INTELLIGENT REPORT AUTOMATIONInsights on Demand

Today’s finance and compliance teams have a tremendous opportunity to leverage intelligent automation to cut costs and drive efficiency gains by leveraging new technologies to automate more than 50% of data-driven tasks.1

1 Digital Finance: Beyond the Hype, Accenture 2018. Access at: https://www.accenture.com/_acnmedia/PDF-90/Accenture-Beyond-the-Hype-PoV.pdf#zoom=50.

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Natural Language Generation (NLG) software is one of the technologies that can greatly impact the bottom line by automating repetitive, time-consuming reporting workflows, from performing analysis to writing commentary, while improving the speed, consistency and quality of reporting.

In many functions within the enterprise, employees spend a significant portion of their day pulling data, deriving insights and subsequently producing some form of written or visual output to be delivered to an audience that can use those insights to make decisions. These tasks typically are repetitive in nature within a reporting workflow or involve building out bespoke visualizations and dashboards. Many organizations have a heavy reporting load along with strict regulatory requirements and with a lack of resources to address both concerns.

These organizations typically have two options:

Increase the workforce – by using full-time equivalents (FTEs) or outsourcing. Adding to the workforce is costly and not easy to scale and may not be a favorable choice given continuing pressures to keep costs down.

Leverage NLG to automate and improve current reporting. This technology can ingest data and apply company-specific business logic to produce reports identical to what the organization writes today. This increases capacity, allowing teams to focus on higher-value work.

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NLG: The Key to Large Scale Transformation

The reporting problem spans functions, with every area of a financial services organization having to analyze and report on some type of data. NLG technology can ingest structured data and generate a written output in plain English. The software perfectly mimics the steps a human would take to analyze data, identify key insights and then articulate and author a report—all of which can be customized and formatted to fit the requirements of the business.

Accenture is working with a Chicago-based software company, Narrative Science Inc., to bring their Intelligent Automation platform, Quill™, into Accenture’s suite of solutions to drive large-scale transformation. Narrative Science’s Quill™ allows enterprises to build custom NLG applications to save time by automating complex data analysis, providing more insightful reporting and increasing reader engagement.

The platform is configured to the custom logic, language and formatting of the company’s reporting. Because it can be configured to mimic the tone and voice of the organization, reports generated are indistinguishable from those written by data-driven teams.

Once Quill™ is configured and trained based on the company’s reporting requirements, it acts as an authoring engine to automatically produce reports to meet those exact requirements each time a dataset is sent to it. This engine can be deployed across a number of areas (such as on-premise, Software as a Services (SaaS), or through a virtual private cloud), and the content can be embedded as required, so that there is no need to change any current workflows or valuable reporting methodologies.

In addition to leveraging custom NLG solutions, Quill™ offers native extensions for organizations that use business intelligence (BI) tools for reporting. These tools embed automated summaries directly into the company’s reporting dashboard. The extensions are architected precisely for large enterprise teams to scale NLG across all dashboards and users, eliminating the need for interpretation or calculation, as Quill™ produces the relevant insights from dashboards in plain English. Many organizations have dashboards that not every stakeholder has the skills or time to properly interpret; NLG fills that gap, surfacing the relevant information and making the visualization more powerful and more accessible to a wider audience. As seen in Figure 1, Quill’s platform helps turn data into easy-to-understand narratives.

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Figure 1. How data becomes narrative

Source: Narrative Science, 2020

StoriesPlain-English stories that make an organization’s data easily understood by everyone on the team.

Relevancy FrameworkUsing artificial intelligence powered technology, Narrative Science surfaces, explains, and contextualizes what is interesting and relevant to an organization.

NLG EngineUsing Narrative Science’s NLG engine, QuillTM efficiently writes content that takes humans hours or days to generate today.

AnalyticsThe proprietary analytical framework analyzes an organization’s data to discover valuable information and surfaces only the meaningful insights.

DataAn organization’s data has a story to tell – starting with the insights waiting to be uncovered. Narrative Science can ingest data from almost any source.

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High Return on Investment (ROI) Use Cases for Finance and Risk

Both financial and regulatory reporting share three common pain points that NLG can help eliminate:

Bandwidth Issues

There are not enough hours in the day to keep up with reporting demand. Not only is hiring additional FTEs costly, but finding the appropriate people can be hard due to the ‘talent war’ occurring in the market for skilled analysts, investigators and other key positions. Resource constraints on reporting may expose an organization to risk.

Lack of Consistency

Establishing consistency in reporting across a large organization is nearly impossible, particularly with a growing set of regulations that can differ across geographies, sectors and business units. The consistency and quality of reporting can have a tremendous impact on the organization’s ability to drive better outcomes downstream.

Not Enough Time for High-Value Analysis

Historical reporting tasks are relatively simple and often repetitive. Employees should be thinking and planning strategically for the future, rather than executing basic reporting processes.

High ROI use cases for report automation are those which have a repetitive workflow that require reporting consistency, quality and speed. For example, in a typical profit and loss reporting process, financial services companies spend tens of thousands of hours a year putting together weekly analysis for regions, countries, divisions, and branches, all of which could be completed with great precision and quickly by a custom NLG engine.

Enterprises can be assured they are getting the same analysis week to week, as the engine uses the same business logic each time and gets the results as soon as the data is ready. The NLG engine is able to author the report in seconds, and according to Accenture and Narrative Science’s experience, can reduce manual effort in the reporting process by more than 80%. The organization is able to look on a continuous basis at real-time financial insights, rather than waiting for the current reporting workflow. NLG allows the organization to think less about producing a report and more about making decisions based on that report.

Another high-value area in which we see NLG’s value applied is anti-money laundering (AML). Investigators often spend hours on every transaction alert flagged as suspicious, analyzing what the alert was, potential related transactions, the customer’s history and other aspects of the transaction. Instead of having

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investigators sift through hundreds of data points, an NLG solution can write a summary of the alert along with related activity and customer history, so that the investigator has immediate access to all the information they require as well as an auditable record of what was looked at during their review. This is a step few banks have time to execute today. With NLG doing the baseline analysis and writing up insights for investigators, banks can expect the time to make a decision to be reduced by more than 60%, freeing up investigators to spend time on higher value or more skilled tasks.

Additionally, if an investigation leads to an open case, an NLG engine can write the formal narrative required from regulators, thus helping meet the regulatory reporting standards. Investigators are still able to make edits as appropriate before submitting any final forms, but the baseline created by NLG can save them a significant amount of time.

Figure 2 below identifies additional use cases for NLG.

Finance Use Cases Compliance Use Cases Audit Use Cases

Balance Sheet Know Your Customer Enterprise Issue Management

Profit and Loss Transaction Monitoring Alerts Enhanced Due Diligence

Collections Suspicious Activity Reporting Case Management

Cash Flow Liquidity Reporting Counterparty Risk Reporting

Out-of-the-Box Business Intelligence Extensions

Tableau Software, Inc.

QlikTech International AB

Microsoft Power BI™

MicroStrategy Incorporated

Domo, Inc. and more

Source: Accenture September 2019

Figure 2. High value use cases for reporting automation

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Getting Started with NLG

However, each involves creating data-driven reports utilizing the organization business methodology. Enterprises start by identifying use cases for NLG, essentially any data-driven report that is based upon a repeatable logic. Once this report or list of reports is identified, an evaluation of the business case and applicability is completed using Accenture’s NLG framework.

Companies often start by building out a business case for NLG. Talking through how the automation can impact or transform the current state is a crucial point in creating an effective NLG solution. In parallel, it is critical to discuss how this technology can become a capability within the organization in order to scale the impact and transform whole functions.

The move to automated reporting helps functions become more data-driven and focused on the high-value thinking that creates a shift in focus, from putting together historical insights to putting together courses of action for forward-looking change.

Whether an enterprise wants to start with a strategic assessment of use cases, building out data connectors and workflow specifications, or configuring NLG applications, Accenture can assist in the process. Deployment strategy is customized and prioritized according to the organization’s highest-value reporting initiatives, supporting the accelerated adoption and capturing higher ROI on NLG technology.

All engagements are unique based on the client and complexity of the use case and reporting workflow.

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Benefits of Intelligent Report Automation

The deployment of NLG to automate reporting workflows can deliver short and long-term benefits including:

Time and Cost Savings

Intelligent report automation with NLG allows finance and compliance teams to dramatically reduce the time needed to run their teams. Headcount is then removed from the workflow and/or re-deployed to forward-thinking strategic projects.

Report Consistency and Quality Improvements

The Quill™ reporting engine never skips a beat and allows for precise identification of exactly how an insight was composed. Reports can be hyper-targeted to a specific stakeholder group and can be trusted for consistency in language and logic across the organization.

Self-Service Analysis

NLG on-demand insights empower business owners to find answers to their questions and explore data, scaling expertise through those insights and creating a more data-driven culture and better decision-making.

Increased Effectiveness of Business Intelligence Tools

The Quill™ native business intelligence extensions provide plain-English summaries that embed directly into dashboards. The summaries reduce the time it takes to interpret a dashboard and drive overall engagement and adoption of business intelligence investment.

Traceability

Quill™ is a deterministic software, which means that correct behavior can be defined, enforced and audited. The technology is transparent in showing the user how it turns data into plain English in a highly customized yet predictable way. This is tremendously important for financial and compliance teams due to the strict regulations and communication protocols required.

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Learn MoreRecognizing a financial organization’s pain points and the opportunities for intelligent report automation is a major step on the path to digital transformation. There are multiple ways to roll out natural language generation, depending on the organization’s appetite and readiness. Accenture and Narrative Science can help determine what that roadmap should look like and how to start realizing impactful returns.

To learn more about intelligent report automation, contact our NLG specialists:

Contact UsSabina Munnelly Managing Director Accenture Financial Services Technology Advisory sabina.munnelly@accenture.com

Pablo Vazquez Senior Manager Accenture Financial Services Technology Advisory pablo.vazquez@accenture.com

Gretta Hermes Manager Accenture Financial Services Technology Advisory gretta.hermes@accenture.com

Stu KendallProduct Marketing Narrative Science skendall@narrativescience.com

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Narrative Sciencenarrativescience.com

https://www.linkedin.com/company/ narrative-science/

twitter.com/narrativesci

www.facebook.com/NarrativeScience

About AccentureAccenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these services. We combine unmatched experience and specialized capabilities across more than 40 industries—powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. With 505,000 people serving clients in more than 120 countries, Accenture brings continuous innovation to help clients improve their performance and create lasting value across their enterprises. Visit us at www.accenture.com.

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Accenture and its logo are registered trademarks of Accenture. 191186

About Narrative ScienceNarrative Science is a data storytelling company that writes stories from business data to drive understanding and results. Powered by artificial intelligence, our technology automatically turns data into easy-to-understand reports, transforms statistics into stories, and converts numbers into knowledge.

Narrative Science works with customers, including Mastercard, USAA, Envestnet, and members of the U.S intelligence community, empowering them to understand and act on critical metrics, make better decisions, and focus talent on higher-value tasks.

DisclaimerThis document is intended for general informational purposes only and does not take into account the reader’s specific circumstances and may not reflect the most current developments. Accenture and Narrative Science disclaims, to the fullest extent permitted by applicable law, any and all liability for the accuracy and completeness of the information in this document and for any acts or omissions made based on such information. Accenture and Narrative Science do not provide legal, regulatory, audit, or tax advice. Readers are responsible for obtaining such advice from their own legal counsel or other licensed professionals.

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