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A Comprehensive Article on the Trends, Dynamics and Developments of Risk Analytics Market

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Risk analytics makes organizations aware of the potential risks in their businesses. It helps companies make risk-aware decisions and improves their overall business performance. Risk analytics tools help investors get a better return on their capital and minimize the money required to be spent on regulatory compliances. Risk analytics tools aid in the central clearing of over-the-counter (OTC) derivatives.

Classification of Risk Analytics Market

Risk analytics market is divided based on:

  • Component type: Component segment of risk analytics market is further classified based on:
    • Type of solution: Risk analytics software group for regulatory compliance, market risk management, credit risk management, etc. are included in this group.
    • Services: Software services associated with risk analytics software like systems integration and risk evaluation are included in this group.
  • Size of enterprise: Risk analytics market based on size of enterprise is further categorized as:
    • Large organizations
    • Small and medium organizations
  • End-use verticals: Risk analytics market based on end-use vertical is further classified as:
    • BFSI- Banking, financial services and insurance
    • Manufacturing and retail
    • Telecom and IT
    • Government
    • Energy and utility, etc.

Risk analytics is expected to draw large revenues from BFSI sector. Recent times have seen developing countries perform better than the developed economies. This causes currency fluctuations and entails considerable risk. In the face of this current economic climate, BSFI sector is demanding improved risk analytics solution. State-of-art risk analytics tools are an absolute necessity for BSFI sector as they have to spot potential frauds using statistical models.

Main Drivers of Risk Analytics Market

  1. Market risk augmentation owing to:
  • Lack of economic stability
  • Market competitiveness
  1. Stringent regulations and policies are causing a surge in the demand of risk analytics software. Following are some policies responsible for the increased demand:
  • Basel I and II
  • Comprehensive Capital Analysis and Review
  • Dodd-Frank Wall Street Reform
  • Consumer Protection Act (CCAR/DFAST)

Small and medium sized enterprises lack cognizance of risk analytics tools. Moreover, a hefty amount of money is required for the installation of risk analytics tools. These issues are likely to hinder the growth of risk analytics market.

A developed IT sector and authoritative presence of blue chip companies are the key factors boosting the development of risk analytics market. North America is expected to hold majority of the market share in risk analytics market. Significant growth in risk analytics market is likely to occur in the Asia Pacific region. The growing competition in the market and fluctuations in currency will fuel the demand of risk analytic tools.

Major Vendors in Risk Analytics Market

  • IBM Corporation
  • SAP SE
  • Tata Consultancy Services Ltd.
  • SAS Institute
  • Oracle Corporation, etc.

With the rise in global risk, companies have to adopt new approaches to analyze risk. Big data and artificial intelligence are paving the way for the development of revolutionary strategies. CEOs are seeking the valuable input of insurers to curb the threat of cybercrime. Risk teams are turning into strategic advisors.

To know more about risk analytics follow Dexlab Analytics- a premium analytics training institute in Delhi. To gain proficiency in credit management tool, enroll for their credit risk modeling courses.

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How Credit Unions Can Capitalize on Data through Enterprise Integration of Data Analytics

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credit risk analysis

To get valuable insights from the enormous quantity of data generated, credit unions need to move towards enterprise integration of data. This is a company-wide data democratization process that helps all departments within the credit union to manage and analyze their data. It allows each team member easy-access and proper utilization of relevant data.

However, awareness about the advantages of enterprise-wide data analytics isn’t sufficient for credit unions to deploy this system. Here is a three step guide to help credit unions get smarter in data handling.

Improve the quality of data

A robust and functional customer data set is of foremost importance. Unorganized data will hinder forming correct opinions about customer behavior. The following steps will ensure that relevant data enters the business analytics tools.

  • Integration of various analytics activity- Instead of operating separate analytics software for digital marketing, credit risk analytics, fraud detection and other financial activities, it is better to have a centralized system which integrates these activities. It is helpful for gathering cross-operational cognizance.
  • Experienced analytics vendors should be chosen- Vendors with experience can access a wide range of data. Hence, they can deliver information that is more valuable. They also provide pre-existing integrations.
  • Consider unconventional sources of data- Unstructured data from unconventional sources like social media and third-parties should be valued as it will prove useful in the future.
  • Continuous data cleansing that evolves with time- Clean data is essential for providing correct data. The data should be organized, error-free and formatted.

Data structure customized for credit unions

The business analytics tools for credit unions should perform the following analyses:

  • Analyzing the growth and fall in customers depending on their age, location, branch, products used, etc.
  • Measure the profit through the count of balances
  • Analyze the Performances of the staffs and members in a particular department or branch
  • Sales ratios reporting
  • Age distribution of account holders in a particular geographic location.
  • Perform trend analysis as and when required
  • Analyze satisfaction levels of members
  • Keep track of the transactions performed by members
  • Track the inquires made at call centers and online banking portals
  • Analyze the behavior of self-serve vs. non-self serve users based on different demographics
  • Determine the different types of accounts being opened and figure out the source responsible for the highest transactions.

User-friendly interfaces for manipulating data

Important decisions like growing revenue, mitigating risks and improving customer experience should be based on insights drawn using analytics tools. Hence, accessing the data should be a simple process. These following user-interface features will help make data user-friendly.

Dashboards- Dashboards makes data comprehensible even for non-techies as it makes data visually-pleasing. It provides at-a glance view of the key metrics, like lead generation rates and profitability sliced using demographics. Different datasets can be viewed in one place.

Scorecards- A scorecard is a type of report that compares a person’s performance against his goals. It measures success based on Key Performance Indicators (KPIs) and aids in keeping members accountable.

Automated reports- Primary stakeholders should be provided automated reports via mails on a daily basis so that they have access to all the relevant information.

Data analytics should encompass all departments of a credit union. This will help drawing better insights and improve KPI tracking. Thus, the overall performance of the credit union will become better and more efficient with time.

Technologies that help organizations draw valuable insights from their data are becoming very popular. To know more about these technologies follow Dexlab Analytics- a premier institute providing business analyst training courses in Gurgaon and do take a look at their credit risk modeling training course.

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

DexLab Analytics is Heading a Training Session on CRM Using SAS for Wells Fargo & Company, US

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credit risk modelling

We are happy to announce that we have struck gold! Oops, not gold literally, but we are conducting an exhaustive 3-month long training program for the skilled professionals from Wells Fargo & Company, US. It’s a huge opportunity for us, as they have chosen us, out of our tailing contemporaries and hope we do fulfill their expectations!

Wells Fargo & Company is a top notch US MNC in the field of financial service providers. Though headquartered in San Francisco, California and they have several branches throughout the country and abroad. They even have subsidiaries in India, which are functioning well alike. Currently, it is the second-largest bank in home mortgage servicing, deposits and debit cards in the US mainland. Their skilled professionals are adept enough to address complicated finance-induced issues, but they need to be well-trained on tackling Credit Risk Management challenges, as CRM is now the need of the hour.

Our consultants are focused on imparting much in-demand skills on Credit Risk Modeling using SAS to the professionals for the next three months. The total course duration is of 96 hours and the sessions are being conducted online.

 

 

 

 

In this context, the CEO of DexLab Analytics said, “This training session is another milestone for us. At DexLab Analytics, being associated with such a global brand name, Wells Fargo is a matter of great honor and pride, which I share with all my team members. Thanks to their hard work and dedication, we today possess the ability and opportunity to conduct exhaustive training program on Credit Risk Management using SAS for the consultants working at Wells Fargo & Company.”

“The training session starts from today, and will last for three-months. The total session will span over 96 hours. Reinforcing our competitive advantage in the process of development and condoning data analytics skills amongst the data-friendly communities across the globe, we are conducting the entire 3-month session online,” he further added.

Credit Risk Management is crucial to survive in this competitive world. Businesses seek this comprehensive tool to measure risk and formulate the best strategy to be executed in future. Under the umbrella term CRM, Credit Risk Modeling is a robust framework suitable to measure risk associated with traditional crediting products, like credit score, financial letters of credit and etc. Excessive numbers of bad loans are plaguing the economy far and large, and in such situations, Credit Risk Modelling using SAS is the most coveted financial tool to possess to survive in these competitive times.

In the wake of this, DexLab Analytics is all geared up to train the Wells Fargo professionals in the in-demand skill of CRM using SAS to better manage financial and risk related challenges.

To read our Press Release, click:

DexLab Analytics is organizing a Training Program on CRM Using SAS for Wells Fargo Professionals

 

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

Join Us at a Free Live Demo Session Today, On Credit Risk Modelling With SAS

Posted on by Dexlab

Learning is almost close to being free with the ascent of the internet era. People keen on learning new things need not go across the world or even migrate to different cities. They can simply open their browser and gather as much knowledge as they want online while watching tutorials, reading articles and guides and watching free demo sessions. This convenience is now available for the challenging field of data analytics as well, as DexLab Analytics the premiere data analytics training institute in the country is offering a free live demo session on Credit Risk Modelling using SAS this Saturday at 5 PM.

 

Join us at a free live demo session today, on Credit Risk Modelling with SAS

 

To join our demo session all you have to do is register for the same with an email directly to us at hello@dexlabanalytics.com or even drop in a line showing interested at our contact us form. Then all that is left to do is to make yourself comfortable with keen ears and eyes at 5 PM sharp in front of the computer screen. The demo session is to be held today (at 15/10/2016) live, online and will be completely free. Continue reading “Join Us at a Free Live Demo Session Today, On Credit Risk Modelling With SAS”

Introduction To Credit Score Cards: Its Use in Crisis

Posted on by Dexlab

The incident we are about to describe took place during 2009 circa at a party, a year in which the world was going through one of its worst financial crisis for the longest time. Every average bloke on the streets was aware of terms like mortgage-backed securities (MBS), sub-prime lending and credit crisis, after all these are the reasons for his plight.

 

Introduction To Credit Score Cards: Its Use in Crisis

 

But at this party we are speaking of, I was fortunate enough to meet with an informed and highly compassionate elderly woman, and after a few minutes of discussion the topic came to what we here do for a living. She wanted to know more about credit scorecard systems. As I further went on to explain the details of how this system works, her expression changed from being just plainly curious to angry to pained. Continue reading “Introduction To Credit Score Cards: Its Use in Crisis”

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