Need help repairing your device? Create a Service Ticket with our Device Repair Form.

Drive Actionable Insights with Automated AI on IBM Power Systems

Innovation requires an artificial intelligence (AI) strategy, and H2O Driverless AI on IBM Power Systems™ is designed to accelerate your ability to create intelligent products and services that quickly deliver trusted results.

The benefits of H2O Driverless AI and Power Systems can include:

Automatic machine learning development

  • Use prepared exploratory data analysis to generate visualizations
  • Perform streamlined and customizable model documentation
  • Harness open and extensible automated machine learning (ML) optimization

Faster and more accurate results

  • Provide predictions designed to be easily explained
  • Acquire reason codes and model interpretability in plain English
  • Apply interpretability for debugging and regulation

Industry-leading interpretability

  • Increase accuracy with automatic feature engineering
  • Use GPU acceleration for 3.7x reduction in AI model training1
  • Build automatic reports including K-LIME, Shapley, Variable Importance, and more

Quick deployment into Power Systems

  • Launch Java and Python MOJOs2 more easily
  • Add H2O AI MOJOs runtime to customer applications
  • Works with existing customer applications in IBM AIX®, IBM i, and Linux® operating systems

How Driverless AI works

By employing AI tools across your IT infrastructure, you can gain insights faster:

  • Drag and drop data
  • Experience automatic visualization
  • Use your own algorithms or choose from the library (optional)
  • Optimize models automatically
  • Automatically generate scoring pipelines
  • Deploy MOJO scoring pipelines in AIX, IBM i, and Linux

The Value of Enterprise-Ready Power Systems

  • Move AI applications into production faster and offer new capabilities and insights
  • Help reduce AI model training time with highly parallelized CPUs and GPUs
  • Experience systems designed to ease deployment for low latency models in Python, Java, and R

Putting Artificial Intelligence to Work: The role of AI in GRC

What is GRC?

With many financial institutions ending up paying massive fines for non-compliance, most businesses are actively seeking to redefine their Governance, Risk, and Compliance (GRC) strategy.

Traditionally, GRC initiatives have been solely about protecting businesses from liability. The importance of GRC, however, has gradually increased.  Today, the impact of noncompliance isn’t limited to just hefty fines but also lesser market credibility and shaken customers and stakeholders’ trust.

The need of the hour is to build an intelligent GRC model through an AI-based tool that can identify potential new patterns of risk and help mitigate them. A business that has a robust AI-infused GRC solution can improve agility, transparency, and the overall performance of the risk and compliance team. The tool can use machine learning and cognitive processing to generate actionable insights, which can be leveraged for managing the key aspects of GRC activities.

The Role of AI in GRC

The infusion of AI capabilities into the GRC framework makes it undeniably smarter. AI-based tools eliminate the manual process of reviewing organizational charts and spreadsheets. Instead, they use language-based or rule-based software to automatically understand texts and provide timely insights to risk and compliance professionals.

Financial firms that embrace the growing trend of AI-based risk and compliance tools are at a greater advantage of preventing major incidents and face minimal danger of falling behind the competition.

Benefits of an AI-driven GRC Framework

Data classification: Precise classification of data enables its efficient usage across the organization and simplifies risk management and compliance processes. Manual data classification, however, is not only prone to errors but training employees to do so can be extremely time consuming.

AI eliminates this hassle by improving the speed and accuracy of data classification. Natural Language Processing (NLP) understands and categorizes data automatically which helps organizations save time.

Real-time smart alerts: Financial institutions get inundated with thousands of alerts daily, out of which some or all may not actually apply to them. NLP helps filter these alerts and ensures that compliance teams only receive the most relevant ones. This fosters better understanding and management of regulatory change.

Control mapping: NLP reduces the chances of duplicate controls in relation to specific obligations within a regulation. It helps compliance teams detect whether an existing control can be mapped to record the organization’s compliance with the rule. This reduces the time spent on understanding the applicability of new rules or regulatory changes.

Challenges of an AI-Driven GRC Framework

Lack of user skills: The success of an AI-infused GRC application depends on how dedicatedly the risk and compliance teams use, understand, and interact with it. Irrespective of how advanced the tool is, it needs to have an enhanced user-experience design to appeal across all lines of defense. A user-focused GRC application doesn’t have the issue of a steep learning curve. This automatically reduces the need of extensive training and fosters complete user adoption.

Data availability and quality: Data is at the heart of AI. The two most prevalent AI techniques (Machine Learning and Natural Language Processing) require a large amount of historical data that can be analyzed to generate accurate insights. Therefore, to successfully implement an AI-infused GRC application, it’s imperative that the tool is supported by a robust data infrastructure that feeds it with high-quality data in the right format and scale.

Providing a Unified Vision – IBM OpenPages with Watson

IBM OpenPages with Watson stands tall as the only cognitive-driven, integrated GRC portfolio in the market that breaks all silos and ensures that no risk and compliance professionals work in watertight compartments. Unlike a rigid, legacy GRC system, it provides an enterprise-wide view of risk, including all business units, business partners, and suppliers. It fosters a collaborative approach where compliance becomes an organization-wide responsibility and no department fails to adhere with requisite standards.

Main Differentiators:

  • Task-focused user interface designed for ease of use
  • NLP and ML capabilities within a UI developed with IBM Enterprise Design Thinking
  • Dynamic dashboards, charts, and dimensional reporting for root cause risk analysis
  • Regulatory expertise from Promontory Financial Group’s 700+ team of experts
  • Extensible to different business processes across risk and compliance domains
  • Smooth data integration and aggregation with IBM’s comprehensive REST APIs
  • Integration with key technologies, such as IBM Cloud for faster data accessibility and IBM Cognos Analytics for crucial data insights
  • Strategic partnerships with Promontory Financial Group, Thomson Reuters, and Wolters Kluwer
  • Scalable, flexible, single model architecture supporting more than 20 thousand users

Key GRC Complexities:

IBM OpenPages with Watson addresses three key problems of the global regulatory environment (low visibility, disparate GRC systems, and limited reach) through the following ways:

  • Provides an accurate, timely view of all obligations and the associated end-to-end responsibilities
  • Breaks down silos and complex systems; provides a holistic view of risk and compliance across all units and risk types
  • Uses the business intelligence capabilities of Cognos Analytics to uncover hidden insights
  • Highlights obligations relevant to business units and maps them to internal controls
  • Provides automated regulatory alerts through partnerships with leading third-party regulatory data sources

Risk-Aware Culture

IBM OpenPages with Watson ensures active engagement from all levels in the business (especially the first line of defense) through a user-focused interface integrated with compelling features:

  • Workspace that can be easily customized through adding, removing, or hiding panels
  • Visual cues, validation messages, and classification recommendations for easy and accurate information captured by the first line of defense
  • Quick view of individual and team tasks to ensure proper monitoring of risk activities
  • Interactive tree maps to depict how assessments, business entities, processes, resources, products, and controls are connected in the organization
  • Zone or count-based embedded heat maps and charts to determine areas of focus and impact

A Combination of Eight GRC Solutions

IBM OpenPages with Watson provides businesses with the advantage of deploying GRC modules as needed with a scalable, forward-looking architecture that can grow with their evolving needs.

  • IBM OpenPages Operational Risk Management

IBM OpenPages Operational Risk Management is an automated tool that helps to identify, evaluate, and manage operational risks. It provides a single repository to store all risk data, such as risk and control assessments, internal and external loss events, and key risk indicators. Consolidated risk documentation enables risk managers to track loss incidents and determine root causes. Also, its advanced reporting feature provides an accurate insight into the state of risk across the organization.

  • IBM OpenPages with Watson Regulatory Compliance Management

IBM OpenPages with Watson Regulatory Compliance Management is both a SaaS and on-premises solution that leverages the AI capabilities of Watson and financial expertise of Promontory Financial Group to streamline regulatory compliance management functions. It enables financial institutions to process large volumes of regulatory updates, highlight the ones relevant to their business units, and map them to internal controls. Dedicated use of this platform helps reduce time and cost in comprehending and triaging regulatory alerts.

  • IBM OpenPages Policy Management

IBM OpenPages Policy Management simplifies the entire process of complying with industry, privacy, and government regulatory mandates. It uses Watson cognitive suggestions to map policies to regulatory obligations and highlights the new updates as regulations and obligations change. On-demand, actionable reporting helps financial institutions gain a holistic understanding of all compliance risks to mitigate them and ensure full adherence to necessary policies and procedures.

  • IBM OpenPages IT Governance

IBM OpenPages IT Governance aligns IT operations management with corporate business initiatives, strategy, and regulatory requirements. It automatically notifies and routs IT related activities, tracks all relevant IT incidents and facilitates root cause analysis. Financial firms can identify IT risks, remediate issues, enforce corporate IT governance policies, and sustain compliance across several best practice frameworks, such as COSO, COBIT, ITIL, and ISO.

  • IBM OpenPages Internal Audit Management

IBM OpenPages Internal Audit Management uses core shared services and open architecture to automate internal auditing procedures. It offers a centralized library of electronic workpapers and can automate workpaper review and approval process. The tool is smoothly integrated with all other risk domains and gives auditors a holistic view of enterprise-wide compliance status across disparate policies and procedures.

  • IBM OpenPages Model Risk Governance

IBM OpenPages Model Risk Governance helps address the challenges of model risk management. It creates and maintains a comprehensive model inventory to remove siloed data, bring transparency and foster collaboration among key stakeholders, such as model developer, owner, validator, and business unit executive. The tool also offers interactive dashboards and dynamic reports for greater visibility into model performance metrics.

  • IBM OpenPages Vendor Risk Management

IBM OpenPages Vendor Risk Management assists in identifying, evaluating, and managing third-party compliance and risk issues. It brings greater transparency and visibility into vendor-related operational and security activities. Financial institutions can streamline the vendor management process by classifying the criticality of vendors as low, medium, or high and managing their contracts in an organized way. The tool uses standard risk assessments to help monitor and mitigate any risk exposure resulting from third-party suppliers.

  • IBM OpenPages Financial Controls Management

IBM OpenPages Financial Controls Management supports financial institutions in complying with Sarbanes-Oxley and other key financial reporting regulations. Firms can refer to a single repository for all financial controls and compliance documentation. They can automate the ongoing control testing, risk assessment, and issue remediation process for better financial controls management. The tool also offers interactive dashboards and dynamic reports for complete visibility into the state of financial reporting and compliance across the organization.

The IBM Difference

IBM empowers financial institutions to confidently address their key challenges with the use of Cloud, Cognitive, Big Data, RegTech, and Blockchain technology. The objective is to provide a unique combination of technology, regulatory, and domain knowledge that helps firms manage the ever-changing risk environment.

IBM OpenPages with Watson is a leading RegTech solution that offers innovative capabilities and techniques to help financial institutions better meet their regulatory monitoring, reporting, compliance, and risk management needs. It replaces manual, labor-intensive approaches with a cognitive solution that facilitates effective decision-making and better risk management.

To learn more about IBM solutions, contact Data Integrity, your IBM Gold Business Partner.

1 Results are based IBM Internal Measurements using Power AC922; 40 cores with NVLink 2.0 vs. 2-Xeon E5-2640 v4 with 20 cores 4xTesla V100 GPU. Using Chainer v3 with Large Model Support running on POWER9 shows the value of NVLink 2.0 and the performance capability that it can deliver when the problem set becomes larger than the memory supported on the GPU cards. These tests move large amounts of data between the CPU and the GPU and can reduce model training times by 3.7X .

2 H2O can allow you to convert the models you have built to either a Plain Old Java Object (POJO) or a Model ObJect, Optimized (MOJO). A MOJO (Model Object, Optimized) is an alternative to H2O’s POJO. As with POJOs, H2O can allow you to convert models that you build to MOJOs, which can then be deployed for predictive scoring in real time. H2O generated MOJO and POJO models are intended to be easily embeddable in any Java environment.