increase profitability through ongoing customer engagement, loyalty, and sales.

Why Roth Automation for Conversational AI?

Roth Automation is partnering with Cognigy to build call center solutions based on Cognigy’s world-class conversational AI platform. Cognigy solutions help businesses leverage the power of conversational AI for customer service automation that can cut contact center costs by 50% and more. With decades of automation experience, Roth Automation’s consultants and engineers will work with you to identify the best opportunities and deploy the most effective conversational AI solutions. To learn how your business can reap the benefits of conversational AI, and speak to one of our experts, click below.