Frequently Asked Questions
Achieve Real Results With Your AI
What is the difference between structured and unstructured data?
Structured data is classified, categorized and sorted. Typical examples are enterprise data bases, online job application forms, spreadsheets, reports, financial data contained in an Enterprise Resource Planning (ERP) system, such as SAP, Oracle. Businesses make decisions based primarily on structured data.
Unstructured data is data that cannot be captured in a database. For example, historical customer information in an employee’s head, emails, apps, texts, web, clicks, social, behavioral, photos, video, voice recordings, voice-to-text conversion/transcripts, word documents, handwritten notes, music, geolocation, IoT, MNO, telematics or anything that has not been written down.
Recent research suggests that 90% of all data has been created in the last 24 months. 90% of that data is unstructured.
Therefore unstructured data makes up 80% of all currently available data.
Are You Moving Forward or Being Left Behind?
Ask yourself, what is the REAL COST of delaying a decision, or not making a decision at all?
Because of the wide spread inability to capture unstructured data, companies are making critical decisions from only 20% of the information available to them. (SEE ABOVE)
This often creates a silent, significant, and negative impact on business continuity and scalability because it greatly reduces the integrity of competent decision support.
Organizations want to glean insights from all their disparate systems (without replacing them), or they’re wishing they could make decisions closer to real-time instead of waiting each month for the information.
What is Artificial Intelligence (AI)?
AI (Artificial Intelligence) is the simulation of human intelligence processes by machines and computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.
Some of the activities computers with artificial intelligence are designed for include:
- Speech recognition
- Problem solving
Artificial general intelligence, is an AI system with generalized human cognitive abilities so that when presented with an unfamiliar task, it has enough intelligence to find a solution.
Machine learning (ML) is a subset of AI. Although AI and ML are closely entwined, they are not quite the same thing. ML gives computers the ability to learn without being explicitly programmed. It solves problems using the strategy of learning from the data.
Why Does it Matter?
When you unleash the full value of people, process, and technology, your organization can...
Leverage current investments in technology while preserving business initiatives, and enabling faster engagement of your workforce
Reduce or eliminate exposure, risk and liability threats to business continuity
Produce demonstrably faster results such as revenue generation, efficiency and effectiveness gains
Track progress of actual vs. targeted value-to-business outcomes in real-time
Ensure compliance with legislated and industry regulated requirements
Deliver repeatable, scalable results to consistently increase ROI and help make effective decisions
What does AI/ML mean for the future?
The “Value” of data is shifting from Structured to Unstructured Data.
Any/All highly regulated industries will be hit hard and fast (Structured Data).
Legislation and Policy are lagging, creating exposure, risk and liability
FOCUS to identify fast and clear differentiation required between background noise VS value-add technology and partnerships.
Early Risk Identification and Management… Exception Reporting.
Use of AI/ML used to accelerate move to Root Cause Analysis – FAST!
Canada/USA are behind in ADOPTION, therefore the rate of change will be faster.
What's In It For Me?
Powerful, Real-World Business Solutions:
- Change Management Component
- Human Resources Component
- Focus on Supporting Ethical Business Practices
- Project Management Component
Operations Perspective (Typical):
- Solution Implementation from Days to Weeks
- ROI Starts in Weeks
- 100% ROI in 4-12 Months
- Solution Becomes Self-Funding
- Solution is Fully Customizable
- Non-Disruptive Implementation
- Short Implementation Eliminates Project Fatigue
- 250 AI/ML Data Scientists
- 20 years Direct Experience in AI/ML; Cross-Industry
- 300 Person Years Invested in the Models Library
- Software that Adapts to Customer Behavior
How long will it take my Organization to see a Return on Investment?
Companies using our artificial intelligence solution typically begin to see a return on their investment in weeks not years!
Depending on the scope of the project, it may be possible to obtain a 100% ROI within 4-12 months, after which, because of the value and ROI we deliver, our projects can become self funding. We build multiple check points into our approach to enable the client to manage risks and costs.
Our Clarity™ solution is NOT invasive; it is a non-disruptive, disruptive solution. We conduct our implementation encouraging our clients employees to "conduct business as usual, using regular software, work flow, etc.
This enables our AI/ML to learn your business while also identifying opportunities for immediate, measureable and scalable improvement.
What is ?
A 360 Degree Transparent View of YOUR Business!
Businesses need to invest in Artificial Intelligence, Machine Learning and Deep Learning to remain relevant. In order to do that, automated platforms need to be robust and trustworthy, as they will be expected to manage high-value activities successfully. Existing systems are limited in scope and are not fine-tuned to process unstructured data from across the entire organization.
Clarity™ is Acquired Insights’ framework for consolidating advanced technologies.
The Clarity™ Advantage
We believe that companies should think for themselves, control their technology, and innovate at their own pace and in their own way.
Unlike other offerings in the marketplace, our Clarity™ solution is not limited to building out-of-the-box products and then selling them to companies. We've developed an adaptive framework that allows companies to gather and leverage any sort of data derived from behavioral, social, unstructured and structured means.
The only secure, closed-loop framework that exists in the market today, part of our Clarity™ solution spiders through new files, finds and open files, searches for content, identifies it, understands the context, compares its findings, creates relationships and gleans insights. Our Clarity™ framework is SMART software that adapts to customer behavior.
These insights are communicated both proactively and reactively. In other words, you can ask a question and get an answer based on all of the information available within its reach, or you can let the solution deliver notifications to you as needed.
Completely customizable to your specific organizational needs, our information capture methodology and analysis tools provide actionable, real-time insights to optimize the integration and productivity between business strategy, people, processes and technology.
Augment human work, decisions and interactions in your Organization.
What is the Behavioral Data Warehouse (BDW)?
Behavioral data generally refers to data derived from human, device or system behavior. Having good quality, predictive behavioral data allows better understanding and prediction of likely behavior. However, it can help beyond simply improving/boosting the performance of existing predictive models. It can also be used to identify previously hidden detail.
Although Behavioral Data can be highly predictive in a wide range of circumstances, it is hard to gather, store and control, is complex and often requires much trial and error. Answering such questions as:
- Which data items to collect?
- Which data are predictive and when?
To address these types of questions, the BDW is a fully featured, Behavioral Data Warehouse with a comprehensive toolset to automate the collection, storage and quality control of predictive behavioral data. The BDW allows enterprises to capture and intelligently react to highly predictive, real-time, behavior features across multiple devices, digital products and customer touchpoints.
The predictive behavior captured contains the synthesis of years of research and practical experience as to which data items are predictive. BDW captured data, just like credit bureau data, enhances predictive modelling, and improves business key performance indicators.
Even though the BDW, non-intrusively captures only predictive behavior data, BDW production deployments generate Big Data volumes. As part of BDW, this behavioral Big Data can be seamlessly integrated to a real-time Decision Engine (DE) and Standard Models Library to facilitate:
- integration of behavior data with other predictive data sources;
- real-time data enrichment;
- adaptive, intelligent, next-best-action decision-making.
By using the Behavioral Data Warehouse, organizations can rapidly implement and benefit from a fully functional, predictive BDW at a fraction of the cost it would take to build such a system in house. BDW allows organizations to focus on the key areas of gaining insight from predictive data rather than the time consuming task of acquiring, testing and managing it.
© Zoral Limited 2017 All rights reserved
What is the Decision Engine (DE)?
The Decision Engine is a SMART system. It captures and intelligently processes a huge range of data in real-time. This includes application, third party, behavioral, social, geolocation, financial, bureau, MNO digital fingerprint, imaging, digitized speech, IoT and many other types of data.
The DE both uses and enriches this data. It allows non-technical users to define complex workflows, rules logic and executes real-time decisions. These can be used to adapt in real time and progressively react as required. This highlights another, essential aspect of a SMART system. The DE has sophisticated, built in machine learning capabilities that help address these issues. It can react and adapt to changing business needs, priorities and requirements.
The Decision Engine allows you to set your target Key Performance Indicators (KPI’s). Then, it intelligently balances the necessary factors to optimize performance and profitability. This is another advantage you gain by using an artificially intelligent, SMART system.
© Zoral Limited 2017 All rights reserved
What is the Dynamic Customer Journey Framework (DCJ)?
The Dynamic Customer Journey(DCJ) Framework works in conjunction with the Decision Engine (DE) to facilitate mass digital product personalization based on customer-product behavioral dynamics and business objectives.
The platform is innovative, scalable and SMART. It has a component based approach and ability to capture up to 20,000 data points on the applicant/customer/end-user within the first 30 seconds, and utilize a wide range of predictive data sources that can be implemented and customized rapidly.
Driven by the Decision Engine (DE), the Dynamic Customer Journey Framework handles the UI, presentation logic, and customer journey across multiple digital channels and customer touch points. It manages the user interface, sequencing of screens, pages and fields, layout, look and feel, and customization.
The Dynamic Customer Journey Framework customization also handles pre-filling forms, enhanced data entry validation and verification (such as address lookup, ID verification etc.). It supports a range of customer-facing applications such as web, mobile, USSD, SMS or voice applications. Its business logic and processes are configurable via DE intelligent workflows to support business operations, customer support, front and back office, web and mobile applications.
© Zoral Limited 2017 All rights reserved
What is the Models Library?
The Models Library contains more than 300 man-years of data science and risk management expertise.
It is a state-of-the-art, robust, comprehensive suite of AI/ML models, methods, and tools with a wide range of model validation and calibration options. The Models Library contains extensive digital product transformation experience, and handles a wide range of predictive data sources.
The Models Library provides advanced predictive data strategy with proven methodologies, and supports regulatory compliance management.
It includes a suite of flexible APIs designed to work with a wide range of data sources, including bureau, behavioral, unstructured, MNO, social, financial, third-party, and many others. The Models Library is optimized for big data, speed, scalability, accuracy and profitability.
© Zoral Limited 2017 All rights reserved
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