INTELLIGENT ROBOTS ENABLE SEAMLESS SERVICING OF CUSTOMER REQUESTS AT A GLOBAL LIFE AND ANNUITIES FIRM

CONTACT CENTER EXPERTISE ARTIFICIAL INTELLIGENCE

DIGITAL INTELLIGENCE

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CASE STUDY

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INTELLIGENT ROBOTS ENABLE SEAMLESS SERVICING OF CUSTOMER REQUESTS AT A GLOBAL LIFE AND ANNUITIES FIRM

Inefficient hand-offs and occasional miscommunication between the

front-office and the back-office can cause inordinate delays in closing

customer requests, leaving customers dissatisfied and angry about the

delay. This was the challenge faced by EXL’s client, one of the world’s

largest life and annuities companies offering its services across 30+

nations.

EXL had been managing back office operations for the firm for several

years. On any given day, several policy holders of the client reach out

to their contact centers for various kinds of service requests. The front-

office staff at the contact centers types out these requests in free-form

text during the conversation, then passes them on to the back-office

for servicing. The back-office was then responsible for pulling up the

relevant records, noting down or updating information as needed, and

sending out customized correspondence to the customers.

However, at times errors or omissions would be made by the front-

office staff while noting down the requests. This would then require

the back-office to revert for clarifications. The back-and-forth would

delay completion of the service request, thereby decreasing customer

satisfaction. Further, because the back-office was processing requests

manually, the overall servicing timelines were quite stretched.

With customers used to the fast pace of today’s digital world, they no

longer accepted old-world inefficiencies in customer service. So, the

client reached out to EXL to implement cutting-edge technologies that

would speed up back-office timelines, providing more leeway for the

occasional hand-off issues between the front- and back-offices.

EXL approached this challenge with Digital Intelligence, its strategy

towards digital transformation. First, the context of the problem is

understood by drawing on the company’s deep domain expertise in

combination with process related data. Then, the right mix of digital

technologies and professionals are precisely orchestrated to deliver

impactful outcomes.

“ Inefficient hand-offs and occasional miscommunication between the front-office and the back-office can cause inordinate delays in closing customer requests, leaving customers dissatisfied and angry about the delay.”

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INTELLIGENT ROBOTS ENABLE SEAMLESS SERVICING OF CUSTOMER REQUESTS AT A GLOBAL LIFE AND ANNUITIES FIRM

Context With several years of experience in managing the client’s back-office,

EXL already had in-depth knowledge of the client’s back-office

processes. In these processes, the team would manually examine the

free-form text sent by the front-office to determine the type of service

the customer was requesting and select the communication template

to be used. The templates had predetermined fields to be populated

with the relevant details pertaining to the request. The team would fill in

these fields by referring to the client’s records database, perform other

necessary actions such as updating records or processing payments,

and then send out the response letter to the customer. All of this

required browsing through hundreds of screens to find the handful of

fields required to be used in the communication.

To speed up this manual and time-consuming process, EXL set out

to build a natural language processing (NLP) engine that would

automatically read and understand free-form text sent by the front-

office staff. EXL would also deploy robots to automatically carry out the

relevant processing commands generated by the NLP engine.

OrchestrationTo automatically process free-form service request texts, the NLP

engine requires a keyword dictionary of frequently occurring words

and phrases. EXL deployed a team of business analysts to spend six

weeks with the process associates on the operations floor to observe

and document their actions. The outcome of this exercise was a

comprehensive keyword dictionary that linked key terms and phrases to

the process steps needed.

While the dictionary development was underway, three developers built

an NLP engine which could automatically parse free-form text using

the keyword dictionary and generate the necessary process-related

commands. In parallel, other developers worked on configuring four

robots that would be able to automatically perform the necessary steps

to service requests basis the commands from the NLP engine.

Further, the solution also incorporated an analytics algorithm that

studies historical patterns in customer service requests, and predicts

the probabilities of when the next such similar requests are likely to

come in. For example, tax gain quote statement requests from some

customers of a particular American state are likely to come in at a

particular time of year based on that state’s regulations. Thus, the digital

bots can proactively send out such statements, even before customers

request them means a proactive communication rather than reactive.

The solution also takes care of frequently changing federal regulations

which require updating customer correspondence templates. The

earlier manual process sometimes mistakenly sent out correspondence

based on outdated templates. Customers would then need to get

in touch with the contact center asking for the missing information

required by new regulations. With automation, the bots are now

responsible for version control of the templates. When a federal

regulation change notification is sent by the client, the bots mark any

related requests as exceptions, which are not serviced until the relevant

templates have been updated.

After the solution was rolled out, the EXL developers are working on

further refinements. A ‘spy bot’ is being built that will observe the

occasional requests that the NLP engine cannot deal with and flags

as exceptions. This bot, using assisted machine learning technology,

will observe the steps taken by human agents while servicing such

exceptions and automatically update the keyword dictionary. Thus,

similar requests in future can be serviced automatically without

human intervention.

Supporting these teams in the background, the EXL governance

team interfaced with the client’s IT department, to overcome policy

challenges relating to systems interfacing and deployment of the

technology in the back-office.

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OutcomesWith the NLP engine — which has a 96% accuracy rate — driving the

digital bots, back-office operations are cruising in overdrive. Over 40%

of the requests coming in through the contact center and through

emails are completely automated. With absolutely no human touch

points for these requests, there is a 15-20% reduction in processing

errors. This has reduced the need for customers to repeatedly reach

out to the contact center and has also significantly improved the

average servicing turn-around time.

All of these factors as well as the bots’ proactive prediction and

servicing of requests have contributed towards a greatly improved

Net Promoter Score, our client’s metric for measuring customer

satisfaction. As a bonus, the 30-40% increase in in efficiency delivered

by the bots working around-the-clock has contributed $200,000 to

the bottom-line through the elimination of 4.5 FTEs. Cutting-edge

digital technology can not only delight the customer, but also deliver

powerful business outcomes.

INTELLIGENT ROBOTS ENABLE SEAMLESS SERVICING OF CUSTOMER REQUESTS AT A GLOBAL LIFE AND ANNUITIES FIRM

EXL (NASDAQ: EXLS) is a leading operations management and analytics company that designs and enables agile, customer-centric operating models to help clients improve their revenue growth and profitability. Our delivery model provides market-leading business outcomes using EXL’s proprietary Business EXLerator Framework®, cutting-edge analytics, digital transformation and domain expertise. At EXL, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation and logistics industries. Headquartered in New York, New York, EXL has more than 27,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), South America, Australia and South Africa.

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Client Challenge

• Inefficient hand-offs between the front- and back-office

• Stretched servicing timelines because of manual processes

• Customer dissatisfaction due to delays in closing service requests

Context

• EXL had in-depth knowledge of client processes

• EXL solutioning included the components of an NLP engine and a digital workforce

Orchestration

• Business analysts built a keyword dictionary for the NLP engine through observing manual processes

• NLP engine built using Microsoft.NET

• Digital workforce deployed through configuring four bots

• Governance team overcame challenges related to IT policies and systems

Outcomes

• Over 40% of back-office processing completely automated

• 15-20% reduction in processing errors

• Greatly improved customer satisfaction scores

• 30-40% gains in efficiency

• Savings of $200,000 through elimination of 4.5 FTEs

SOLUTION SUMMARY

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