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Latest Jobs

Salary

US$100000 - US$135000 per year + Bonus

Location

New York

Description

Are you a stats master? Don't miss this opportunity to join a leading Fintech in the consumer lending space where you will build predictive scorecard models!

Salary

US$140000 - US$160000 per year + benefits

Location

New York

Description

This exciting opportunity will see you joining a leading National bank to manage a dynamic team of credit risk analysts within the retail lending sector.

Salary

US$120000 - US$150000 per year + Benefits

Location

New York

Description

This exciting Fintech, poised to disrupt the traditional credit card market using machine learning, is seeking a Credit Risk Manager to join their dynamic team

Salary

US$90000 - US$110000 per year + Benefits

Location

New York

Description

A leading Fintech is seeking a Risk Analyst to build predictive models and analyze data. This is a great opportunity to join an innovative business!

Salary

US$100000 - US$135000 per year + Bonus

Location

New York

Description

Don't miss this opportunity to join a growing fintech in the commercial lending space. Play a crucial role in loss forecasting for this dynamic business!

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Finance 4.0 – Who Determines Credit Risk in the Fourth Industrial Age?

If you’ve applied for a credit card or loan recently, you’ll be aware of the swift response you now receive. No human can crunch the numbers and make the determination that fast, right? Although big banks are now adopting Big Data, Machine Learning, and AI into their legacy processes, startups have been disrupting the sector for a few years now. As banks and credit unions scramble to keep up, Fintech innovation is bringing together machine language, analytics, and AI to help form Big Data decisions in the industry. The forward-thinking potential of these technologies has led to some real-world uses to combat fraud, offer access to alternative data sources, and suggest real-time analysis for risk. So, Robots are Determining My Credit Risk? Well, yes and no. Often, those in the financial sector are using AI to assess Credit Risk. What once required Risk Analysts to determine manually, is now done in a matter of seconds with an early warning system developed by ING, PwC, and Google. This AI-powered system helps analysts make faster and more informed decisions about potential risk. How do they do this? Using pre-set criteria, they can gauge and analyze risk based on parameters such as whether or not a client has negative media coverage or if a share price falls below a certain percentage. If the world today is based on perception, even such items as bad reviews, negative coverage, and lower than average share prices can affect determinates. In addition, having these parameters can also help determine best practices and how businesses and individuals can be given opportunities outside the scope of big bank processes. However, as data breaches continue to mar profiles of both individuals and business, Machine Learning components offer platforms the chance to stem the tide of negativity. How Machine Learning Helps Prevent Fraud This is a simple process which requires two key measures. The first is to feed the machine not just a large amount of data, but knowing the parameters set, so the machine is fed relevant information. The second is human input which gives the machine its parameters to operate by. From there, the software will take the information, gain an understanding of the data patterns, and identify any signs of fraud. If done well, the automation process will employ solutions without sacrificing quality. Machine Learning in Determining Scorecard Models Alternative data sources offer more options not only to banks and credit unions, but also to borrowers. Using Machine Learning creates a more flexible, robust model when it comes to the type of information most useful to various borrower profiles. Having profiles prepared allows for automated scorecard updates and can generate better responsiveness and intelligence of a borrower’s risk profile. This process can be empowering for both startup and big bank tech.  The Matured State of Analytics Though humans must initially input parameters, the benefits of Machine Learning using a decision engine can dig deeper and reach farther than ever before. This type of platform can gather a variety of scenarios across the industry and can constantly analyze the information, helping inform the processes of setting credit limits, loan origination, and risk-based pricing. As an extension of a modern analytics platform, these processes fill in the gaps where other platforms may lack the data or programming required to run effectively. But, as these platforms mature, they are helping to drive innovation throughout the Fintech industry and shaking up the outdated, cumbersome processes of old for a much more streamlined efficient operation. Want to inform decisioning and work with data engineers to build validation frameworks? Are you looking to get in on the ground floor of a startup opportunity in the Fintech industry?  If so, we may have a role for you. If you’d like to learn more, check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, call (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com. 

How Businesses Can Build Better Trust through Fraud Security

In the wake of Cambridge Analytica, Facebook data misuse, the Equifax breach, and the latest round of political finger pointing in regard to voter and election fraud, it’s no small wonder that demand for Fraud Analysts and Cybersecurity professionals is high.  If you search: “why should businesses hire fraud analysts”, you’ll see Amazon near the top, hiring for fraud security roles. If they’re taking action, should you be as well? And as the 2018 mid-terms near, Facebook is back in the news. Determined to curtail a repeat of the issues surrounding the 2016 election, the social media giant is working diligently to remove misinformation from the platform.  But with all these giant companies making fresh efforts to tackle fraud, what does this mean for you and your business? Fraud Security Begins at Home Your employees are your first line of defense when it comes to security of your business. No matter the size, it’s important to build a culture of anti-fraud policies right from the start. Below are a few essentials that all businesses should consider: Create a list of anti-fraud policies and share them with your employees, staff, and board members. Offer fraud training for both management and employees. Create a culture of reward for whistleblowers and open lines of communication such as a hotline/tip line. Though any business should be wary of prevailing scams and frauds in the marketplace, small businesses should be especially vigilant. Business News Daily offers additional tips for small businesses looking to prevent fraud right from the hiring process. The Customer Is Always Right: Balancing Fraud Risk Management with Customer Experience Experian® released their 2018 Global Fraud and Identity Report, based on results from 500 businesses and over 5,000 customers worldwide to understand what customers think of today’s security protocols. Trust was, far and away, the biggest talking point. With over 90% of consumers using smartphones and mobile devices followed by over 80% on laptops to search and buy, online security is paramount, and the new digital currency is trust. However, businesses are now having to grapple with the tension between managing fraud and maintaining a positive customer experience. Whilst they may need to lead customers to better solutions, businesses are finding that customers favor more familiar, time-tested methods like passwords. Ironically, those methods just might be compromising the experience they are advocating for by introducing an unintended nuisance and security risk; one-quarter of consumers have forgotten a username or password within the past six months.  Building a Fraud and Risk Management Team In order to protect against fraud, IT needs to play a big role in guiding your business and bringing multiple solutions together. However, we all understand that teams dedicated to technology, risk, fraud detection, and data security take time and resources to integrate.  So, to begin, here are a few ways to introduce Fraud Analysis and Risk Management into your business: Make data and fraud security guidelines part of your business plan and include them in your budget process – will the risk outweigh the reward? Involve staff, employees, management, and stakeholders at every level in the process. Be a hero in the eyes of your customer – balance detection with the customer experience. No matter where you are in your fraud detection and security hiring efforts, we may be able to help you. We specialize across roles of all levels in Data and Analytics on a global scale, with an eye for placing the right candidates in the right roles. For more information about recruiting top talent in the credit & risk sector, get in touch: Our West Coast Team can be reached at (415) 614 4999 or sanfraninfo@harnham.com. Our Mid-West and East Coast Teams can be reached at (212) 796 6070 or newyorkinfo@harnham.com.

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