Mphasis DeepInsights™ is a patent pending Cognitive Intelligence platform, which enables enterprises to have faster and more effective access to insights from data. Cognitive intelligence is one of the major pillars on which tomorrow's enterprises are being built. By turning nearly every aspect of inferencing and decision making, it is revolutionizing the competitive differentiation of enterprises. DeepInsights™ is powered by state-of-the-art algorithms in machine learning, neural network, deep learning, semantics, image analytics, graph theory, predictive analysis and natural language processing. This further enables enterprises to engage with their customers through personalized experiences and explore newer business models that leverage the potential of anywhere any time on any device computing capabilities.  

COGNITIVE COMPUTING PLATFORM

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    Smart Data Ingestion

    Machine Learning based intelligent extraction of data from thousands of file types including images, documents, PDF, emails and HTML
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    Cognitive Analytics

    Deep analysis of structured and unstructured data using Deep Learning, Neural Networks, Graph Theory, Image analytics, Machine Learning and Natural Language Processing
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    Automated Decision-Making

    Contextual and temporal decisioning to generate the right insights from documents and trigger downstream workflows for manual actions or Robotic Process Automation
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    Versatile Interaction

    Interact with enterprise systems and channels such as virtual and human agents, databases as well as APIs across industries such as Wealth Advisory, Trade Finance, Insurance and Banking

Deep Insights

BENEFITS

 

  • Powerful cognitive engine automatically leverages the best of machine learning and deep learning algorithms to analyze data
  • Cloud based and provides the most contextual and accurate decision metrics from structured & unstructured data
  • DeepInsights™ enables timely decision making by exponentially reducing the turn-around time of business processes
  • DeepInsights™ work with multiple file formats and types and presents information in a structured format for downstream consumption
  • Image processing capabilities along with cognitive OCR enables it to faster process unstructured scanned documents
  • Cognitive analytics driven straight-through processing
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Automated Intelligent Ticket Routing

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Automated Intelligent Ticket Routing

Business Challenge:

  • Manual assignment of tickets based on human intuition and knowledge
  • Large human effort across projects devoted to only assigning tickets to appropriate resources.
  • Simple Yes-No judgements with rigid guided diagnostics
  • Machine learning techniques employed for ticket assignment (if available) do not take domain knowledge into consideration
 
DeepInsights™ Solution:
 
  • Guide diagnostics on a probabilistic basis embedding expert knowledge while considering utility, satisfaction, cost, and time of repair in a multi-criterion decision making framework
  • Extract Key Features from past ticket resolution data and use past data to predict probabilities of closing tickets by different users using Bayesian networks
  • Assign tickets to resources who are most likely to resolve them based on this calculated probability
  • For new tickets, use online learning algorithms to assign and learn simultaneously\
 
Benefits:
 
  • Optimize allocation of tickets by assigning more tickets to better resources
  • Natural, data-driven selection and matching of supply and demand
  • Reduced time for closure of tickets and increase in user satisfaction
  • Automate the diagnostic and repair process by linking with Robotic Process Automation
  • Reduce effort involved in allocation of tickets and free up resources for more productive work.


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Cognitive Next Best Action prediction

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Cognitive Next Best Action prediction

Business Challenge

  • Large number of application support tickets raised
  • Many of the support tickets can be solved with minimal guidance
  • Current guidance systems are rule based and not intelligent enough to provide contextual help to the users
  • The current self-help systems or chat bots, do not learn from past data or patterns
 
DeepInsights™ Solution
 
  • Utilize historical trend, pattern identification for ticket resolutions - Extract Key Features from Ticket Resolution Data on actions taken in each step
  • Graphical models of probabilistic next resolution steps - Use past data to predict possible causes and next best action for support technician
  • Aggregation of support data from relevant sources
  • Recommendation of ‘Next Best Action’ to support staff and users for self-service
 
Benefits
 
  • Reduced time for closure of tickets
  • Assistance on ‘Next Best Action’
  • Can enable the creation of ‘Self-help’ platforms for end-users
  • Natural, data-driven selection of better ticket resolution
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Cognitive Data Extraction & Analytics

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Cognitive Data Extraction & Analytics

Business Challenge

  • Generate actionable insights from physical and digital data sources such as annual reports, bank statements, emails, customer complaints etc.
  • Complexity of the problem makes manual analysis non-real time, challenging, costly and low on accuracy
  • Information is residing in varied data and document types such as databases, PDFs, HTML, JPEG etc.
  • Lack of standardization of information as well as fields needed for decision making

DeepInsights™ Solution
 
  • Machine Learning for intelligent extraction and analysis of data from digital as well as paper documents and images
  • Cognitive data extraction techniques for conversion of documents to machine readable format
  • Built in Big Data analytics module to analyze structured and unstructured data
  • Key metrics trigger next steps in the automation workflow
 
Benefits
 
  • Over 95% accuracy in detection and extraction of key fields
  • Reduced time taken for data extraction by over 70%
  • Reduced operating costs by over 50%
  • Improved client satisfaction through near real-time analysis of data
  • Exponential reduction in turn-around time from data to insights
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Policy Document Analysis & Chatbot based interaction

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Policy Document Analysis & Chatbot based interaction

Business Challenge

  • Large proportion of in-bound queries from brokers and customers regarding policy wordings, policy schedules or similar FAQs.
  • Complexity of the problem makes manual data extraction and analysis non-real time, challenging, costly and low on accuracy
  • Customer queries are coming in 24*7, resulting in the need to respond at near real time
  • Need to reduce demands on key insurance personnel and prevent inconsistent responses to customer queries
 
DeepInsights™ Solution
 
  • Natural Language Processing to understand the "intent" of query and identifies those that don’t need manual intervention (e.g. negotiation).
  • Cognitive data extraction techniques for conversion of documents to machine readable format
  • Built in Big Data analytics module to analyse structured and unstructured data
  • Analysed data is leveraged by the DeepInsights™ chatbot for 24*7 versatile customer interactions
 
Benefits
 
  • Achieved over 97 % accuracy in the data extracted from policy documents
  • Time taken to find relevant information from documents reduced from 60 seconds/field to 5 seconds/field
  • Reduced operating costs by over 60%
  • Improved customer satisfaction through 24*7  query support
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Broker Claim Submission Analysis

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Broker Claim Submission Analysis

Business Challenge

  • Large volume of in-bound documents from brokers with the information spread across the body of the email or in  email attachments. Attachments are in word format, or digital or scanned PDFs
  • There is no consistency of document structure either between brokers or within the same brokerage company
  • It’s a time consuming and tedious process. An operator typically clears 8-10 quotes from his queue per day
  • Complexity of the problem makes manual data extraction and analysis non-real time, challenging, costly and low on accuracy
 
DeepInsights™ Solution
 
  • The DeepInsights™ AI engine iterates through various techniques and deploys the predictive  technique most suitable for the data at hand
  • The engine checks for inter-field validity and  flags values that occur with low confidence to call for manual intervention
  • RPA systems then access the key fields and update multiple legacy databases
  • DeepInsights predictive analytics engine predicts quote conversion probability and highlights high/low performing brokers who consistently accept/reject quotes
 
Benefits
 
  • Achieved over 90 % reduction in processing time per case document
  • Predictive analytics prioritized underwriting queue with respect to quote conversion probability
  • 90% accuracy in predicting deal conversion
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Self-healing of IT Operations

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Self-healing of IT Operations

Business Challenge

  • Large number of application support tickets raised
  • Difficulty in identifying and prioritizing high risk and impactful alerts among Terabytes of event logs that can lead to subsequent failure
  • Longer cycle times to arrive at incidence resolution due to difficulties in RCA (Root-cause analysis) on event log.
  • Less efforts on proactive fixation of possible incidences due to high manual intervention. This leads to more infrastructural cost and high risk of interruptions.
  • More effort in resolution of L2 and L3 incidences
 
DeepInsights™ Solution
 
  • DeepInsights™ Cognitive Data Extraction engine ingests data from event logs and mines to identify events
  • Predictive Analytics Engine predicts incidences that leads to failure in IT infrastructures
  • The engine reasons root cause of the incidence based on historical knowledge Repositories using Self-learning
  • The system works with RPA to automate resolutions
  • Resolution implemented by AI bots which plugs in to resolve the issue by learning from past resolutions
 
Benefits
 
  • Achieved over 95 % accuracy in predicting events
  • Reduced resolution times due to speedy and accurate RCA
  • Expedite Resolution management with minimal or no manual intervention
  • Increases infrastructure reliability due to automated preventive maintenance schedules
  • Increased Business Continuity without disruptions
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Incident Management in IT Operations

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Incident Management in IT Operations

Business Challenge

  • Incident information can be logged either by user or by set of automated business rules.
  • Information fields can be inconsistent and diverse based on device type, monitoring agent, and type of incidence.
  • Accurate categorization of incidences is manual intensive and subjective.
  • Incidence routing to the right expert among resources of varied skill set is complex.
  • Identification of resolution for an incidence from existing massive knowledge repositories is tedious and time consuming.
 
DeepInsights™ Solution
 
  • DeepInsights™ Cognitive Data Extraction engine extracts Key Features from Ticket Resolution Data and Incidence Type and Description Data
  • The AI engine would intelligently categorize incidences based on past data.
  • The Predictive Engine based on past data predicts probabilities of closing tickets by experts and ranks based on Deep Learning and Bayesian Models.
  • RPA systems then route the incidences to respective experts and initiates business processes.
  • Recommendation engine to shortlist and order knowledge documents that are relevant for resolution.
 
Benefits
 
  • Faster, accurate and automated incidence categorization and routing.
  • Reduced time for incidence resolutions by identifying right expert at right time.
  • Optimize incidence allocation by assigning to better resources
  • Use learning algorithms to optimally assign incidences in a dynamic context
  • Real-time Knowledge Management System to arrive at quicker resolution.

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Email analytics, segregation and routing

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Email analytics, segregation and routing

Business Challenge

  • Enterprises are faced with a problem of having to process and respond to a large volume of inbound mails with a variety of content
  • Assessing and classifying these emails requires effort of experts with vast variety of domain knowledge
  • The routing of emails to the right recipient is time consuming and prone for errors and are dependent on the tacit domain knowledge of assessing experts.
  • Manual segregation by domain experts involve time for action caused by email content length, variety of topics and overall volume in queue for action

 

DeepInsights Solution

  • Email data provisioning system for intelligent ingestion that scale to volume and variety of inbound email
  • Cognitive engine that reads the email content and identify the topic(s) discussed using Deep Learning, Machine Learning and Text analytics
  • The Classification and Prediction engine segregates them and assigns them to various classes, prioritises and routes the email to the right workflow

 

Benefits

  • Rapid email data ingestion and intelligent provisioning for analysis
  • Reduced requirement of domain experts for email assessment and content summarization
  • Reduced time for processing emails and segregating them based on content
  • Real time routing of emails to right recipient
  • Intelligent end to end workflow platform for email processing, routing and knowledge management

For a Consulting Engagement, please contact us at nextlabs@mphasis.com