Robotic Process Automation in Insurance Industry

RPA) applies specific technologies to automate routine, standardized tasks in support of an enterprise’s knowledge workers. By freeing human employees from these mundane tasks to apply themselves to core business objectives, RPA offers a number of compelling benefits to the workplace.
– Institute for Robotic Process Automation (IRPA)

Robotic Process Automation (RPA) seems to be now crossing over the hype cycle and delivering real-world benefits in driving efficiencies, leaner processes and reducing costs and errors in processing of massive amount of demand or data driven processing systems that traditionally had a lot of human effort invested in mundane tasks.

Let us take a look at some real-life business solution areas in Insurance that RPA has been able to address successfully over the last year.

Insurance has some very key areas that are time consuming, data intensive as well as customer contact center based. Lot of human effort is spent on data gathering, collating data from multiple system, updating systems with changes or new data and validating and processing.
Based on data and case studies shared by various RPA Tool implementations, here are the areas in insurance where RPA has demonstrated successful implementations:

• Claims Registrations: RPA has improved time for claim registration process by at least 50%.The contact center has saved at least half the time it took for each claim registration to be registered and updated.
• Credit Note Refunds: RPA implementation improved the overall time and cost for Credit Note Refund process. On an average for the same number of transactions, it reduced the processing time to 1/5^th and the same throughput achieved through 1/4^th of the processing staff.
• Approval for Credit Note Refunds: With the implementation of RPA, the Credit note Approval process delivered 50% more efficiency with 75% less manpower.
• Cancellation of Policies: RPA implementation improved the cancellation process massively. For the same amount of transactions, the current process delivers in 1/3^rd of the time with 1/9^th of the earlier processing staff.
• Registration of Forms: RPA implementations improved forms registration process by 40% with half the number of staff.
• NCD (No Claims Discount) Verification: Pre- RPA, the NCD validation manually took about 10 mins. Post RPA, after the agent uploads the details, the BOTs can verify and flag mismatches within 2 minutes for the same number of applicants.
• Policy Issuance: Policy Issuance is a time consuming exercise and can take more than a week for the process to be completed manually. RPA implementation has reduced the effort at all stages and in the post RPA world, policies are issued in less than 2 days.

The above benefits highlight the success of RPA.

The RPA Bots have been able to:

1. Download Data
2. Scan and Read Data
3. Upload / Enter Data in key systems
4. Verify Insurance period / NCD and flag mismatches
5. Provide approvals
6. Create follow-up emails / alerts
7. Collate Data from various systems by logging in and provide a 360 degree view to contact center staff.

Though there are still limitations on how RPA can be effective, (mostly hardware/mechanical and OCR related), there are many new research and tools that are scaling up to overcome these limitations.

Given the real-world benefits, beyond the hype delivered by RPA, it is bound to spread into other business areas. With incremental improvements in Artificial Intelligence (AI) and cognitive systems, RPA implementations can only improve to deliver more benefits. The limiting factor is most likely to be how organizations and society are geared up for these changes and respond to them.

Robotic Process Automation (RPA) and Enhanced Customer Experience

In my last blog I talked about how, Robotic Process Automation leads to changing job roles and it’s effect on employees and employers. I take the opportunity to highlight the great multiplier effect a successful effect RPA implementation has on customer experience.

A customer journey can be simple set of tasks or a complex journey. It could involve looking up information, filling information, time taken for processing forms or those long holds on telephone. Whatever be the forms of these journeys, we had some such poor experiences. This is where a successfully implemented RPA and related investments can enhance customer experience and eliminate customer pain points.

How RPA transforms Customer Experience?

As an example let us consider the customer journey for Loan or mortgage origination and processing. Traditionally it will require the customer to fill up many forms and information and submit required sets of documents. These would then be sent for processing. Someone would re-enter the details (with possible errors), then back-office managers will do checks (credit scores, property details, etc) and sent for approvals. Some of these work may be outsourced to 3^rd parties (lack of proper controls / audits). The overall process itself takes a few weeks for the customer to get a feedback on status of his loan approval.

If an RPA is successfully implemented, the BOT can take over the complete process – from uploading the scanned documents, verified e-signatures, verification and checks and scores for automatic approval or rejection recommendations with complete audit trail. The turn-around time has seen to be reduced to a few days days (conditional approvals to as less as 1 hour) and customers can track their application stages and status online. This not only creates a beneficial customer experience, but allows the Mortgage provider to invest these savings in front line / customer facing resources – which along with RPA will drive up revenue as well as customer experience. 

Metrics and continuous improvement

Organizations can set-up metrics to measure customer experience (number of complaints, changes, rework, etc) and work on a continuous improvement plan for customer experience journey. The comparison could be made between pre and post-RPA implementation metrics. It will clearly bear out the investment in RPA and the subsequent investments in direct customer touch-points had improved the overall experience.

RPA is not an end in itself to improvements in customer experience. A continuous improvement plan will need improvements and maintenance of BOTS. Automated systems will encounter “exceptions” (due to change in processes or new data sets being introduced) and organizations would need to maintain the BOTS as well as carry out Quality control.

RPA and New Jobs

A few months ago I had written about the impact of RPA on traditional back-office and rule based activities performed by humans.

The key impacts that are evidenced in various industries and by analysts are:

•          Jobs that had been traditionally “out-sourced” or “off-shored” are brought “in-house” or “right-shored”. This is evident in many “off-shored” or “out-sourced” services being bought back “in-house” or moved back to developed countries and economies.

•          The skill-sets needed for fulfilling the replaced jobs are not same as those that are being replaced. The new jobs are more to support and maintain the RPA. As an example if the “bot” hits an error in the process, it alerts for human intervention. This requires task to be performed by “specialized” human support, maintenance and QA – a new set of job roles.

Who benefits?

·         Employers benefit from lower costs, higher efficiency and less errors. This savings in-turn can be invested to focus on better “customer experience activities” and a more focused “customer centric” approach to business operations. In combination with Big Data, Business Analytics and Natural Language Processing, this will drive better customer services and lay the roadmap for future “cognitive” technology implementations.

·         Employees benefit from a new set of job roles that are specialized in nature and not “repetitive” in nature. There is an ample scope of people being trained on new analytics and data mining technologies that will help drive the future growth of individuals as well as organizations. More jobs will open up in area of direct customer interaction and providing better “customer experience” that machines cannot yet replicate in the near future.

The disruptions looks scary and has an impact in the short term. However, newer sectors of job roles opening up will make it more interesting for workers as well as helping organizations run better customer centric experiences.

Intelligent Automation, Robotic Process Automation and it’s impact

In my last blog I touched upon Intelligent Automation broadly covering Machine Learning, Autonomics, Machine / Computer Vision and Natural Language Processing.

I will focus on Autonomics and it’s impact on business and IT. Autonomics are intelligent systems that apply self-adapting policies to “learn” from experience and respond to new conditions, with the potential to perform more and more complex tasks.

Autonomics are entering the mainstream in back-office work performing high volumes and routine tasks. It is predicted that it will completely transform the Business Process Outsourcing (BPO) industry. However, the current systems are not “autonomics” in the truest sense but are evolving and will reach that stage in the near future.

Traditionally robots revolutionized the manufacturing industry largely in the context of assembly lines. Now Robotics Process Automation (RPA) is impacting the back office and process related work in the same way. Whereas in manufacturing, physical robots replaced workers doing repetitive tasks, in the office world, software automation ( termed as RPA) is replacing many of the repetitive tasks and associated jobs.

RPA is most effective where:

-          ·     Actions are consistently and steps repeatedly
·         Data is template based and data entered repeatedly in the same fields
·         Applications are rule-based

Many organizations have started to use it effectively across many functions but not limited to:

•          Data entry and validation
•          File and data manipulation
•          Automated formatting
•          Multi-format message creation
•          UI manipulation
•          Web scraping
•          Text mining
•          Uploading and exporting
•          Downloading and importing
•          Workflow acceleration
•          Currency/Exchange rate processing
•          Reconciliations   

Other than the horizontal / generic functions listed above some notable usage has been across specific industry verticals like:

·         Regulatory Compliance for Financial Services – RPA solutions not only address the regulatory compliance, by performing the function in the same way repeatedly but provides a detailed and sustainable audit log of activities – important requirement for compliance. Also the tools can be scaled easily as well as “learn” to perform new processes as they are introduced by regulatory agencies.

·         Mortgage Loan Processing – RPA tools execute routine rules-based tasks and therefore provide increased and accurate loan processing experience. By applying rule-based algorithms RPA tools resolve errors and increase speed through the loan origination systems. Also RPA tools can “learn” to analyze data in the applications and recommend cross-selling of other products to the customers like insurance, savings instruments, etc

·         Telecom Sector – Telecom providers need to switch circuits based on customer movement. However some of the decommissioning work requires verification from multiple systems and third party circuits and sources. Traditionally these have been resource intensive requiring multiple steps and checkpoints. RPA tools are providing increased efficiency as most of this process is rule based.

This is still evolving and with more cognitive and Artificial Intelligence built in, the RPA tools are becoming smarter. The impact is felt across many industries not limited to BPO only, not to mention the impact on jobs and change of roles and skills.

The robots have arrived in “white-collar” jobs!! Humans need to adapt to the new reality and create new jobs and skill sets to work with the robots. Humans have always adapted and though the near term future may have some pain, in the long term it will benefit all in moving away from repetitive jobs.

As the saying goes "Change is the only constant!!!"

Intelligent Automation – coming of age

By 2019, the global market for content analytics, discovery and cognitive systems software is projected to reach $9.2 billion, according to IDC, more than double that of 2014.

Intelligent automation is rapidly coming of age. “Smart” machines and “smart” systems and “smart” bots are becoming mainstream.Intelligent automation which is a combination of Artificial Intelligence (AI) and automation is mainstream now. It is helping businesses to achieve higher levels of efficiencies. The range of applications could be from collecting simple data to making contextual decisions to guiding autonomous vehicles.

Intelligent Automation broadly covers Machine Learning, Autonomics, Machine / Computer Vision and Natural Language Processing.

Machine Learning – refers to the ability of systems to improve their performance by exposure to data without explicit programs or instructions. It is the ability to automatically discover patterns in data and carry out predictions. These applications can potentially improve performance through systems that generate lot of data and over time. Typical mainstream usages of Machine Learning systems are in fraud detection, sales forecasting, Oil and Gas Explorations and Public Health Management (predicting and containing outbreaks)

Autonomics – refers to systems that are designed to perform routine tasks and processes by humans. The technology interfaces with existing applications to process transactions and trigger responses. The system typically goes through two phases – Learning and Executing Phases. The machine-learning software programs ‘observe’ how a trained user takes decisions or resolve issues and replicates the same ‘decision making’ process. Autonomics are entering the mainstream in back-office work performing high volumes and routine tasks. It is predicted that it will completely transform the Business Process Outsourcing (BPO) industry.

Machine / Computer Vision – refers the ability of machines or computers to identify objects, scenes, activities as images. The sequence of image processing leads to break down the observations to smaller tasks analyze and decide. These applications have become mainstream most famously through Facebook – face recognition software. The mainstream usages are in security area and fraud detection activities. Identifying forged bank notes or criminals has gone mainstream with these technologies.

Natural Language Processing (NLP) – refers to the ability of computers to interpret human language in the proper context to take appropriate actions. The mainstream application is most popular through application like Siri offered on iPhone / iPad devices. Dictionary usages, uses in Museums as well are more query response based. Translation and internationalization are also catching up.

The applications of intelligent automation are already coming of age and mainstream in our daily lives. We are interacting with more intelligent systems that are combining all the above intelligent platforms.

Advances in artificial intelligence, robotics and automation are becoming important for companies in all sector to understand the impact and adopt intelligent automation or risk falling behind.

I will try and cover that in my next blog on autonomics and its impact.

IoT impact on Financial Technology Sector – Will customer experience win over “brand value”?

Projections

Gartner, Inc. forecasts that 6.4 billion connected things will be in use worldwide in 2016, up 30 percent from 2015, and will reach 20.8 billion by 2020. In 2016, 5.5 million new things will get connected every day.

Gartner estimates that the Internet of Things (IoT) will support total services spending of $235 billion in 2016, up 22 percent from 2015. Services are dominated by the professional category (in which businesses contract with external providers in order to design, install and operate IoT systems), however connectivity services (through communications service providers) and consumer services will grow at a faster pace.

Implications

IoT services will become the real drivers and value add. Service providers and vendors which will provide integration to third party applications will become the critical part in the value chain. Those service providers that provide the best value in terms of customer experience will win market share.

Customer experience vs brand value?

The financial sector is heavily dependent on exchange of “data” on a large scale for normal operations. IoT by it’s nature itself will increase it many times more. It is therefore imperative that like manufacturing, retail, energy, transportation, etc, financial sector will be disrupted in a major way by this new “technology revolution”.

Retail banking experience is the obvious choice. How can retail banks make the ATM experience more engaging? Can the smartwatch and smart- wallets be connected to provide an enhanced experience? Walking into an ATM or bank can be a different customized experience for each customer based on his needs (Like many retail stores). One need not slot in the debit card in the ATM, proximity sensors or authenticated messages from my smart watch or wallet can authenticate and dispense the required services.

Data mined from various IoT sources can provide customized experience to the end user. Walking into a car dealership, the connected banks can send provide customized interest rate and contextual offerings on models that I searched online.   

The Mortgage industry can adopt the same customer experience. Real estate agents and builders are already providing VR (Virtual Reality) experiences on the property. Mortgage industry can exploit these date to provide customized loans. With e-documents and e-signatures also being adopted, the experience becomes smoother. The connectivity could move across the whole lifecycle from real estate agents, mortgage providers, movers and interior designers to local authorities and utilities. A mortgage provider providing such a connected experience will hands down against an established brand.

The same connected experience (“Smart Homes”) can be extended to home insurance. Homes with updated fire systems and burglar alarms connected to emergency systems are already being provided with customized home and fire insurances.

Connected cars (cars with telemetry) are already allowing car insurance providers to reward or punish drivers based on their driving habits.

IoT by it’s nature and underlying value makes static objects more engaging by interaction of data. Therefore it is imperative that “customer experience” will overtake brand values and pricing in customer decisions.

Impact of Internet of Things (IoT) on Financial Services

Internet of Things (IoT) is having a huge impact on business models and systems around the world. IoT in simple terms can be explained as devices that have been given the ability to collect data and communicate with each other. It implies that devices can collect and transmit the data they capture. This means that insights can be obtained at granular level to create specific inputs or analyzed for a “larger picture” effect.

Data available in public domain from analysts and industry research indicate an exponential growth in such interconnected systems and revenue impact of the same:

•          Cisco estimates the IoT market to be $19 Trillion
•          McKinsey Global Institute expects the IoT will deliver revenues of $6.2 Trillion by 2025

The financial services is largely impacted by IoT. The impact across different financial services sectors as per industry findings are shown below:

  

The highest impact is seen in insurance, followed by commercial real estate and banking. With more wearables, connected cars and connected healthcare, insurance sector is the biggest benefactor. However the impact is all across. The recent tie-up between Samsung and MasterCard is a good example of how it can help in banking and retail. As an example, based on the data shared by your Samsung refrigerator or Samsung washing machine, it may be time to replace / repair. These data can then allow MasterCard to send you personalized offerings on extending credit for a purchase based on your portfolio and lifestyle.

In insurance it is more obvious, from your lifestyle to driving habits, your insurance offer can be suited to your behavior and habits.

Some of the key impacts that financial services industry would need to consider would be around some of these key issues:

1.      

•       Identity Management  – With spread of devices across home and offices it would to identify the users. Same device may be used by multiple users, like a car or treadmill. Identifying the right user will be challenge and traditional forms of identification may not work.
•              Privacy – In line with identity management will be the challenge to manage data privacy. The data is collected across a whole range of device will create own sets of risk. This will call for new policies and processes around data privacy and there may be still many unknowns in this area.
•           Security – Tied to the above two aspects are security policies and mechanism. Data shared over multiple devices and medium are prone to be hacked or manipulated. This can impact the end user services. There needs to be standards developed and agreed for these. Also the question will be who is liable for or pays for which part of the data security domain. Is the Bank or insurance company liable for data leakages inside my home or from my car?

Other than the above critical impacts, issues of inter-operability standards, reliability and collaboration between devices and their impacts on services will be an important consideration. The technical standards may be easy to resolve or address, the challenge will be to determine the contextual relevance of the data. Which in turn means how much of intelligence resides on the device and how much on a central system?

Though the proliferation of IoT devices is without doubt in the financial sector, it would seem that the impact has not yet been assessed. The systems and models are likely to evolve along with the requirement, but the speed of change will be very quick. Those who start early will benefit.