The allowance for loan and lease losses ("ALLL") is considered as one of the most important estimates in an institution's financial statement and regulatory reporting. Each institution is required to develop a comprehensive, systematic and consistently applied process to determine the ALLL amount.

Recent regulatory guidance requires financial institutions to transition from the current incurred loss credit impairment model to a more forward-looking loan loss reserve recognition process.

Under the new loan loss reserve model, a financial institution would recognize the loss allowance equal to the current estimate of expected credit losses of its financial assets as of the end of the reporting period. Accenture has developed an expected loss framework to help financial institutions meet recent regulatory requirements.

Key features

• ALLL amounts definition based on empirical data and under a controlled environment.
• Data-driven results through a robust quantitative methodology.
• Real-time analysis and adjustments.
• Different ALLL scenarios can be compared across segments and time horizons.

While detecting refund fraud and reducing losses is a key goal for audit managers in public service organizations, conducting a detailed analysis of audit claims information is usually difficult, time consuming and expensive to do.

To help auditors quickly identify and stop improper behavior involving refunds, Accenture's Audit Operations Efficiency application for Public Service covers the end-to-end fraud detection process—from creating risk models that detect risky cases, to analyzing claim data to determine if it is fraudulent, to closing out the investigation. And it provides managers with insights that help them to identify risky refund claim behavior and take action.

Key features

• Risk indicator for each business rule at all levels to integrate the industry knowledge
• Ability to manage events / transactions
• Ability to manage real-time monitoring and alerting logic

In a competitive market, telecommunications providers are pressed to win customers and meet margin targets. And with the increasing amount of data - sales performance by category and reference, competitor prices, and promotional data -- telecommunications companies can better determine appropriate pricing policies.

Accenture Analytics' Bundle Pricing is the advanced analytics application designed to help telecommunication companies determine bundle pricing options to meet business objectives and identify the best strategies to increase profitability and market share.

The application can support marketing and inventory decision-making. For the marketing team, the application performs competitive analysis to better understand customer preferences. For the inventory team, it can help users to understand the optimal inventory level for each handset, performing store level forecasts at granular level.

Key features

• Accurate store level forecasting to maintain optimum inventory level
• Competitive analysis to understand customer preferences
• Analysis at granular level to understand product level price elasticity

The contact center is one of the key points of contact between telecommunications companies and their customers. Its proper management is also linked to the complexity of workforce management

The Call Volume Forecaster application meets the planning and management needs of the contact center. The application provides forecasts for traffic planning down to the individual contact level up to the business aggregate level. These forecasts help define the right staffing resource and skill mix for each day and time slot, improving service levels and therefore increasing customer satisfaction, loyalty and brand perception.

Key features

• Get the best inbound-calls load prediction for one or more call centers
• Predicts the call load by type of call and type of customer
• Get accurate, timely and usable hourly forecasts
• Takes all available information into account in order to get the best prediction

In the insurance market, it is crucial for claims managers to have as much information as possible to spot fraudulent behavior and to identify possible networks of fraudsters among counterparties, dealers and other parties involved in the business.

To offer assistance in navigating challenges related to claims fraud, Accenture designed an application to help insurance companies use data and analytics to identify fraudulent activities and reduce costs connected to fraud.

The application uses predictive modeling and also allows users to assess all risk factors thanks to a library of business rules that are specific for the insurance industry.

Key features

• End-to-end and business outcome focused.
• Modular approach.
• No black box. Business fully enabled.
• Insight-driven to enable ease of change management.
• NBA focus—a way to standardize investigation best practice.
• Open to any analytics tool and skillset.

In the Utilities industry, missing payments by customers are increasingly frequent and recovery activities are intensifying to help reduce the amount of loss to the company.

Accenture Analytics' Credit Collection application is designed to improve the profitability of utility companies by reducing their financial risk. Its insights help to maximize the value of the recovery and give an overview of the claim status and the likelihood for recovery. This advanced analytics application supports the business user in selecting the best contact method, identifying the claims that are best suited for follow-up action through a third party.

Key features

• Identification of high-risk customers and the potential exposed value
• Assignment of a customer specific risk score
• Prioritized customer specific plans identifying the best action to maximize the recovery value.
• End-to-end processing

Energy industry portfolio managers and traders operate in energy markets internationally to maximize revenues from cross-border trading activity, taking advantage of the different prices of gas, oil and power in various markets and time horizons.

The Cross-Border Trading Optimization is a fast and reliable app that optimizes the short term position in order to catch market opportunities, maximizing revenues and profitability. It provides portfolio managers and traders with a tool that integrates and collects data from multiple systems into a single environment, leading to better and faster decision making.

Key features

• Optimize profit & loss: Location spreads, time spreads and capacity optimization.
• Simulate extra Injection/Withdrawal on storages.
• Optimizing respecting constraints: Monthly targets, Market liquidity, Transfer capacity, contractual minimum and maximum.
• Manage scenarios: Create, compare, update and revise different what-if scenarios.
• Flexible and Real Time Reporting: Base Market Position, Optimized Market Position, Unused Capacity, Monthly Target Follow-up, Asset Flexibility, Dispatching Priorities List, Storage Levels.

In the financial services industry, customer expectations are rising, but customer confidence continues to fall. Losing a customer means losing an important asset, and the cost of reacquiring that asset is high.

Accenture has developed an application to help identify early signs of customer defection, so that businesses can take retention actions before the customer is lost. This predictive tool provides a contact list to the sales force, reducing the effort and increasing the rates of customers processed.

Key features

• Industry-specific, pre-defined attrition triggers
• Unified churn definition
• No black box. Business fully enabled
• Insight-driven to enable ease of change management
• NBA focus - a way to standardize churn best practice
• Standardized data-driven approach for measuring campaign effectiveness
• Standardized data-driven approach for churn treatment (e.g. by segment, value)

Financial companies want to retain high-value customers, so it's important to take the right actions to increase cross-selling, retention and marginality.

CRM managers often have an inadequate understanding of customer value, because the segmentation is usually based only on current financial assets. Furthermore, segmentation is usually updated only once a year, while customers change more often.

Accenture Analytics' Customer Potential application allows users to analyze actual and potential value for the customer base, exploiting customers that are not expressing their full potential, in an effort to drive marketing and sales actions.

Key features

• Industry-specific KPIs to define actual and potential value.
• Actual and potential value calculated and updated every month, for each customer.
• Definition of the contact channel based on the customer profile/ preferences and on value.
• Standardized, data-driven approach for campaign effectiveness.

The electricity market is characterized by a large amount of data and data sources. The interaction with these data sources is a key problem for market operators.

Data Management is the application that allows businesses to manage consumption data for the resources market. The tool accurately and easily maps the technical structure of the network and the contractual relationships with end customers and infrastructure, enabling users to prepare and analyze the energy balance, taking into account different levels of transportation and local distribution.

Key features

• Data storage and organization in an energy management context
• Data management: Supply sites, contracts, customers
• Data Acquisition Layer: Data import/export, loading of withdrawal data (hourly curves, monthly/two-hourly/three-hourly curves, Standard formats (XLS) and market)
• Load profiling data acquisition
• Monitoring of withdrawal trends and their composition in the year and in relation to the different time bands
• Data management and extraction at different levels of aggregation of supplies and time frames: Per month and peak/off-peak. Per contract or customer. Per groups of sites
• Management of withdrawal historical data with alert concerning the state of availability of data

Banks often face various challenges related to the early warnings process—the process that monitors credits (loans, mortgages, etc.) to identify the potential non-payers and offers an early warning on this potentially risky customer activity. These challenges are usually related to having the credit and risk activities scattered throughout different platforms and business unit silos.

Accenture Analytics' Early Warnings application offers an end-to-end environment for early warning process management. It helps risk managers to easily manage client data coming from multiple sources— such as external bureaus or providers—by applying business rules and predictive models to all of the data so early warnings of potentially risky behavior may be identified.

Key features

• Flexibility of methodology for the Warning Score elaboration
• Classification Models provide accurate and intuitive scoring
• Risk Matrix accepts risk scores from multiple sources

Energy companies have witnessed growing fraudulent behavior, with customers illegally attaching to distribution networks, leading to losses and accounting troubles. Detecting fraud and reducing losses is a key goal for audit managers of energy companies.

Accenture Analytics' Energy Fraud Detection is the advanced analytics application that helps utilities identify risks of fraud or improper behavior resulting in losses.

Key features

• Use of all available information to fight fraud
• Real-time checking and scoring
• Alert, e-mail, and report management based on deterministic rules
• Predictive models for customers or risk score

Because of tight regulations, the natural gas market requires accurate forecasts. For users of the National Gas Pipeline, an error in the daily schedule of withdrawals for each point of delivery to the network operator can cause significant imbalanced costs.

Forecaster Gas is designed to meet the forecasting needs of the gas market. It provides daily withdrawal estimates and monthly planning per point of delivery, and offers a full range of functions, graphics and indicators for a valid and simple management of the forecasting process.

Key features

• State-of-the-art statistical forecasting methods
• Statistical KPIs
• Automated modeling
• Stepwise selection, self-identification
• Modeling logic based on meter clustering
• More

The resources market has unique demand forecasting challenges, like the need to submit detailed forecasts to grid operators, or the need to operate on the day ahead market. Measures come from thousands of meter devices, producing hourly—or even more detailed—time series.

Customer behaviors differ markedly: Production schedules drive industrial electricity usage, while domestic usage is sensitive to temperature, so different load curves need to be treated in the most appropriate way. A poorly accurate load forecast can lead to very expensive unbalancing.

Accenture Forecaster Power advanced analytics application meets the needs of short- and medium-term forecasting for the energy market. It provides demand forecasting with hourly detail for each point of delivery, or it aggregates on different time frames, according to the needs of the energy market. Forecaster helps users to examine the energy demand forecasting to verify the quality of the result, and to operate by exceptions only on points that do not perform in an optimal way.

Key features

• Profiles for new customers
• Unbalancing economics KPI
• State-of-the-art statistical forecasting methods
• Statistical KPIs
• Automated modeling
• Stepwise selection, self-identification
• Modeling logic based on meter clustering
• KPI-driven intervention strategy

The need for accurate planning of energy generation is increasing, complicated by the types of generation involved. With complex behaviors, each generation reacts differently according to different weather conditions. This challenge impacts the energy generation area of the company, but the forecasting problem has many points in common with the forecasting activities already managed by sales portfolio forecasting.

The Accenture Forecaster Renewables advanced analytics application implements forecasting models for the generation of power from renewable sources. The application is based on time series models, regression models, neural networks and hybrid models that manage the necessary weather drivers.

The combination of sophisticated models with updated information and drivers provides very accurate results, thus overcoming the forecasting problem for such complex systems.

Key features

• State-of-the-art statistical forecasting methods
• Statistical KPIs
• Automated modeling
• Stepwise selection, self-identification
• Modeling logic based on meter clustering
• KPI-driven intervention strategy
• KPI for accuracy assessment
• Alerts
• Automatic building of weather and calendar driver
• NDM treatment
• Modeling for direct TSO customers

When sales networks do not function, organizations can experience heavy losses. Detecting fraud and reducing losses is a key goal for retail audit managers, but detailed analysis of available information can be difficult and expensive, especially considering the large volume of transactions, the size of the network and the detail recorded (including movement of the drawers of the boxes in the stores). It's critical to quickly identify and stop improper behavior, but it's also necessary to identify new behavior and risks that were not previously associated with losses.

The Accenture Fraud Detection analytics application identifies risks of fraud or improper behavior resulting in losses. Through a mix of business rules, anomaly detection and predictive analytics that identify risky behavior, the application can assign a fraud risk score to any event.

The application contains a predefined set of business rules related to the retail market. Users can add new rules according to their experience, and their business knowledge, to spot new unethical behavior. The application adds anomaly detection, predictive analysis and social network analysis (SNA) to the business rules for better predictive detection

Key features

• Business rules at all levels (store, cashier, retail)
• Risk matrix
• Clustering and anomaly detection
• Anomaly indices and risk scores
• Risk drivers and impact analysis
• New rules from anomaly detection algorithms
• Ability to manage events / transaction ("fraud" label assigned by the user)
• Predictive models
• Social Network Analysis at multiple levels
• Ability to manage real-time monitoring and alerting logic

IT supports the entire decision-making process, from the mapping of assets to simulating the impact of future application scenarios. Analytics insights provide short-term indications that highlight the systems and subsystems already under stress, and also medium- and long-term scenarios in which users must manage application scenarios, the rollout of project activities and migrations. Once the IT manager defines a strategy, the application supports him or her with ad hoc reports that help to validate decisions and actions.

The Accenture Analytics IT Governance application supports companies in the optimization and improvement of IT resource efficiency, even when transitioning to virtualized environments.

Key features

• Registry of systems and subsystems
• Historical series of workload data relating to CPUs, clusters, servers, MIPS
• Automatic data acquisition, historical depth and configurable time granularity of data
• Scheduled forecast refresh
• Statistical techniques of reference (ARIMA; ARMAX; AREG; EXSMOOTH)
• Automatic modeling
• Data available at different granularity levels
• Simulation of aggregations and rationalization of installations or machines used
• Personalized alerts
• Maintenance planning

The electricity market has two main objectives: promote, while remaining neutral, the transparency, objectivity and competitiveness of the activities of the electricity supply chain, and guarantee the management - in economic terms - of the distribution of services.

Accenture Analytics Market Interface is the application that supports the companies that operate in the electricity market in the management of market operations. In particular, the interface allows users to operate in real time in day-ahead, intra-day or ancillary services markets. The forward electricity account trading platform interface allows users to manage and automate the communication information flows of bilateral contracts with their commercial obligations and injection and withdrawal schedules.

Key features

• Management of data concerning: day-ahead market transaction, consumption/production units, OTC and forward contracts
• Ability to aggregate data by: period, date, status, classification (sent, accepted, cancelled, rejected)
• Creation of a day-ahead market plan based on the forecast data
• Creation of an ancillary services market plan and evaluation of the operations: production unit input, offers on the day-ahead market, maximum availability plans
• Platforms supported: day-ahead market, intra-day market and ancillary services market
• Transactions performed according to Market Operator criteria: day-ahead market- intra-day, ancillary services, balancing market offer, functional acknowledgment, offer notification
• XML format for transactions

In the big data era, companies are no longer suffering from a lack of data, but they do struggle in identifying the right data to make better, faster business decisions.

Accenture has applied predictive analytics and approaches to enterprise network management, helping clients diagnose, transform, operate, and innovate while simultaneously enabling significant savings, mitigating security and business interruption risks, and uncovering entirely new uses of the network.

The Network Predictive Fault Management application helps telecommunications companies reduce costs connected to maintenance and upgrade plans by optimizing the content and the sequence of interventions. It predicts network incidents before they occur, allowing pre-emptive maintenance and improving service assurance. It also provides operational insights to IT Managers giving them visibility on network vulnerabilities and recommendations for proactive maintenance of the network infrastructure.

Key features

• Maps the organization network, including all types of devices, technical teams, service levels
• Maps complex geographies, allowing different users to collaborate in a single framework
• Predicts more accurate maintenance, optimizing the intervention plan with a more proactive approach

The increased intensity of retention activities and the need to meet sales targets have led to considerable pressure on customers in the financial services market. What's more, limiting the number of contacts a customer can receive by phone or mail within a given period of time means that each name becomes a valuable source of information in terms of proposition of an offering.

Accenture Analytics's Next Best application allows marketing professionals to identify the best product to suggest based on the probability of purchase and profitability of the product itself. Cross selling for every customer can increase loyalty, maximizing both margins and sales. Next Best takes full advantage of every interaction with the customer, and offers the sales force a chance to have correct information to close deal: Customer profile and propensity to purchase.

Key features

• State-of-the-art predictive methods
• Logistic regressions
• CRT, QUEST, CHAID trees
• Outliers detection
• Automated management of blind period
• Cross-selling and local loyalty indicators
• Automated data preparation
• Automated modeling
• Default parameters
• Partitioning/sampling
• Performance measurement
• Campaign RO

The shippers need a ready-made application that includes the balancing process, validation and sending of daily programs to the Transport System Operator. Before sending the nominations via needed protocol, the user must perform the so-called balancing of the program: The energy injected into the network, plus the storage energy (injected or withdrawn) must equal the withdrawal from the network.

Nomination Interface is the application for gas that meets the need to balance the transport network withdrawal program, daily nominations and Virtual Point balancing. Nomination Interface is able to offer the business user a balancing program that uses the demand forecasts per single point of delivery and the parameters concerning procurement contracts, entry capacity, capacity of Regional Networks and points of delivery, as well as transactions already recorded at Virtual Point.

Key features

• Transport network withdrawal program
• Modification and validation of daily nominations
• Proposes a balanced program using the storage
• X12, SL-ATR, SCTD, Kiss-A protocols
• Proposes an unbalanced program for the gas day
• Allows the user to balance the program using the Virtual Point
• Generates the corresponding Virtual Point transaction

In the increasingly competitive resources market, medium- and long-term planning is key to improve efficiency and increase productivity. This activity focuses on the analysis of procurement sources and of possible trading scenarios.

Accenture Analytics' Portfolio application is designed to support procurement decisions in the resource market. It interfaces directly with the management of customer portfolios and offers the possibility to include prospects without a final contract. Customer management is completed by the segmentation function, which produces the portfolio control matrix. The trading simulation functions allow the user to work on any part of its contracts and easily change the number, composition and expected withdrawal. Each hypothesis, after having been assessed and validated, can be used to create the open position.

Key features

• Open Position: Breakdown of the position per period and standard products, indicators for any set of contracts (per platform, pricing formula, deal or sub-portfolio)
• Mark to Market: Breakdown per period and standard products, definition of price benchmark
• Invoicing amounts: Receivables/payables by supplier, contract type and pricing formula
• Contract management for any frequency and time frame
• Management of pricing formulas (fixed, index-linked, bsld)
• Definition of indexing formulas
• Management of commodities
• More

The creation of a new product in the Energy market requires a vast amount of information including historical quotes and forward price of energy commodities, price trends and related indexing, customers demand and terms of supply contracts. Tools to analyze this data must be extremely flexible to support custom formulas and strategy.

Accenture Analytic's Pricing for Utilities application is designed to assist Sales in building a line of effective products, by dynamically comparing formulas with user-customizable benchmarks and by analyzing the profitability of formulas on different customer segments. This holistic application allows for the comparison of alternative pricing, formulas and supply costs and allows for that information to be integrated into existing workflows within the sales department, who will take advantage of the output data provided by the application to define pricing, having time to focus on maximizing margins.

Key features

• Pricing: Enables the Sales Force to easily calculate the optimal pricing for all clients
• Outstanding Risk Probability: Allows the Risk Manager to calculate a risk score for each client
• Unbalancing Risk and Cost: Helps the Risk Manager to calculate the unbalancing cost related to every single client
• Hedging Cost Fee: Allows the Portfolio Manager to calculate hedging cost at a client level
• Price and Demand Forecasting: Allows the Portfolio Manager to forecast the expected price of the commodity and the expected demand for each client

Credit risk has always been one of the top issues in financial services, and there's a growing need to automate procedures to help manage the ever-increasing workload that risk offices face. To ensure responsive and efficient management of credit scoring, it is essential to quickly develop and deploy grids of acceptance that are reliable, accurate, automated and based on advanced analytics applications.

Accenture Analytics' Real Time Credit Decision application helps banks and financial institutions with managing end-to-end development of credit acceptance models. The app allows users to develop and execute scoring grids and business rules, with features to support every need, such as analyzing data quality, binning of continuous variables, selection of historical depth to be used for sampling and more.

Key features

• Testing and simulation of possible impacts before running campaigns.
• Flexible approach to define segments and actions.
• Credit risk matrix allows users to summarize different credit scores for each client.
• A comprehensive and analytically oriented data model.
• End-to-end and focused on business outcomes, from generating credit scores to defining target campaigns.
• Modular approach that allows users to grow at their own pace.
• Insight-driven, making for easier change management.

In the ultra-competitive telecommunications market, it's imperative to be quick in testing, accurate in defining actions and reactive in defining tactic responses to competitors' actions. Effective control requires timely and accurate forecasts of traffic and resulting revenues, so the need to get detailed forecasts by type of service, direction and components of revenue (fixed, variable) makes the process more complex. Manual management is extremely difficult and time-consuming.

Accenture Analytics' Revenue Forecaster application reduces the effort to prepare data that often reside on different systems, and it automates the forecasting process. In this way, users involved in control activities can use their time to find interesting patterns, highlight issues and propose corrective actions. It allows forecasting revenues in the Telco market at the desired detail level.

Key features

• State-of-the-art statistical forecasting methods (Arima, Armax, AREG, Exponential)
• Flexible forecast horizon
• Management of seasonality and calendar events
• Wizard-guided processes
• Auto modeling to identify the top-performing algorithms on each series
• Scheduling of all operations, from data loading to forecast production
• KPIs at every level (service, type of customer, direction)
• Treatment of different tariff plans
• Traffic and revenue forecasts for all service types (Voice, Data, Services SMS, MMS, VAS)
• Ability to include internal competitors' information (Promotional activities, availability of new plans / services, network issues, communication campaigns)

As deceptive schemes increase and morph quickly to stay under the radar, public service organizations need a cost-effective way to detect fraud. The Accenture Analytics' Revenue Fraud Prediction application is an innovative and robust advanced analytics solution for accelerating value-added tax (VAT) fraud detection.

The application leverages Accenture's established methodology for advanced fraud analytics while providing a visual experience. Data science or model managers can improve audit efficiency and effectiveness for their organizations by gaining increased insight into operations and key performance indicators using various analytical tools, including rules, networks and predictive models. With a heightened awareness and understanding of model performance, model managers can take swifter corrective action to help optimize the detection process.

Key features

• Prioritized cases for VAT refund fraud investigation based on advanced analytics
• Built-in visualizations with logical touch points, helping to bring data to life for business user interaction during model development
• Automated data ingestion and integration for focusing development time instead on analysis and insight generation

Energy companies have multiplied their offerings to customers, with an increase in fixed price options, index-linked offers based on specific customer needs or offers as a discount on authority tariff. These actions have resulted in a growing asymmetry between formulas used in the sales portfolio and those used in the purchase one. The awareness of the price risk financial exposure, which was already growing in the market due to the competitive context, is now very topical.

The Accenture Analytics' Risk Management analytics application starts from the open position, which determines the national price risk exposure. The methodological heart of the process is very complex: Volatility estimation methods, Montecarlo simulation algorithms and synthetic risk indicators such as VaR make it possible to summarize the exposures and possible future trends of raw materials (or of the single national price) into synthetic indicators. When an exposure, which is outside the parameters set, is identified, a simulation of coverage operations is carried out (by formula, commodity, portfolio or distribution) to identify the most suitable choice to bring the indicator toward a safe value.

Key features

• Net exposure: Volumes by purchase and sale formulas and breakdown per commodities
• Commodities management
• Management of hedging contracts: SWAP contracts and CfD and IDEX contracts for power and commodities
• Financial Open Position Report: Self-hedging and final position after portfolio hedging
• Montecarlo simulation: Commodities and Market Prices
• Hedging What If: Formula/commodities SWAP, CfD, Energy Derivatives

The process of spare parts demand planning is a key success factor for any business managing inventory. Actively collecting and analyzing sales data, verifying production plans and identifying collateral conditions and assumptions without an automated process can drain resources. A manual approach lacks accuracy, leads to forecasting errors, and generates overstock or inventory shortages.

The Accenture Analytics' Spare Parts Inventory Optimization application provides accurate demand forecasts for thousands of units, taking into account the amount of stocked items, the lead time for each individual component, the life cycle of the products and other factors, such as replacements and phase-in / phase-out. It then manages all the elements needed to get an accurate and reliable forecast. The application allows the enterprise to efficiently manage and control the whole process of forecasting and production of components. When integrated with the Safety Stock component you gain the ability to update intra-period forecasts and notification of stock level or lead time anomalies for single components.

Key features

• Take into account Spare Parts peculiarities
• Safety stock management
• Drive restock decisions
• Minimize the statistical know-how required
• Produce accurate forecasts for thousands of SKU's

Reducing public spending remains a high priority for many governments, and forecasts suggest that spending will continue to fall during the next few years. Auditor-controller agencies and departments need to improve product vendor cost and compliance management, implementing policies to favor more economical vendor selections.

The Accenture Analytics' Spend Optimizer application facilitates the development and management of policies through a step-by-step guide and rules creation functionality. The application empowers users to decide which policies to apply, using a "what-if" simulation capability which helps to advise regarding the most cost-effective spend allocation based on a fixed budget. Compliance monitoring can help ensure that both vendors and the departments stay within policy spending limits. The application also helps reduce the time and complexity around managing future spending based on supply and demand trends.

Key features

• Preconfigured business rules engine for establishing product or vendor groupings before simulations
• Scenario management for taking into account different strategies on spending policies related to department vendors
• Algorithms for calculating differences in spending among groups to help determine optimal levels
• Ability to create and manage different spending policies for multiple business levels
• Comprehensive solution for helping to address the end-to-end process

Telecommunication companies are perpetually fending off fraud. The ability to identify and trace new anomalous behaviors through continuous monitoring is vital for companies to take preemptive actions against future costly occurrences of fraud.

The Telco Predictive Fraud Detection application helps company audit managers identify anomalous behaviors to reduce fraud risk exposure through real-time monitoring of preset business rules and advanced analytics. The application analyzes internal company data and external data to help determine the risk factors and level associated with each service user. Audit managers receive alert notifications about anomalous behaviors that may pose a fraud risk, using customized logics based on their control targets.

Key features

• Management of business rules for facilitating integration of existing business experience.
• Use of historical data comparisons for identifying new fraudulent behaviors.
• Identification of anomalous connections posing high fraud risk.

The Trade Marketing Activities Optimization Application supports sales force allocation, allowing users to optimize the planning of future trade marketing activities by considering past performance along with business capacity and constraints.

The application allows users to identify and select the right activities and points of sale for annual initiatives, while also accounting for adequate sales force staffing and resource constraints. Now, It is possible to design and test many scenarios to understand the best solution.

Key features

• Initiative dashboard to analyze field force capacity, touch points capacity and activities mix effectiveness for each initiative.
• ​Activity dashboard to explain where each activity contributes in which initiative and touch point type, in terms of volume contribution to the overall volume targets.

Measuring trade marketing impact on sales is a challenge. When executing trade activities, marketers may experience a time delay on the impact on sales. Moreover, a sales increase can result not only from trade activities, but also from multiple contacts, multiple influencers and unpredictable, extraneous variables.

The Trade Marketing Impact Measurement Application is a Web-based solution that allows trade marketing professionals to assess and quantify the impact of trade marketing activities. It delivers accurate estimates of the impact that single trade activities have on sales. By examining past performance, it sheds light on halo/cannibalization, optimal duration and Touch Point best profiles.

The application quantifies the impact of the factors driving sales, taking into account external and macroeconomic factors as well as estimating the baseline, volume not dependent from the activities execution or the external factors. The app makes it simple to visualize the results of complex models and drill down the uplift by quarter, region and brand.

Key features

• Simple to use as it hides the advanced analytics complexity.
• A proven statistical model developed by the Accenture Advanced Analytics Center of Excellence statistical team.
• Fast and easy Web access.
• Up-to-date with quarterly refreshes.

Reducing risk exposure from misconduct remains a top challenge for firms in the financial services industry. Conventional risk management processes employed today, however, are largely inadequate when it comes to heading off financial misconduct.

The Accenture Analytics' Trade Surveillance application helps arm risk managers with a more comprehensive surveillance management capability by augmenting an organization's existing surveillance competencies with risk detection enablement. The application analyzes structured, semi-structured and unstructured data across disparate sourcesfrom company text and voice-based communications to social media to human resources-specific data. Applying analytics and thresholds for risk to these data sources helps prioritize and focus investigations concerning suspect and unauthorized behavior.

Key features

• Improved visibility and detection for reducing exposures to trader, employee or insider misconduct.
• Integrated solution augmenting existing competencies for a more robust in-house surveillance capability.

When processing warranty claims, manufacturers are usually using legacy systems that have limited automated validation and reporting functionalities, poor data quality and require data to be analyzed manually. As a result, manufacturers detect and correct warranty issues too late. This negatively impacts financials, brand image and customer experiences.

The Accenture Analytics' Warranty Analytics application helps warranty managers identify the causes for losses in the warranty process by providing data visualizations that offer insights into business issues (dealer issues, supplier issues, no root cause, anomalies, etc.) It also enables the prioritization of actions to resolve the issues. Manufacturers, as a result, can detect emerging issues and make data-driven decisions that can lead to reducing warranty costs.

Key features

• Reduce warranty costs.
• Automatically detect emerging issues and reduces time to resolution.
• Reduce the size and cost of recalls.
• Increase the efficiency of problem-solving efforts for improved quality and customer satisfaction.

Segmented client service standards of care and adherence to increasingly restrictive compliance standards are key drivers of customer loyalty and assets under management (AUM) growth in the post-financial crisis wealth management industry. Financial advisors must rapidly identify clients who require immediate attention, prioritize client-specific actions among the different options available (e.g. compliance reminders, portfolio alerts, cross-sell opportunities, etc.) and engage clients accordingly.

Accenture Analytics' Wealth Advisory Toolkit application helps the home office generate actions and campaigns, link them to target clients and ensure that they drive desired behaviors and campaigns—all while enabling branch managers to monitor the financial advisors' ability to execute on the recommended actions. In turn, financial advisors will be able to identify the top priority actions to be taken on each client, and plan their activities accordingly.

Key features

• The Advisory Relationship Strength (ARS) score reveals the health status of the advisory relationship.
• Home office can prioritize high impact actions and promote desired behaviors.
• Financial advisor activities are standardized and structured through a prioritized list of client-specific actions.
• The ARS score reveals the status of the relationship with a customer, evaluates contact priorities and identifies urgent actions.
• Logging of ARS-driven actions and feedback is incentivized by the associated improvement in the client's ARS score.
• Helps financial advisors to plan new actions through simulations.

Utilities and companies handling widespread gas and oil pipelines face the need to maintain and optimize their assets while ensuring efficiency and productivity. Traffic and congestion, and weather conditions can have an impact on execution time, number of technicians needed in the field and the number of incoming calls to the back-office. Having reliable resource planning tools that account for external variables is crucial in avoiding operational bottlenecks. Analytics provide an opportunity to quantify, visualize, predict and confirm operational bottlenecks while translating the raw operational data into actionable insight.

The Accenture Analytics' Workforce Management application is an end-to-end solution that can cover the Resource Planning and Management process for every division. Field force productivity can be increased by better planning the technicians and the skills required and by forecasting the optimal number of resources needed daily. The application can also help improve back-office efficiency by reducing or eliminating tasks—generating consistent time savings—and by creating an industrialized real time plan of the crews on the field.

Key features

• Ability to plan, schedule, and dispatch work in real time.
• Better integration of asset and work planning.
• Monitoring of KPIs.
• Analytics capabilities: Root Cause Analytics, Forecasting, Capacity Planning, Predictive Device Maintenance, Network Incident Management.