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

Posted on April 19, 2018May 23, 2020 by Dexlab

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.

#WeAreDelighted: DexLab Analytics is honored to conduct a comprehensive 3-month long training program for Wells Fargo, US on Credit Risk Modeling using SAS. Spread over 96 hours, the session will be imparted online. #CreditRisk | #SAS | #socialmedia | #india | #course | #Gurgaon
A post shared by DexLab Analytics (@dexlabanalytics) on Apr 16, 2018 at 5:42am PDT

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

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How Fintechs Help Optimize the Operation of Banking Sector

Posted on April 13, 2018April 18, 2018 by Dexlab

Financial technology- Fintech plays a key role in the rapidly evolving payment scenario. Fintech companies provide improved solutions that affect consumer behavior and facilitate widespread change in the banking sector. Changes in data management pertaining to the payment industry is occurring at a fast pace. Cloud-based solution and API technology (Application Programming Interfaces) has played a major role in boosting the start-up sector of online payment providers like PayPal and Stripe. As cited in a recent PwC report over 95% of traditional bankers are exploring different kinds of partnerships with Fintechs.

Interpreting consumers’ spending behavior has enhanced payment and data security. Credit risk modeling help card providers identify fraudulent activities. The validity of a transaction can be checked using the GPS system in mobile phones. McKinsey, the consulting firm has identified that the banking sector can benefit the most from the better use of consumer and market data. Technological advancements have led to the ease of analyzing vast data sets to uncover hidden patterns and trends. This smart data management system helps banks create more efficient and client-centric solutions. This will help banks to optimize their internal system and add value to their business relationship with customers.

Role of Big Data

Over the past two years, the digital revolution has created more data than in the previous history of humankind. This data has wide-ranging applications such as the banks opening their credit lines to individuals and institutions with lesser-known credit-score and financial history. It provides insurance and healthcare services to the poor. It also forms the backbone of the budding P2P lending industry which is expected to grow at a compound annual growth rate (CAGR) of 48% year-on-year between 2016 and 2024.

The government has channelized the power of digital technologies like big data, cloud computing and advanced analytics to counter frauds and the nuisance of black money. Digital technologies also improve tax administration. Government’s analysis of GST data states that as on December 2017, there were 9.8 million unique GST registrations which are more than the total Indirect Tax registrations under the old system. In future big data will help in promoting financial inclusion which forms the rationale of the digital-first economy drive.

Small is becoming Conventional

Fintechs apart from simplifying daily banking also aids in the financial empowerment of new strata and players. Domains like cyber security, work flow management and smart contracts are gaining momentum across multiple sectors owing to the Fintech revolution. For example workflow management solution for MSMEs (small and medium enterprises) is empowering the industry which contributes to 30% of the country’s GDP. It also helps in the management of business-critical variables such as working capital, payrolls and vendor payments. Fintechs through their foreign exchange and trade solutions minimizes the time taken for banks to processing letter of credit (LC) for exporters. Similarly digitizing trade documents and regulatory agreements is crucial to find a permanent solution for the straggling export sector.

Regulators become Innovators

According to the ‘laissez-faire’ theory in economics, the markets which are the least regulated are in fact the best-regulated. This is owing to the fact that regulations are considered as factors hindering innovations. This in turn leads to inefficient allocation of resources and chokes market-driven growth. But considering India’s evolving financial landscape this adage is fast losing its relevance. This is because regulators are themselves becoming innovators.

The Government of India has taken multiple steps to keep up with the global trend of innovation-driven business ecosystem. Some state-sponsored initiatives to fuel the innovative mindset of today’s generation are Startup India with an initial corpus of Rs 10,000 crore, Smart India Hackathon for crowd-sourcing ideas of specific problem statements, DRDO Cyber Challenge and India Innovation growth Program. This is what enabled the Indian government to declare that ‘young Indians will not be job seekers but job creators’ at the prestigious World Economic Forum (WEF).

From monitoring policies and promoting the ease of business, the role of the government in disruptive innovations has undergone a sea change. The new ecosystem which is fostering innovations is bound to see a plethora of innovations seizing the marketplace in the future. Following are two such steps:

IndiaStack is a set of application programming interface (APIs) developed around India’s unique identity project, Aadhaar. It allows governments, businesses, start-ups and developers to utilize a unique digital infrastructure to solve the nation’s problems pertaining to services that are paperless, presence-less and cashless.
NITI Ayog, the government’s think tank is developing Indiachain, the country’s largest block chain. Its vision is to reduce frauds, speed up enforcement of contracts, increase transparency of transactions and boost the agricultural economy of the country. There are plans to link Indiachain to IndiaStack and other digital identification databases.

As these initiatives start to unfold, India’s digital-first economy dream will soon be realized.

Advances in technologies like Retail Analytics and Credit Risk Modeling will take the guesswork and habit out of financial decisions. ‘’Learning’’ apps will not only learn the habit of users but will also engage users to improve their spending and saving decisions.

To know more about risk modeling follow Dexlab Analytics and take a look at their credit risk analytics and modeling training course.

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Breaking the Misconceptions: 4 Myths Regarding Data-Driven Financial Marketing

Posted on March 23, 2018May 23, 2020 by Dexlab

A majority of low-mid financial services companies toil under the wrong notion that owing to their capacity, size and scope, the complex data-driven marketing tactics are simply out of their reach – this is not true and frankly speaking quite a shame to consider even.

Over the past decade, the whole concept of data analytics has undergone a massive transformation – the reason being an extensive democratization of marketing tactics. Today’s mid-size financial service providers can easily implement marketing initiatives used by dominant players without any glitch.

Besides, there are several other misconceptions regarding data and its effect on financial marketing that we hear so often and few of them are as follows:

Myth1 – Legally, banks are only allowed to run broad-based advertising

While it’s partially true that there are certain restrictions on banking institutions when it comes to target consumers, based on income, age, ethnicity and other factors, marketers can still practice an array of tactics, both online and offline.

Marketers can leverage a pool of data for online and offline marketing to formulate data models, keeping in mind the existing customers need and preferences. Once you have an understanding of their online behavior, how they use the data power to carry out transactions, these insights can be applied to attract new customers, who exhibit similar behaviors.

Myth 2 – Data-driven marketing doesn’t bolster customer relationship

It’s a fact, Millennials, especially wants to be aware about financial services and its associated products, and are keen to understand how can banks lend an additional support to their living and social life. Companies can start building relationship based out of it, while implementing data-driven marketing perspective into them.

Myth 3 – You need a huge budget and an encompassing database to drive marketing campaigns

Corporate honchos and digital natives certainly maintain sprawling in-house database to boost marketing activities, but don’t be under the impression that mid-size institutions cannot leverage much from virtual datamart. The impressive SaaS-based solutions houses first-party data, safely and securely and offer you mechanisms that let you integrate with other third-party data, both online and offline.

Datamarts let mid-size marketers achieve a lot of crucial task success. Firstly, you will be able to link online user IDs with offline data – this lets you derive insights about your current customers, including their intents, interests and other details. The most important thing is that it will usher you to build customer models that could target newer customers for your bank.

Myth 4 – Data-driven marketing is too much time-consuming

A lot of conventional marketers are of the opinion data-driven marketing is a huge concept – time-consuming and labor-intensive. But, that’s nothing but a myth. Hundreds and thousands of mid-size companies develop models, formulate offers and execute campaigns within a 30-day window using a cool datamart.

However, the design and execution part of campaigns need no time, whereas the learning part needs some time. You need to learn how to develop such intricate models, and that’s where time is involved.

To ace on financial models, get hands-on training from credit risk analysis course online – DexLab Analytics offers superior credit risk management courses, along with data analytics, data science, python and R-Programming courses.

In the end, all that matters is prudent marketing campaigns powered by data yields better results than holding onto these misconceptions. So, break the shackles and embrace the power of data analytics.

The article has been sourced from – http://dataconomy.com/2017/08/5-misconceptions-data-driven-marketing

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How Credit Risk Modeling Is Used to Assess Credit Quality

Posted on December 30, 2017February 13, 2018 by Dexlab

Given the uproar on cyber crimes today, the issue of credit risk modeling is inevitable. Over the last few years, a wide number of globally recognized banks have initiated sophisticated systems to fabricate credit risk arising out of significant corporate details and disclosures. These adroit models are created with a sole intention to aid banks in determining, gauging, amassing and managing risk across encompassing business and product lines.

The more an institute’s portfolio expands better evaluation of individual credits is to be expected. Effective risk identification becomes the key factor to determine company growth. As a result, credit risk modeling backed by statistically-driven models and databases to support large volumes of data needs tends to be the need of the hour. It is defined as the analytical prudence that banks exhibit in order to assess the risk aspect of borrowers. The risk in question is dynamic, due to which the models need to assess the ability of a potential borrower if he can repay the loan along with taking a look at non-financial considerations, like environmental conditions, personality traits, management capabilities and more.

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Analyze the Risk of a Borrower with These Sure-fire Credit Risk Analytics Techniques

Posted on December 28, 2017February 13, 2018 by Dexlab

It’s a hard but true fact – no more do businesses survive without leverages. In a quest for success and expansion, they need to resort to debt, because equity alone fails to ensure survival. Be it funding a new project, fulfilling working capital requirement or expanding business operations, an organization needs funding for various corporate activities.

Talking of India, the credit market scenario in here is not so matured in comparison to other developed countries; hence there exists an excessive dependency level on conventional banking structure. Nevertheless, raising finance from issuance of bonds by companies is also not so rare – majority of companies in need of capital raise money from bonds and shares and this practice is widely prevalent throughout the nation.

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Incredible Future Possibilities of Market Risk Analytics

Posted on December 18, 2017May 23, 2020 by Dexlab

Global risks are burgeoning; companies of all sizes are seeking the perks of risk analytics and management. Smart companies are realizing the change is coming from people as well as recent technological breakthroughs, including Big Data and AI. And CEOs are improvising their risk teams, and transforming them into perceptive strategic advisors to address budding dangerous threats like cybercrime.

Modern risk analysts have accurate knowledge about risk, artificial intelligence and cyber security – so, it’s time they get an opportunity to show a greater presence in the stoic boardrooms as strategic advisors. AI, the cutting-edge risk analytics tool surfaced out to enhance the inexorable march of big data. As such, their importance in the organization in assessing risk has greatly increased.

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Market Risk Management 101: Types of Market Risks and How to Manage Them

Posted on November 30, 2017July 2, 2026 by Dexlab

Last year, Britain opted to leave the European Union – and that created spiking fluctuation and acute market uncertainty across the globe.

Most of the investors out there know investment involves risks and rewards, just like head and tail in a coin and so do the analysts. Higher the risk, better are the chances to gain potential rewards. As a result, it is critical for both an investor and analyst to understand the true nature of market risks that influences the market conditions and controls the shooting volatility and the ways to manage those risks.

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Common Market Risks

Relevant market risks depend largely on the nature of investment as well as geographic boundaries. Some of the key market risks are as follows:

Interest Rate Risk – It is the risk of a decrease in the value of a security owing to changes in interest rates. The rate of change of interest rates is inversely proportional to bonds – based on a rationale that a bond is the future security of a healthy stream of payments – hence as interest rate rises, the price of the issued bonds decreases.

Inflation Risk – It relates to the risk that gets affected as the prices of goods and services increases reducing the value of money. This risk results in affecting the value of investments in a negative way. It decreases the purchasing power of money, thereby reducing the value of investment. Sometimes inflation risk is also known as Purchasing Power Risk.
Currency Risk – This type of risk arises when your money needs to be converted to a different currency for investment purposes. Here, a small change in exchange rates between the home currency and US dollars can affect your investment return.
Liquidity Risk – It refers to the risk of not being able to fulfill certain investment requirements quickly for a price that determines the true value of the asset. Sometimes, one may face difficulties in selling the investment due to a lack of buyers, resulting in a drastic decrease of investment value of that product until someone is ready to pay for it. Foreign investments, over-the-counter markets and small-capitalization stocks are some of the high liquidity risks items.
Sociopolitical Risk – The socio-political environ, such as war, terrorist attack, election and corruption affects the market conditions. They affect investor perceptions, resulting in severe oscillation in stock prices.

Managing Market Risk

Well, you can’t control the market risks from taking a front seat in your financial life, though you can take some steps to manage and mitigate them.

As globalization seeped through all leading economies and market segments, a majority of fintech institutions started realizing the criticality of an enhanced operational risk, especially related to cyber-security, IT failures and data theft. Amid this, cyber risks and data theft issues posed key challenges, followed by IT failures and outsourcing issues. The revolution of digitization did many goods to our society, but the moment banks got dependent on single computer networking setups, the vulnerability of confidential customer data leakage multiplied. As a result, the need for data analysts and market researchers spiked up – they are the trained souls who possess both the experience and expertise to tackle diverse investment portfolios for clients in the best way possible to fetch maximum profits.

For that, affluent market risk courses in Delhi are available around – train your mind well, before taking the big leap in the big field of data analytics. Once you are done, reach DexLab Analytics – their comprehensive Market Risk Modelling using SAS courses are top-of-the-line courses in the industry at present.

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Credit Risk Modelling: How Indian Fintech Startups Are Hitting a Home Run

Posted on November 20, 2017June 27, 2020 by Dexlab

After scoring high with top notch conglomerates, Indian economy is heating up more than ever – because of flourishing Indian fintech establishments that are popping up here and now.

In this blog, we will take a deeper look down into the mechanism how startups are doing well for themselves in this competitive world from a credit risk perspective. For that, we will dig deep into the personal account of an employee working in one of the notable startups in India, which deals with data analytics product for the financial services industry – what experiences he gathered while working in a startup sector, what advices he would like share and things like that will help us crack this industry better.

DexLab Analytics offer the best credit risk analysis course.

Pointed things to learn from a fintech startup in India:

Product is king, so is its timing – Never ever compromise with a good product. Similarly, make sure the timing is right too – may be, because you waited too long, you missed the best product. It happens.

Hit the customers right away – Don’t vouch for any product, unless 10 people have validated the product. Allow at least 10 customers to use that product and then sit with them to grab some feedback. Startups work like this, so do you!

Economics is the essence, so do proper homework – Risk and Finance go hand in hand, but are distinct in nature. Get a grip on well-structured financial models – they will help you understand the credit exchange stuffs better. Streaming costs, revenues and growth in a single line will obviously put you in a better position in predicting the impact of credit risk. FYI, credit risk’s impact is endured on not only losses, but on costs too – which is surely a matter of concern.

Teamwork is the best work – Building a potent team is an art. Creating something of your own requires a substantial amount of risk, both personal and professional. Most seasoned consultants coming under a single roof to offer something unique is in itself an exciting idea – startups in India boast of an average age of 25 or 28 years in a particular company. Nevertheless, some companies also excel with a core team whose average experience is that of 10 years – across domains like tech, product, risk, operations, sales and marketing. The figures are interesting, ain’t they?

Fintech is more finance and less technology – As compared to other industries, fintechs’ operational mode is very different. Though credit risk and cost management are the founding pillars of a robust fintech business setup, none of them can make up for below-standard quality products. Offering high quality product is of supreme importance for the success of any Fintech, and if you look at fintech companies in the US and Europe you will understand why we are focusing our attention on the quality part.

While we are on the closure, there is still a lot of learning to be done – but we surely believe India is on its way to success and our fintech sector is witnessing a plethora of amazing ideas. Just keep your fingers crossed, and hope our teams pull it off in a snap.

Get credit risk modelling certification from DexLab Analytics today! Their credit risk management courses are intensive, well-researched and are written down, while keeping students’ grasping skills in mind. Go give it a shot!

Market Risk Analytics: How Top Notch Companies Are Assessing Intricate Risks

Posted on November 10, 2017May 23, 2020 by Dexlab

Risk analytics tools boost operational efficiency. But do you know what tools to implement to derive the best results?

With the burgeoning demand for big data all over the world, major corporate houses are taking risk analytics – the process of collecting, analyzing and measuring real-time data to forecast future risk for improved decision-making – to a new high.

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Category: Credit and Market Risk

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

Interested in a career in Data Analyst?