Amelia in Action

A selection of stories from organizations adopting IPsoft’s cognitive agent, Amelia

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Amelia is IPsoft’s virtual cognitive agent. Her mission is to deliver best-in-class service to customers, fully automating human-to-human interactions and process execution.

Like a human, Amelia communicates using natural language and can respond to customers’ emotional states. Unlike a human, she can hold thousands of conversations in parallel.

Why is Amelia different?

She understands everyday languageAmelia stands out from other technologies through her ability to understand natural language; not simply the words we use, but also their intended meaning. In contrast to pattern-matching platforms, Amelia can comprehend like a human to get straight to the point.

She learns quickly and gets smarterAmelia can follow process maps created from her prior interactions. And like any smart worker, she observes colleagues to discover the optimal course of action. Amelia can then apply her learning to address similar future scenarios without human intervention. If she cannot address an issue herself, she escalates to a human colleague.

She adapts to usWhereas other technologies demand that humans adapt their behavior to interact with “smart machines,” Amelia adapts to human behavior.

Episodic Memory to understand what your customer wants in context, and provide immediate answers

Meet Amelia Your first digital employee

A glimpse into Amelia’s brain

Neural Ontology to allow your customers to have a very natural conversation with Amelia

Process Ontology to execute a process for your customer in order to address their needs

EQ Ontology to enable Amelia to adapt her responses to your client’s emotional state

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During the rollout, an SEB project team member commented, “The response is always positive when we introduce Amelia to the staff. As soon as Amelia is demonstrated, the room fills with positive energy.”

Of her first 4200 conversations the majority were solved by Amelia, so agents were freed from repetitive employee queries. As for the queries Amelia cannot resolve, she observes the employee-agent interaction, learning how to deal with similar variations. Once her learnings are approved by her human supervisors she can answer these queries herself. The pilot phase also measured the ability to automate requests end-to-end by integrating Amelia with IPcenter, IPsoft’s service delivery platform. SEB had already deployed IPcenter through a long-standing contract with IPsoft, so new automations were quickly deployed. Amelia integrates securely with SEB back-end systems via IPcenter’s autonomic engine, giving her a robust platform to engage with.

By adopting Amelia in its Service Desk, SEB can improve user experience and speed up response for requests, while providing staff with time to dedicate to more complex requests.

The bank’s deployment highlights the potential of integrating digital labor, autonomics, people, processes and technology into a single system. Amelia’s performance has inspired SEB to continue the journey. The bank plans to extend Amelia on the Service Desk and incorporate support centers and customer-facing channels.

SEB, the leading Nordic corporate bank, has completed a rapid deployment of IPsoft’s cognitive virtual agent Amelia inside their IT Service Desk. The Amelia pilot rolled out in August 2016 and within three weeks handled over 700 bank employees and 4000 conversations. The project met its targets two weeks ahead of schedule.

Amelia’s role covers two internal business cases which make up 15% of the Service Desk volume: Identity Access Management and Knowledge Management. These were chosen after prioritizing 90 tasks Amelia was capable of supporting. Amelia is engaging directly with employees to:

• Unlock Active Directory accounts

• Unlock accounts for a mortgage application for home loans

• Provide password guidance

• Supply knowledge base answers to questions like ”How do I order remote access?”

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SEB, Nordic Bank IT Service Desk Agent

4

7004000conversations with

employees

in 3 weeks

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In a move to enhance customer service for more than 330,000 residents, the north London borough of Enfield is adopting Amelia.

Enfield is one of London’s largest boroughs and its population is growing by four to five thousand each year. Demand for service is growing all the time and each month the council receives 100,000 visits to its website and takes 55,000 telephone calls. Sustaining consistently high quality customer service in order to meet rising expectations 24 x 7 is challenging. This is particularly difficult when set against a backdrop of central government spending cuts. By introducing Amelia, the council expects to increase the volume of queries it manages; Amelia will be able to absorb time intensive routine requests while freeing up the time of council employees to focus on more complex issues. In short Amelia will help the council deliver more with the same resources.

In the first instance, the council plans to implement Amelia to answer general queries coming to the website — answering requests in an intelligent, non-scripted way. In addition, the council will explore how far Amelia can help in managing application processes for specific areas: for example, pre-screening planning applications and providing self-certification for those building plans that fall within specific parameters.

As Amelia works alongside the existing service channels, residents will be able to select the way of interacting with the council that best suits their personal needs.

Rather than requiring diverse visitors to be technology-literate, Enfield Council will require that their technology be “people-literate.” Given the fact that Amelia interacts using natural language, the expectation is that she will be well placed to support everyone.

Enfield’s pioneering adoption of cognitive technology is expected to set a trend for other public sector bodies both in the UK and across other regions.

Enfield CouncilPublic Service Virtual Agent

“Our approach to transformation embraces digital technology to find completely new ways of supporting residents, which, in turn, frees up valuable resources for reinvestment in front line services. Deploying IPsoft’s world-leading artificial intelligence is another major milestone in this journey.”

—James Rolfe Enfield Council Director of Finance, Resources & Customer Services

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Global Bank Mortgage Broker AgentOne leading global bank intent on seizing first-mover advantage in its digital strategy is working with IPsoft to transform key operations by incorporating Amelia. In order to test her flexibility and breadth of understanding, the bank set out a project that could demonstrate the depth of her capabilities by incorporating her into the mortgage broker advisory team.

Around the clock external mortgage brokers request information about bank products and policies. Their questions need to be answered correctly to ensure that subsequent mortgage applications are compliant and can lead to a successful approval. A fast response can make the difference between a broker selling the bank’s product or that of a competitor. By equipping Amelia to respond to queries, a bank could be sure to satisfy both requirements. Just as one would with a human agent, the first step in Amelia’s training was to assemble the data to give her the knowledge required to answer 160 of the most common queries raised by mortgage brokers. The project team then began to test her ability to manage the questions.

The questions themselves were highly challenging. For example, “My customer is self employed and has land and property income, do you take this into account?” is an interesting question for Amelia to answer as there isn’t enough information shared by the customer to match all the parameters defined for providing a response in her training.

Amelia was able to understand the underlying intent, which is to confirm the acceptable income types for a mortgage application. However, to provide an accurate response, Amelia

also needed to interpret “land and property income” as a synonym for rental income and seek clarifying information to see how this attribute might impact the mortgage types available. As a result, Amelia would ask, “Is your mortgage type residential or buy to let?” Only once this has been answered is she able to determine the answer on the basis of having established employment status, additional incomes available and purpose of mortgage.

Over the space of just two weeks, Amelia’s ability to comprehend the questions, however they were phrased, and provide the correct response, rose dramatically. At the end of the training period Amelia could answer 120 of the full 160 with an 88% success rate. The speed with which Amelia’s performance improved has now led to the bank to extend the scope of potential scenarios in which she could impact operational efficiency and revenue growth.

At the end of the training period, Amelia could answer 120 of the full 160 questions with an 88% success rate.

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be applied depending on the individual in the conversation. Upon contact using a live chat function, Amelia reconfirmed the identity of the supplier, before answering questions in the same way as a human service desk agent. Typical questions included:

• I received a payment of $512. What’s it for? • I would like to know the status of an invoice. • When will my invoice be paid?

As you would expect of a human agent, Amelia asked questions to establish exactly which invoice was being referring to. For example:

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Oil & Gas CompanyInvoice Query AgentWorking together with Accenture, IPsoft conducted a project for a large oil and gas company to assess whether Amelia could help provide a prompt and more efficient way of answering invoicing queries from suppliers. Amelia was trained in the process to respond to the top 25% of questions received from 500+ suppliers.

To provide the most effective response, Amelia was integrated into a supplier self service portal. A secure log in is required, so whenever a supplier initiated a conversation, Amelia would instantly be aware of whom she was speaking with and which organization they represented. The single sign-on approach opened up the possibility of providing personal context to every interaction and the ability to eliminate time wasting basic questions. It also allowed for varying levels of access to information to

Amelia’s estimated resolution rate was 72% in less than 8 weeks.

• What is the invoice number?• What date was the invoice issued?• What amount was the invoice for?

A warm “handover” process was established to provide the full context of the conversation taking place to a “live” agent whenever Amelia needed to escalate the query. Importantly, when a live agent joined the conversation, Amelia stayed engaged to observe the dialogue and learn what she should do in future. Although she would subsequently put forward updates to the process based on what she had observed, an SME check point was in place to allow the company to ensure that Amelia would only learn new steps that they had approved.

To roll Amelia into production, it will be necessary to give Amelia access to the company’s ERP systems where invoicing data is held so she can retrieve answers and execute next steps such as uploading an invoice. Based on the test phase Amelia’s successful resolution potential was estimated at 72% with less than 8 weeks of on the job training refinement.

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Insurance Company Digital Service Desk AgentA large US-based insurance company approached IPsoft about digital service agent integration with their support website. The company’s web support service already has more than 3,000 users a week and is growing quickly. By using Amelia, the increased demand for chat-based interactions can be met while improving customer experience. More importantly, the company sees the potential to have a positive impact on revenue growth when Amelia is involved in the initial quotes process.

Initial efforts to test Amelia’s ability to provide quotes focused on auto insurance and integrating the process with the existing India-based chat support function and relevant systems. Before providing a quote, Amelia queried and verified relevant data: for example, customer’s zip code, car model and year, homeowner’s insurance, etc. Early trials successfully integrated the client’s Amelia instance with existing APIs for quote generation to provide accurate and compliant offers to customers.

In parallel, Amelia is being trained to answer 150 FAQs that come through on a regular basis. Rather than have customers navigate unwieldy web pages in search of information, Amelia will be able to provide an accurate, near immediate response. Customer service improvement remains at the forefront of the initiative. With trials going well, the insurer is already exploring future scenarios and considering employing Amelia to assist in dental insurance applications.

Media CompanyDigital Service Desk AgentA large US-based media services organization with millions of customers across the country sought to explore the potential for Amelia to raise the bar for customer service. Together with IPsoft, the company wanted to increase the speed with which customers could receive assistance in resolving technical issues with internet, cable and telephony services. It sought to test how Amelia could be integrated into the team fielding more than 65,000 calls a month. The project placed Amelia between the first line call center agents and the third line agents with deeper technical skills. This would allow Amelia to work alongside her colleagues to shrink the time taken to respond to high-volume, repetitive questions.

Amelia was trained to manage common requests including

account unlock/reset, rate code investigations, porting a number and access requests. It took 3 months to train Amelia to respond successfully to 64% of the queries on which she was trained. Results of pre-production trials showed mean time to resolution (MTTR) drop from 18.2 minutes per query to 4.5 minutes per query. Similarly, average speed of answer waiting times fell from 55 seconds to 2 seconds.

Mean time to resolution per query dropped from 18.2 minutes to 4.5 minutes.

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In parallel, Amelia is being deployed to improve the customer service through support for the company’s customer service center and being trained in the first phase to help deal with as many as 166,500 of the monthly calls the customer service center receives. The overall goal is to improve support quality, reduce the training time for agents and reduce turnover. Amelia will help the agents understand their role, provide advice and assist their learning, especially in terms of the new systems they need to use. Overall operations efficiency will also be impacted. Amelia will route queries to the most appropriate customer service agents. The target impact is clear:

• Reduce new customer service center unlicensed agent training from 14 weeks to 10 weeks

• Reduce new customer service center licensed agent training by 4 weeks

• Reduce the average call handle time for new analysts (those that have been employed for fewer than 6 months) by more than a minute.

Insurance Company Digital Service Desk Agent

This Fortune 100 insurance company is interested in the potential of digital agents to improve efficiency of the business whilst improving customer service. After signing a contract to deploy Amelia in March 2016, the company decided to focus on training Amelia to support two initial user groups: agents who sell the company’s insurance out in the field and the firm’s existing call center agents.

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Amelia will interface with insurance agents to ensure they remain productive and can access all the technology needed to sell the company’s products. For example, Amelia will guide one of the licensed agents through installing essential software. She will help the end user work through a series of known steps to resolve the issue.

Amelia will also guide insurance agents through which forms need to be compiled and submitted. As part of the pilot underway with just under 100 field agents, Amelia is resolving common queries and integrating with other systems — most notably the company’s policy and underwriting applications and IT service management tools including ServiceNow.

Amelia is being trained to assist with as many as 166,500 calls received monthly.

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