Still trying to stop insurance fraud? With PNA's Data Analytics, you can find insurance fraud before it happens. With advanced pattern recognition, you can stay ahead of the fraudsters.
In the business of money, there can be no errors. That goes doubly so for keeping your customers. With PNA's finance data analytics, discover the hidden patterns that customers give you, and learn the language needed to retain them.
The banking industry is data-demanding with acknowledged ATM and credit processing data. As banks face increasing pressure to stay successful, understanding customer needs and preferences becomes a critical success factor. Along with Data mining and advanced analytics techniques, banks are furnished to manage market uncertainty, minimize fraud, and control exposure risk.
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
In the business of money, there can be no errors. That goes doubly so for keeping your customers. With PNA's finance data analytics, discover the hidden patterns that customers give you, and learn the language needed to retain them.
The banking industry is data-demanding with acknowledged ATM and credit processing data. As banks face increasing pressure to stay successful, understanding customer needs and preferences becomes a critical success factor. Along with Data mining and advanced analytics techniques, banks are furnished to manage market uncertainty, minimize fraud, and control exposure risk.
Acquire Grow & Retain customers - The business imperative for Big DataIBM Software India
The emergence of Big Data and Analytics has changed the way marketing decisions are made. Marketing has moved away from traditional ‘generalisation’ practices such as customer segmentation, geographical targeting etc. and is focussing more on the individual – the ‘Chief Executive Customer’.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Analytics is a two-sided coin. While on one side, it uses
descriptive and predictive models to gain valuable knowledge from data, i.e. data analysis, on the other side, it provides insight to recommend action or guide decision making, i.e. communication
How a centralized audit management system transformed our teamACL Services
Session from ACL Connections 2016
You understand the value that audit management technology can play in enabling success with your team, but are you overwhelmed
by the process of implementing software? In this tell-all hour, an ACL customer shares a window into their migration onto a
centralized system for managing projects, issues, and actions—including their thought process, approach, pitfalls and successes. She
will also share how ACL professional services helped her make critical change management decisions and mapped her processes to
ACL GRC functionalities. This session is intended for those who are interested in purchasing and implementing a new audit
management system as well as current ACL GRC users who want to learn how one of their peers is taking full advantage of the tool.
Key learning outcomes:
• Learn about the different factors that went into selecting a new tool
• Understand the challenges in the onboarding, migration and change management process of implementing a new audit
management system
• Learn how ACL professional services helped them transform their vision into reality, and made it easy for their team to
adopt
• See how their team is using project templates, and automating communication of issues and action plans
• Understand what the benefits have been so far and where the organization plans to go next
Are your service level reports all green, but your customer is still not happy? That's because traditional time-based IT support metrics suck. Discover a better way to measure IT service quality.
Recently, Oracle and Accenture polled some 200 CFOs and senior finance executives about
their strategies for improving the management reporting process. More than a third—41%— said selecting the right analytics tools and technologies was their top concern.
Unbundling the Insurance Value Chain - Disruption in the Insurance Sector - The 7th. International Istanbul Insurance Confrence - Prof. Dr. Selim YAZICI (2016)
Churn is a top revenue leakage problem for banks: is deep learning the answer-Sounds About Write
The impact of churn within the financial services industry is striking. BCG research found that attrition affects 30% to 50% of a corporate bank's client base and spans all products and segments.
Penser Consulting answers the key questions:
- What is big data, and why does it matter?
- How can big data drive business decisions?
- How can you build data analytics capabilities in your organisation?
Ten Commandments for Tackling Fraud: The Role of Big Data and Predictive Anal...CA Technologies
Accurate enterprise-wide data combined with data-driven fraud analytics can have a transformational effect on banking and related industries. This presentation provides tips and insights on using technologies like neural network predictive modeling, user behavior-based pattern recognition and statistical big data analytics to reduce the risk of fraudulent activities in the enterprise.
For more information on CA Security solutions, please visit: http://bit.ly/10WHYDm
The advent of ‘big data’ has completely changed the way businesses can harness the information about customers to make powerful business decisions. Data could be of any type – campaign information, customer demographics, individual transaction behavior, interactions on social networks, web usage, or satisfaction surveys etc. BRIDGEi2i has the ability and experience to mine this wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross sell and up-sell opportunities and thereby enhance the life time value of customer relationships. To know more visit: http://www.bridgei2i.com/customer-intelligence.html
Guide to Data Analytics: The Trend That's Reshaping the Insurance IndustryApplied Systems
Information you need is in your management system –- you just have to understand how to use it. Read this guide to learn what data analytics is, how it's impacting the insurance industry, why it's important for independent agencies and brokerages, and how to create your own data analytics strategy.
Insuring the insurance business with actionable analyticsWNS Global Services
The Insurance Industry is faced with a myriad of challenges such as a need to manage costs better, keep update with stringent regulations and the ever increasing demands from consumers. Analytics can play a vital role in assisting Insurance Executives navigate the technical and operational complexities to accelerate the growth of the industry.
Covering key aspects like Reporting, Descriptive or the advanced Predictive and Prescriptive analytics, this Whitepaper “Insuring the Insurance Business with Actionable Analytics” examines a complete view on how analytics can transform the insurance business to create value for all stakeholders.
GROW Your Life Insurance Agency Without Relying on InsurersJohn Lynch
With more online competition by insurers, a surplus of agents and a declining consumer market for quality insurance, life insurance agents and agencies need to find new ways to prospect and build their agencies with new revenue sources and a better foot-in-the-door with prospects that can afford quality insurance products.
The new ‘A and B’ of the Finance Function: Analytics and Big Data - -Evolutio...Balaji Venkat Chellam Iyer
Published in 2013, this White Paper discusses how the finance function would evolve with the combined forces of Big Data and Analytics and the levers that could help catalyze the change and has drawn upon the Global Trend Study conducted by Tata Consultancy Services (TCS) on how companies were investing in Big Data and deriving returns from it.
Analytics is a two-sided coin. While on one side, it uses
descriptive and predictive models to gain valuable knowledge from data, i.e. data analysis, on the other side, it provides insight to recommend action or guide decision making, i.e. communication
How a centralized audit management system transformed our teamACL Services
Session from ACL Connections 2016
You understand the value that audit management technology can play in enabling success with your team, but are you overwhelmed
by the process of implementing software? In this tell-all hour, an ACL customer shares a window into their migration onto a
centralized system for managing projects, issues, and actions—including their thought process, approach, pitfalls and successes. She
will also share how ACL professional services helped her make critical change management decisions and mapped her processes to
ACL GRC functionalities. This session is intended for those who are interested in purchasing and implementing a new audit
management system as well as current ACL GRC users who want to learn how one of their peers is taking full advantage of the tool.
Key learning outcomes:
• Learn about the different factors that went into selecting a new tool
• Understand the challenges in the onboarding, migration and change management process of implementing a new audit
management system
• Learn how ACL professional services helped them transform their vision into reality, and made it easy for their team to
adopt
• See how their team is using project templates, and automating communication of issues and action plans
• Understand what the benefits have been so far and where the organization plans to go next
Are your service level reports all green, but your customer is still not happy? That's because traditional time-based IT support metrics suck. Discover a better way to measure IT service quality.
Recently, Oracle and Accenture polled some 200 CFOs and senior finance executives about
their strategies for improving the management reporting process. More than a third—41%— said selecting the right analytics tools and technologies was their top concern.
Unbundling the Insurance Value Chain - Disruption in the Insurance Sector - The 7th. International Istanbul Insurance Confrence - Prof. Dr. Selim YAZICI (2016)
Churn is a top revenue leakage problem for banks: is deep learning the answer-Sounds About Write
The impact of churn within the financial services industry is striking. BCG research found that attrition affects 30% to 50% of a corporate bank's client base and spans all products and segments.
Penser Consulting answers the key questions:
- What is big data, and why does it matter?
- How can big data drive business decisions?
- How can you build data analytics capabilities in your organisation?
Ten Commandments for Tackling Fraud: The Role of Big Data and Predictive Anal...CA Technologies
Accurate enterprise-wide data combined with data-driven fraud analytics can have a transformational effect on banking and related industries. This presentation provides tips and insights on using technologies like neural network predictive modeling, user behavior-based pattern recognition and statistical big data analytics to reduce the risk of fraudulent activities in the enterprise.
For more information on CA Security solutions, please visit: http://bit.ly/10WHYDm
The advent of ‘big data’ has completely changed the way businesses can harness the information about customers to make powerful business decisions. Data could be of any type – campaign information, customer demographics, individual transaction behavior, interactions on social networks, web usage, or satisfaction surveys etc. BRIDGEi2i has the ability and experience to mine this wealth of unstructured and structured information to help businesses identify prospects, target them through the right channel, maximize cross sell and up-sell opportunities and thereby enhance the life time value of customer relationships. To know more visit: http://www.bridgei2i.com/customer-intelligence.html
Guide to Data Analytics: The Trend That's Reshaping the Insurance IndustryApplied Systems
Information you need is in your management system –- you just have to understand how to use it. Read this guide to learn what data analytics is, how it's impacting the insurance industry, why it's important for independent agencies and brokerages, and how to create your own data analytics strategy.
Insuring the insurance business with actionable analyticsWNS Global Services
The Insurance Industry is faced with a myriad of challenges such as a need to manage costs better, keep update with stringent regulations and the ever increasing demands from consumers. Analytics can play a vital role in assisting Insurance Executives navigate the technical and operational complexities to accelerate the growth of the industry.
Covering key aspects like Reporting, Descriptive or the advanced Predictive and Prescriptive analytics, this Whitepaper “Insuring the Insurance Business with Actionable Analytics” examines a complete view on how analytics can transform the insurance business to create value for all stakeholders.
GROW Your Life Insurance Agency Without Relying on InsurersJohn Lynch
With more online competition by insurers, a surplus of agents and a declining consumer market for quality insurance, life insurance agents and agencies need to find new ways to prospect and build their agencies with new revenue sources and a better foot-in-the-door with prospects that can afford quality insurance products.
The third edition of the BoardMatters Quarterly explores how big data and analytics emerge as game-changers for business. This edition also explores how we can tackle corruption, boosting internal control mechanisms.
Data Science for Small Business: Make Your Business SmarterKavika Roy
https://www.datatobiz.com/blog/data-science-for-small-business/
SMEs or small and micro enterprises form an integral part of a country’s economy. In India alone, the sector is said to have employed around 111.4 million people in the year 2014, and in 2012 it contributed 37.5% to the GDP. But, the irony is that even after being such an important part of the economy, SMEs are not able to flourish as they should have. There is a major lack of strategic business planning and innovation that hinders their growth.
In order for the SMEs to remain competitive both nationally and globally, it is imperative that every SME owner investigates the lacuna and starts working on it. Developing economies such as ours often find it difficult to foster innovation in the SME sector, because there are other factors that need the government’s attention.
The major problems faced by SMEs include unskilled staff, irregular finances, poor infrastructure, old marketing strategies and lack of information.
An SME owner tries to tackle all the issues but neglects an important one. This factor is “information”. Even after having skilled people, a good flow of money and good infrastructure the business may cease to flourish as expected by the owner.
Data Science Process: Resolve Business Problems SmartlyKavika Roy
https://www.datatobiz.com/blog/data-science-process-solve-business-problem/
Whether you run an empire or a small enterprise, every business faces certain common problems and hitches. The questions like, How do I improve my sales? What is my organization lacking? What to do when old customers are not purchasing my product? What ought to be done with a specific end goal to pull in more clients?
And much more such, often boggle a business owner’s mind. If this is the case with you as well, then there is definitely a path that can offer you a cutting edge over the others and it doesn’t take much effort in guessing what it is. Yes, I am talking about “data science” something that is taking over the corporate world with its capability to make complex things simple.
To understand the applications in a better way, you may look at the working model of big tycoons like Amazon, Uber, Netflix, Starbucks, etc. They all utilize Big data analytics to refine their marketing, manage their finances, predict frauds, evaluate the viewing habits of millions of clients, etc.
This is how Uber is able to provide the easy-to-book cab service and Starbucks does not suffer losses even after having three shops at the same location. Isn’t it mesmerizing as to what all data science can do?
The next question coming to your mind would be how to incorporate the data science process into your particular business module? Or how is this prediction even possible?
Do not worry, all your queries will be answered. But before moving ahead we must understand the basic concept of data science and the fields it merges together.
A data scientist combines concepts of, statistics, analytics, data processing, machine learning, predictive analysis, basic mathematics and computer science, to bring out the desired outcome that can benefit your business.
Do you run a business or work with the management closely? Have you ever thought about why sales numbers are going down? Is your operational cost going up? Why is it becoming harder day by day to retain clients? Why are customers flocking for competitors’ products? – In case you’ve ever been bothered with any of these types of questions, then you do understand the importance of data.
With the technology revolution, the operational aspect of businesses has changed drastically. Data is the new gold. He who knows how to churn out the insights and intel will beat all the competition. Data Science is the methodology for retrieving valuable information from the stockpile of data.
Nick krest - best strategies for business successNickkrest
The shorter term enables greater accuracy in completing the action steps to achieve the key initiatives, Wilson explains. The company’s co-principal Julie Stoney recommends the plan focus on only three to five key initiatives, as each initiative will require several steps. Among the steps for “growing the business,” for instance, may be acquiring a complementary business, developing new product lines and franchising.
Today there is a lot of buzz around customer experience. Many companies have realized that investments in customer experience improvement is important not just because it helps to boost the bottom lines of their businesses but because it takes at least 4 to 6 times more cost to acquire a new customer than to retain an existing customer.
7 Ways Insurance Brokers Should Approach InsurTechSiren Group
“InsurTech” is a term used quite often these days – a spin-off of the even more popular word “FinTech.” It refers to technologies and platforms. These platforms can help optimize any of the principles for success or requirements of insurance.
InsurTech encompasses companies that provide insurance, but engage technology in a user-centric way.
Here are 7 ways of making InsurTech the heart of your business:
Granting insurance cover is a complex process of assessing risks and evaluating claims. Insurers have to sort through large volumes of data to assess the risk involved in a single proposal for insurance cover. At the time of claim, the insurer must ensure that the claim is genuine and this again requires sorting through a sea of data. Experienced underwriters and claim investigators rely on their past experience to underwrite proposals or assess claims. New insurers, however, do not have this advantage. Big data can come to the aid of the insurance industry to help them sort through information and use it to their advantage. Let us find out how big data can help the insurance to tackle the everyday challenges that appear in the business.
Read the full blog here: http://suyati.com/the-role-of-big-data-in-the-insurance-industry/
To get in touch, write to us at: jghosh@suyati.com
Afinium.com Big Data Big Sales White Paper 2014 Afinium
Customer centricy drives sales, and real time data analytics allows creation of uniquely personalized buyer experiences to convert even casual browsers into loyal customers.
Behavioral-Based Safety – Predictive Analytics and a Safe Workplace McKenney's Inc
Companies large and small are using predictive analytics to decrease workplace incidents – by focusing on behavioral trends. Learn more at http://blog.mckenneys.com/2017/02/behavioral-based-safety-predictive-analytics-and-a-safe-workplace/
Artificial intelligence (AI) currently being used by insurance companies has failed to remove gender bias from the profession’s claims, underwriting and marketing processes.
A Chartered Insurance Institute (CII) report tells insurers they must tackle these gender biases. The report found that the datasets used to train the algorithms which support AI systems are rooted in outdated gender concepts. Algorithms learn by being trained on historic data but the report notes more and more of that data is now unstructured, coming from text, audio, video and sensors.
Yet the report warns embedded in that historic data are decisions based upon historic biases, particularly around gender. The report concluded insurance firms need to prepare a structured response to this issue, starting with visible leadership on tackling gender bias in AI.
5 Traits of Companies Successfully Preventing Fraud and How to Apply Them in ...IDology, Inc
With billions of dollars lost to fraud each year, it might seem daunting to protect your business from fraud. Yet many companies are successfully doing it and can be recognized by 5 key traits. Learn what these traits are and how to cultivate them in your business so you can successfully prevent fraud too.
Analysis of Sales and Distribution of an IT Industry Using Data Mining Techni...ijdmtaiir
The goal of this work is to allow a corporation to
improve its marketing, sales, and customer support operations
through a better understanding of its customers. Keep in mind,
however, that the data mining techniques and tools described
here are equally applicable in fields ranging from law
enforcement to radio astronomy, medicine, and industrial
process control. Businesses in today’s environment
increasingly focus on gaining competitive advantages.
Organizations have recognized that the effective use of data is
the key element in the next generation is to predict the sales
value and emerging trend of technology market. Data is
becoming an important resource for the companies to analyze
existing sales value with current technology trends and this
will be more useful for the companies to identify future sales
value. There a variety of data analysis and modeling techniques
to discover patterns and relationships in data that are used to
understand what your customers want and predict what they
will do. The main focus of this is to help companies to select
the right prospects on whom to focus, offer the right additional
products to company’s existing customers and identify good
customers who may be about to leave. This results in improved
revenue because of a greatly improved ability to respond to
each individual contact in the best way and reduced costs due
to properly allocated resources. Keywords: sales, customer,
technology, profit.
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
2. Overview of Analytics
The insurance industry is about helping people’s problems and getting them back on their feet.
But insurance companies need to keep their own internal issues in control to ensure all of their
customers stay with them, instead of taking their business to a competitor. Two of the biggest
issues for insurance providers lies with understanding and reducing customer churn and detecting
fraud before it happens. Both problems are vast and muddled by mountains of data that aren’t
easily deciphered.
Customer churn is notoriously tricky to nail down. With thousands of customers each having a
reason of their own to be dissatisfied, and not enough staff on hand to address each customer
individually, nailing down the actual reasons for churn in an insurance company can seem like an
insurmountable task.
And then there’s fraud. Insurance is a high-stakes game, and there are always going to be people
that try and get a claim done even when there’s no valid reason. But the problem that plagues
customer churn also plagues fraud. There’s simply way too many claims at any given time to sift
through to find which are real claims and which are frauds. So, most insurance providers rely on
human intuition and thorough investigations to uncover whether it’s an actual claim or attempted
fraud.
This is where data analytics can ease the burden. Insurance providers are never in deficit of useful
data to use for analysis. The only problem they face is figuring out how to use the data efficiently.
1
Marketing Analytics
Marketing
Claims
Legal
Provider
Mgmt
Finance
Investment
Sales
Customer
Service
UnderWriting
Actuarial
Sales AnalyticsInvetment Analysis
Customer Service
Analytics
Financial
Analytics
UW Analytics
Provider and
Supplier Analytics
Actuarial Analysis
Claims Analytics
Legal Analytics
• Lead Generation
• Market Research
• Business
Development
• Campaign mgmt
• Advertising and
promotions
• Channels
• Sales Mgmt
• Field Development
• Productivity
• Compensation
• Training
• New Business
Processing
• Renewals
• Payments
• Complaints
• Inquireies
• Assessment
• Classification
• Pricing
• Profitability
• Rate Dev, and Filings
• Prod, Development
• Reserving
• Reporting
• Registration
• Adjustment
• Fraud Mgmt
• Medical Mgmt
• Litigation Mgmt
• Compliance
• Ins.Dept
Complaint Mgmt
• Litigation Support
• Contracting
• Resource Mgmt
• Performance Mgmt
• Expense Mgmt
• Planning and
Budgeting
• Profitability Mgmt
• Performance Mgmt
• Financial Rpting
• Compliance
• Reinsurance
• Asset and
Capital Mgmt
Insurance analytics
3. 2
Churn Analytics
Customer churn is a major
performance indicator that
companies seek to reduce as
much as possible, since
customer retention is less
expensive than finding new
customers. Additionally,
reducing churn can directly
correlate to better customer
satisfaction, since the
customers are not looking for
better alternatives.
Business Need
Using this churn identification
and prediction, we can find
what is currently causing
churn, and what can be
expected to cause churn in the
future. By identifying and
rectifying these problems with
intelligent business decisions,
we can reduce customer churn
to a large extent.
OutcomeApproach
First, churn rate has to be
categorized and measured.
There are two types of churn,
customer churn and revenue
churn. Using logistical
regression and SVM machine
algorithms, we can identify
the various reasons causing
either customer or revenue
churn. This gives us a baseline
to predict future reasons.
Churn Analytics helps understand the individual issues customers face that’s making them turn
away from a company’s insurance policies, and provide direction to help mitigate the churn.
It’s much less expensive to retain existing customers than to acquire new customers. To acquire
new customers, insurance providers have to start from the very beginning of the marketing and
sales funnel to find and convince new customers to buy insurance policies.
4. 3
With these methods, we expect
to find a variety of types of
fraud, including identified fraud,
unidentified fraud, and predict
future instances of fraud.
Keeping track of current and
anticipating future methods of
fraud can help insurance
companies stay vigilant against
malicious parties.
Outcome
Fraud Detection
The need here is to identify
and flag fraudulent insurance
claims to human agents, who
can then follow up these
cases to deal with
appropriately. Additionally,
new and novel methods of
fraud need to be identified
before they cause the
business any losses.
Business Need
Insurance fraud is no small issue for insurance providers. But the issue with detecting and
preventing insurance fraud is no small problem. Insurance providers have hundreds of thousands
of customers. Insurance claims are also complicated and lengthy processes, which can hide fake
insurance claims amongst legitimate claims. Dealing with insurance fraud using only human agents
is time-consuming, laborious, inefficient, and often, inaccurate. But that’s where Data Analytics can
help.
Approach
We look at past and present
patterns of recording fraud
using algorithms like the
Naive Bayes Classifier to
classify and use data. Using
these methods, we can
prepare to deploy measures
to handle current incidents, as
well as stay alert for future
incidents where fraud may
happen.
5. 4
Smooth and Easy
Adoption of Analytics
When it comes to adopting analytics in the insurance sector, the technical requirements aren’t as
vast as some other industries. Data is already collected and stored. Adopting analytics is done
through the following steps.
• Identifying internal use cases (what are the goals for incorporating analytics into a firm?)
• Understanding the role and impact of analytics (Finding out what analytics can do for you and
your needs)
• Finding Required Talent (Third party consultant, or adding an in-house analytics wing?)
• Technical requirements (How are we collecting data? What new methods can be used?)
When it comes to data analytics, one size
does not fit all. It can be wise for some
companies to try and reach out to a dedicated
Data Analytics solution provider to avoid the hassle of
setting up an internal team. With thorough internal
deliberation, an outcome can be reached as to
whether the company should hire third party
consultants, or to begin assembling a team internally.
There is also an option of hiring a team occasionally to
check current performance and suggest changes in the
future.
Finding Required Talent
Once the format of the team is finalized,
the technical requirements are viewed. For
insurance, there is already a wealth of
customer data through insurance policies and their
background checks. Here, there should be a check to
see if the data collected is sufficient, or if there is more
data needed. If there is more data or resources
required, then appropriate methods to collect and
obtain those resources should be implemented.
Technical Requirements
Every department in a company has data waiting to be
mined and processed into actionable insights.
Although every department does have data useful for
data analytics, the problem is that not every company
has the time or resources necessary to make use of all
the generated data. By identifying these internal use
cases, we can create clear and actionable goals for
data analytics to work on. With this, we can create
metrics and milestones to measure the progress.
Identifying Internal Use Cases
Once the use cases have been identified, the next step
is to set up how future changes will be measured. This
means having a conversation before deployment and
asking a few key questions.
-What are the performance goals after deploying the
solution?
-How are these goals going to be measured?
-Does our organization have the tools necessary to
measure them?
Questions like these will provide valuable insight into
finding out whether or not the deployed
solution is actually performing as intended,
or if it has any unintended consequences.
measuring Analytics
6. We hope this gave you better insight into how Data Analytics can help your company reach new
business goals. If you have any questions, please contact us using the details below.
Thank You
PositiveNaick Analytics Ltd. No177,1st floor,
LM Tech Park, 1st Main Rd, Nehru Nagar, Kottivakkam,
Chennai, Tamil Nadu 600041.
Email: customercare@positivenaick.com
Website: www.positivenaick.com
Phone: +91-44 4857 6162