Cognitive Automation and Its Importance for Enterprises

Published on Sep 27, 2018

Updated on Jan 3, 2020

One of Japan’s leading insurance firms — Fukoku Mutual Life Insurance claims to have replaced 34 human tasks with IBM Watson (AI technology).

Cognitive automation is a subset of artificial intelligence that uses advanced technologies like natural language processing, emotion recognition, data mining, and cognitive reasoning to emulate human intelligence. In simple words, cognitive automation uses technology to solve problems with human intelligence.

Cognitive automation vs Robotic Process Automation

The main pillars of cognitive automation

Consider an automated home security system programmed to function based on millions of decisions. It may still encounter situations when it does not know what to do. Machines can make logical decisions in many unforeseen situations using cognitive neuroscience.

The technologies to make cognition-based decisions possible include natural language processing, text analytics, data mining, machine learning, semantic analytics, and more. The following table gives an overview of the technologies used in cognitive automation.

TECHNOLOGY	DESCRIPTION
Machine Learning	It involves improving a system’s performance by learning through real-time interactions and without the need for explicitly programmed instructions.
Data Mining	It is the process of finding meaningful correlations, patterns, and trends from data warehouses/repositories using statistical and mathematical techniques.
Natural Language Processing	NLP is a computer’s ability to communicate with humans in native languages.
Cognitive Reasoning	It is the process of imitating human reasoning by engaging in complex content and natural dialogues with people.
Voice Recognition	It is transcribing human voice and speech and translating it into text or commands.
Optical Character Recognition	It uses pattern matching to convert scanned documents into corresponding computer text in real-time.
Emotion Recognition	It is the understanding of a person’s emotional state during voice and text-based interactions.
Recommendation Engine	It is a framework for providing insights/recommendations based on different data components and analytics. For instance, Amazon was one of the first sites to use recommendation engines to make suggestions based on past browsing history and purchases.

Why is cognitive process automation important for enterprises?

Cognitive automation improves the efficiency and quality of computer-generated responses. In fact, cognitive processes are overtaking nearly 20% of service desk interactions. The following factors make cognitive automation next big enhancement for enterprise-level operations –

Cost-effective: Cognitive automation can help companies to save up to 50% of their total spending for FTE, and other related costs.
Operational Efficiency: Automation can enhance employee productivity, leading to better operational efficiency.
Increased accuracy: Such systems are able to derive meaningful predictions from a vast repository of structured and unstructured data with impeccable accuracy.
Facts-based decision making: Strategic business decisions drill down to facts and experiences. Combining both, cognitive systems offer next level competencies for strategic decision making.

4 benefits of cognitive automation for enterprises

Also read – Cognitive approach vs digital approach in Insurance

Applications of cognitive automation

End-to-end customer service

Enterprises can understand their customer journey and identify the interactions where automation can help. For example, Religare — a leading health insurance company incorporated NLP-powered chatbot into their operations and automated their customer-support and achieved almost 80% FTE savings. Processes like policy renewal, customer query ticket management, handling general customer queries at scale, etc. are possible for the company through chatbots.

Processing transactions

Reconciliation is a tedious yet crucial transaction process. Banking and financial institutions spend enormous time and resources on the process. Paper-based transactions, different time zones, etc. add to the complicacy of settling transactions. With human-like decision-making capabilities, cognitive automation holds a huge prospect of simplifying the transaction-related processes.

Claims processing

In insurance, claims settlement is a huge challenge as it involves reviewing policy documents, coverage, the validity of insured components, fraud analytics, and more. Cognitive systems allow making automated decisions in seconds by analyzing all the claims parameters in real-time.

Also read – How intelligent systems can settle claims in less than 5 minutes

Requirements

Deloitte’s report on how robotics and cognitive automation will transform the insurance industry states that soon, automation will replace 22.7 million jobs and create 13.6 million new jobs. However, not all operations can be automated. The following are the requirements for successfully automating processes.

Input sources: The input sources should be machine-readable, or needs to be converted into one. Also, there’s a limitation to the number of sources that the system can process for decision making. For instance, in an email management process, you cannot automate the resolution of every individual email.
Availability of the technology: Cognitive automation combines several technologies like machine learning, natural language processing, analytics, etc. Thus, all the technologies should be available to make automated processes functional.
Data availability: For the cognitive system to make accurate decisions, there should be sufficient data for modeling purposes.
Risk factor: Processes like underwriting and data reconciliation are good prospects of cognitive automation. However, based on the risk value and practical aspects, human intervention may be required to make the final decision.
Transparency & control: Cognitive automation is still in a nascent stage and humans may overturn machine-made decisions. Therefore, the system design needs to adhere to transparency and control guidelines.

Wrapping up

Cognitive systems are great for deriving meaningful conclusions from unstructured data. Many back and front office operations can be automated for improving efficiency, especially in consumer-facing functions to understand requirements and feedback. For instance, cognitive automation comes with powerful emotion recognition capabilities. It can help with making sense of customer tweets, social updates, through face recognition and analyzing texts.

Since cognitive automation solutions help enterprises to adapt quickly and respond to new information and insights, it is becoming crucial for customer-centric businesses. The following graph shows how important cognitive technology adoption is for businesses that focus on consumer centricity.

Customer centricity and cognitive technology adoption — *Source: Deloitte*

Also read – 5 Front office operations you can improve with AI

Claims are the moment of truth. Are you turning them into moments of loyalty?

In insurance, your app interface might win you downloads. Your pricing might drive conversions.
But it’s the claims experience that decides whether a customer stays—or leaves for good.

According to a survey by NPS Prism, promoters are 2.3 times more likely to renew their insurance policies than passives or detractors—highlighting the strong link between customer advocacy and retention.

NPS in insurance industry is a strong predictor of customer retention. Many insurers are now prioritizing NPS to improve their claims experience.

So, what are today’s high-NPS insurers doing differently? Spoiler: it’s not just about faster payouts.

We’ve worked with claims teams that had best-in-class automation—but still had low NPS. Why? Because the process felt like a black box.
Customers didn’t know where their claim stood. They weren’t sure what to do next. And when money was at stake, silence created anxiety and dissatisfaction.

Great customer experience (CX) in claims isn’t just about speed—it’s about giving customers a sense of control through clear communication and clarity.

The Traditional Claims Journey

Forms → Uploads → Phone calls → Waiting
No real-time updates
No guidance after claim initiation
Paper documents and email ping-pong

The result? Frustrated customers and overwhelmed call centers.

The CX Gap: It’s Not Just Speed—It’s Transparency

Customers don’t always expect instant decisions. What they want:

To know what’s happening with their claim
To understand what’s expected of them
To feel heard and supported during the process

How NPS Leaders Are Winning Loyalty with CX-Driven Claims and High NPS

1. Real-Time Status Updates

Transparency to the customer via mobile app, email, or WhatsApp—keeping them in the loop with clear milestones.

2. Proactive Nudges

Auto-reminders, such as “upload your medical bill” or “submit police report,” help close matters much faster and avoid back-and-forth.

3. AI-Powered Document Uploads

Single-click scans with OCR + AI pull data instantly—no typing, no errors.

4. In-the-Moment Feedback Loops

Simple post-resolution surveys collect sentiment and alert on issues in real time.

For e.g., Lemonade uses emotional AI to detect customer sentiment during the claims process, enabling empathetic responses that boost satisfaction and trust.

Smart Nudges from Real-Time Journey Tracking

For a leading insurance firm, we mapped the entire in-app user journey—from buying or renewing a policy to initiating a claim or checking discounts. This helped identify exactly where users dropped off. Based on real-time activity, we triggered personalized notifications and offers—driving better engagement and claim completion rates.

Tech Enablement

Claims Orchestration Layer: Incorporates legacy systems, third-party tools, and front-end apps for a unified experience.

AI & ML Models: For document validation, fraud detection, and claim routing, sentiment analysis is used. Businesses utilizing emotional AI report a 25% increase in customer satisfaction and a 30% decrease in complaints, resulting in more personalized and empathetic interactions.

Self-Service Portals: Customers can check their status, update documents, and track payouts—all without making a phone call.

Business Impact

What do insurers gain from investing in CX?

A faster claim is good. But a fair, clear, and human one wins loyalty.

And companies that consistently track and act on CX metrics are better positioned to retain customers and build long-term loyalty.

At Mantra Labs, we help insurers build end-to-end, tech-enabled claims journeys that delight customers and drive operational efficiency.
From intelligent document processing to AI-led nudges, we design for empathy at scale.

Want a faster and more transparent claims experience?

Let’s design it together.
Talk to our insurance transformation team today.

Cognitive Automation and Its Importance for Enterprises

The main pillars of cognitive automation

Why is cognitive process automation important for enterprises?