Conor Larkin - Recruiter Profile | Harnham Recruitment

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Conor Larkin

Principal Recruitment Consultant - UK

Bio

Conor began his career at Harnham when he joined the Credit Risk team as a Recruitment Consultant in 2016. He earned promotion to Senior Consultant after a very successful first year working across Risk Analytics

His consultative approach to recruitment enables Conor to understand the needs of his clients and candidates so he can provide tailored staffing and career solutions in the Risk Analytics space.

My jobs

Senior Strategy Analyst

Salary

£38000 - £47500 per annum + Competitive Benefits

Location

London

Description

Credit Strategy role at a fast-growing fintech!

Reference:

21301

Expires on

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Credit Risk Analyst

Salary

£40000 - £65000 per annum + Competitive Benefits

Location

London

Description

A top tier, international lender specialising in unsecured lending is looking for a bright analyst to join the business as a Lead Credit Portfolio Analyst

Reference:

44995,/cl

Expires on

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Credit Risk Modelling Consultant

Salary

£40000 - £65000 per annum + Competitive Benefits

Location

Leeds, West Yorkshire

Description

I'm recruiting for a Credit Risk Modelling Consultant (permanent role NOT contract) for a well know management consultancy business

Reference:

49697/cl...

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Lead Credit Risk Analyst

Salary

£45000 - £65000 per annum + 15% bonus + 12% pension

Location

London

Description

A lead Credit Risk Analyst role at an unsecured lender. Great role for anyone looking to drive data-driven lending strategies in a fast-paced business

Reference:

112365/cl

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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.

Mitigating Risk In The Financial Services Sector With Machine Learning

Data & Analytics is an industry that is constantly evolving and is always using the latest technology to innovate its services and capabilities. More recently, these advancements have moved in areas such as Artificial Intelligence (AI) and Machine Learning (ML). Machine Learning is a method of data analysis, under the branch of Artificial Intelligence, that allows systems to learn from data, identify patterns and ultimately make decisions with little to no human intervention. Used across a vast range of sectors, this arm of Data & Analytics has become widely popular, especially within highly-advanced industries such as Finance. Since the 2008 financial crash, at the top of the agenda for many Financial Institutions (FIs) was, and still is, the need to protect business, increase profitability and, possibly most importantly, address the abundant inadequacies of risk management. This includes risks posed by consumers such as liquidity, insolvency, model and sovereign, as well as any internal process and operational risk the FIs may also be facing through any failures or glitches. Machine Learning has played a crucial role in improving the quality and precision of FIs risk management abilities. In HPC Wire, it has been reported that the use of AI and ML within the financial sphere to mitigate risk, improve insights and develop new offerings may generate more than $250 billion for the banking industry. How does ML work? By using incredibly large data sets, drawn (with consent) from consumers, ML can learn, and predict, patterns in consumer behaviour. This can be done in one of two ways: through supervised learning tools, or unsupervised learning tools. Explained by Aziz and Dowling; “In supervised learning you have input data that you wish to test to determine an output. In unsupervised learning, you only have input data and wish to learn more about the structure of the data.” How do banks use ML to mitigate risk? In FIs, a mix of the two ML tools are used. Most commonly, we can expect to see learning systems such as data mining, neural networks and business rules management systems in play across a lot of banks. These models work in tandem to identify relationships between the data given from the FIs and their consumers – from their profiles to their spending habits, credit card applications to recorded phone calls – which then build ‘character profiles’ of each individual customer. The process can then begin, spotting signs of potential risk factors. This may include debt, fraud and/or money laundering. Here we break down two key examples. Fraud Thanks to ML, customers have become accustomed to incredibly quick and effective notification of fraudulent activity from their banks. This ability from FIs comes from large and historical datasets of credit card transactions and machines which have been algorithmically trained to understand and spot problematic activity. As stated by Bart van Liebergen; “The historical transaction datasets showcase a wide variety of pre-determined features of fraud, which distinguish normal card usage from fraudulent card usage, ranging from features from transactions, the card holder, or from transaction history.” For example, if your usual ‘character profile’ is known by ML tools to spend between £500 - £1000 per month on your credit card, and suddenly this limit is overtly exceeded, fraudulent activity tags will be alerted, and the freezing of your account can be done in real-time. Credit applications When borrowing from a bank or any other FI, consumers must undertake a credit risk assessment to ensure that they have a record of paying back debt on time, and therefore not adding greater cost, and risk, to the lender. Traditionally, FIs have approached credit risk with linear, logit and probit regressions but, serious flaws were found in these methods, with many applications being left incomplete. In this space, the evidence for the effectiveness of ML is overwhelming. Khandani et al. found that FIs using ML to analyse and review credit risk can lead to a 25 per cent cost saving for the FI involved. These ML models come in various shapes and sizes, with the most common being instantaneous apps or websites which allow users and their banks to have access to real-time scoring, data visualisation tools and business intelligence tools. The risk of risk management with ML Like with any AI or ML application or tool, there will always be cause for concern and real need to always remain vigilant. While ML has shown to be an invaluable tool across lower risk areas, the complexity of more statistical areas of banking, such as loans, has proven to be an Achilles heel for the technology. This usually stems from bias, a perpetual problem for AI and ML across all industries. Technology Review notes that “There are two main ways that bias shows up in training data: either the data you collect is unrepresentative of reality, or it reflects existing prejudices.” Data, analytics, AI and ML are notoriously non-diverse working sectors. The person behind the screen creating learning algorithms tends to be white and male, and very unrepresentative of the whole society that the machine learning tool will serve. Over the years, we have heard numerous accounts of unfair and unjust machines, which have learned from a very narrow and unrepresentative dataset, which stems from the lack of diversity amongst the employees within the Data & Analytics industry. For example, Microsoft’s racist bot and Amazon’s sexist recruitment tool, both clear examples that ML and AI are not ready to be used on their own, and humans still need to play an integral part in decision making. Banks and FIs must be aware of the, potentially lethal, consequences that bias in ML may present. Lenders must be careful to ensure they are working within the guidelines of fair lending laws and that no one group of people are being penalised for no reason other than issues within the technology and its algorithms. It is vital that the humans behind the technology don’t rely on ML to provide them with an answer 100 per cent of the time but, instead, use it to aid them in their decision making when it comes to risk mitigation. If you’re looking for a role in Data & Analytics or are interested in finance or Risk Analytics, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to learn more.

by Conor Larkin

18. March 2021

Risk Analytics & Your Job Search

Risk Analysis is a daily part of our decision-making process. Its influences are felt in how we prioritise projects. Hello, project management. It determines when we take breaks. And in the working from home or remote working culture, lines between personal and professional life are soon blurred. Our decision-making ratchets through microanalyses of next steps, words to use, when to log off the computer, and what time to make lunch or dinner. Almost without realising it, we're using the SWOT matrix determine risk. That's just in our personal day-to-day lives. Organisations have been using these strategic planning techniques as a daily part of their enterprise lives. So, imagine this. You determine your strengths, weaknesses, opportunities, and threats (SWOT) to write your CV, land the interview, and get the job. Aren't you already on your way to helping your company determine their risk on a bigger scale? Isn't Risk Analysis the Same as SWOT? Not exactly. While you are identifying, measuring, and analysing issues, the idea is to avoid or lessen risk. In the movie War Games, the main character decides he's going to play a game. But, neither the computer nor the main character understands the game is not a game. They have no idea what risk they've unleashed as keystrokes begin to lead to war. Militaries use Risk Analysis regularly to determine if war should begin, estimated casualties and cost just for a start. But, in the end, it's usually decided peace keeps the world away from war after all the risk has been analysed. Though most businesses and individuals don't have the risk of war at their doorstep, there are extenuating circumstances which must be determined to avoid risk. This can be anything from natural disasters to legislation to physical requirements and locations. The SWOT technique is a tool within strategic planning as are Risk Analytics. Let's take a look at the benefits of Risk Analysis. It can help your business improve security, manage costs, and plan for any surprises. Whether it helps you in your job search or manage your business once you're hired, a combination of SWOT and Risk Analytics can help your decision-making process shine. Done well, Risk Analysis is an important tool for managing costs associated with risks, as well as for aiding an organisation's decision-making process. SWOT your way to a Successful Job Search So, first, let's take a look at what SWOT is and isn't. This type of analysis is a tool most often found in strategic planning for organisations. But, it's not the only tool when assessing risk. Like any data profession, you'll want to gather, collect, and analyse the information before you. And when it comes to the job search, knowing yourself and your self-awareness levels may play a bigger part than you imagine. Skipping ahead to the interview from your 'foot in the door' CV and cover letter both delivered via video, of course, you begin to plan for your interview. "What are your biggest strengths and weaknesses?" your hiring manager asks. You've come well-prepared for this question because you've done your SWOT analysis. From the moment you decided your areas of expertise, your roles in organisations, and any areas you know you need to improve but can turn into a positive. You've pre-assessed your strengths, weaknesses, opportunities or obstacles, and threats. Strengths – What characteristics do you possess which gives you an advantage over your competition? Have you cross-trained across a variety of departments? Do you have a knack for telling a compelling data narrative story to help make leadership make an informed decision? Weaknesses – Where could you use more training? Are you looking for a business that offers it in-house or do you need a certification or class to give you a leg up over your competition? What puts you at a disadvantage and how would find a work around? What can you do to improve? Opportunities or Obstacles – Has your experience taught you a new way of doing things within the industry? Does your experience extend from working alone to strong member of a team? Was the team in-house or scattered around the world? How did it affect your working style and what did you learn from it? Threats – Threats may seem at odds with a job search, but…that was then. This is now. Threats are simply external forces which cause trouble in your planning. In other words, this is your risk assessment. What risks are involved and of those risks which will have less effect and which will have more on your desired outcome? Performing this technique in your personal and professional life helps you peel back the layers of you. What has your education prepared you for? Your work experience? The projects you've chosen or been assigned to? It's all leading somewhere, right? This is where you match your strengths to opportunities. Hello, dream job. If you're looking for your next role in the Data & Analytics, we may have a job for you. Take a look at our current opportunities or get in touch with one of our expert consultants to learn more.

by Conor Larkin

12. November 2020

Being Human: How the Interview Process is Evolving

Should we make our interview processes more like a talent show? That’s what a job centre in France thought when they introduced ‘This Is The Job’, an interview more in the style of ‘The Voice’ than a traditional Q&A session. Complete with spinning chairs and buzzers, this ‘technique’ has been swiftly brought to an end following public outcry. But whilst it might not be the best idea to base the recruitment process on a popular TV show (let’s not use ‘Bodyguard’ as an inspiration for problem-solving tasks), we are seeing an evolution in how interviews are conducted. Here’s a look at some of the most popular trends we’re seeing businesses apply to their recruitment processes. Cultivating a culture Perhaps the most significant change we’re seeing at the moment is the increased prominence placed on cultural fit. No longer an afterthought, this is now a make or break factor for most employers. Interview panels are looking for a candidate’s personality to come through when they discuss previous projects they’ve worked on. They’re keen to know that they can explain their findings to a wider audience. This includes being open about where they can improve and showing a level of humility. We’ve seen candidates rejected for being overly-defensive when receiving critiques of their technical work. Alongside this, businesses are adapting their interviewing techniques to reflect this more human approach. First-round telephone interviews are being replaced by video calls, offering an experience closer to face-to-face. Agencies, in particular, are taking interviews out of the office and into coffee shops, with the ambition of creating a more social interaction. All of these changes should mean that both businesses and candidates have a better understanding of what they’re signing up for before an offer is made or accepted. Ironing out the creases Given the fast pace of working life, finding time to dedicate to an interview process is a challenge for businesses and candidates alike. Fortunately, we’re seeing processes streamlined. Whereas we had seen a trend for employers sending out time-consuming tasks to thoroughly test people’s abilities, the amount time required led to delayed processes and candidates dropping out. As a result, businesses are now including technical screenings within the interview itself, alongside short demos, presentations of work and online coding sessions. By keeping things simple, we’re now seeing less candidate drop off early in the process. This, alongside combining technical and competency questions, has resulted in a more concentrated, yet just as detailed, way of assessing an applicant’s suitability for a role. Getting hands on Employers have always looked for someone who can walk the walk, as well as talk the talk. Now they’re taking matters into their own hands by requiring candidates to react to real world examples. Most commonly, we’re seeing these take the form of case studies, generally falling into one of two categories: Quantitative, where a relevant business situation and data are provided and need to be addressed. Conceptual, where there are no figures, and the interviewer is trying to gain an insight into the candidate’s approach and thought processes. On top of this, we’re beginning to see new methods introduced that test applicants even further. Job Auditions are becoming an increasingly popular way of assessing how well a candidate can perform in a real-world situation. There’s even talk of introducing Virtual Reality to push this idea even further within a controlled simulation. Regardless of what the future may hold, companies are clearer than ever with what they’re looking for in the interview process. Don’t be surprised if we continue to see innovations that offer more depth into a candidate’s true behaviour, personality and working styles. If you’re on the lookout for a new role, we can support and guide you through the interviewing process. We have a variety of roles in both Junior and Senior positions, both Contract and Permanent. Take a look at our latest roles or get in touch with one of our expert consultants to see how we can help you progress you career.

by Conor Larkin

25. October 2018

The fight for senior risk analysts

If you have had difficulties hiring a Senior Risk Analyst recently, and you’re scratching your head as to why – this article should hopefully shed some light on the matter. Year on year we have seen the demand for Senior Risk Analysts skyrocket, making them the most sought after analysts in the ever-evolving world of risk. It’s no surprise that since 2012, the growth of challenger banks and the subprime sector means hiring candidates with experience in risk/FS alongside experience of SAS, has become even more challenging.The growth in demand just can’t be matched by supply. Risk analysts with 2-5 years’ experience are the golden eggs within this rapidly growing and advancing market and it seems that everyone wants them. If a strong Senior Risk Analyst comes on the market, they can have as many as 15 roles to consider at any one time – now this is great for the candidate but it is a recruitment nightmare for the companies looking to get this person on board. I have seen the good, the bad and the ugly when it comes to recruitment processes and these 5 tips below will give you a huge advantage in securing your perfect candidate in the face of fierce competition!1. You must have a slick and efficient recruitment processThe days of a 3+ stage recruitment process for Senior Analysts are over. Why do three one-hour interviews when you can cover it all in one stage and send a message of intent to the candidate? If the recruitment process is slow, unorganised and laborious, a candidate will perceive that this is what it is like to work for the company. Ultimately, the quicker the process, the more chance you will have of securing your perfect candidate.2. Sell, sell, sellAt the end of the day, the purpose of an interview is for the candidate to show off their skills in front of a prospective employer. But as the interviewer, you have a duty to sell the role as much as possible because if you don’t, I can guarantee your competitors will. Another big sell is skipping any testing at the first stage – face-to-face interaction as a first stage is such a good way to get a candidate engaged in a process. Sometimes, there may be 2-3 stages before candidates have even met anyone in the company!3. It’s the little things that make a big differenceBelieve it or not, some people don’t like regular contact from recruiters requesting updates on their situation (I couldn’t believe it!). One really nice touch I have seen work is a hiring manager calling their preferred candidate from their personal mobile in between interviews to check in and see how things were going – little things like this can make a big difference in the long run, and only take a couple of minutes.4. Best offer firstThis is the most frustrating thing that I come across in recruitment. Companies sift through a huge number of CVs sent through by recruiters/direct applicants, spend countless hours interviewing candidates, and when they finally find the perfect candidate, they under-offer them to see whether they can get them slightly cheaper… It all comes back to intent, and by offering the best possible offer first time, it sends a positive and decisive message to any prospective candidates.5. Flexing on skills – have you considered it?Although it may not always be ideal to begin with, employers flexing on skills and experience is something I have seen work a number of times over the past 12 months. For example, a role may be open for 6 months whilst the employer is trying to find their perfect candidate but within that time, they could have hired someone who didn’t quite tick all of the boxes, trained them up in 3 months and saved themselves a lot of time and money! If you think the candidate can pick things up quickly, definitely consider them.It’s never going to be a seamless process when attempting to hire a Senior Risk Analyst so don’t make it harder for yourself!

by Conor Larkin

27. July 2016

Callcredit win Nationwide Business

Callcredit to support Nationwide's new credit application functionality. Nationwide, an international building society, has decided to integrate Callcredit Information Group’s credit and affordability suite into its new credit application functionality. Nationwide will be able to effectively identify the credit risk associated with each applicant through the real time data solution supplied by Callcredit. This solution was created to deliver a credit data summary of a customer’s credit file, accompanied by a credit risk score. By automating applications to Callcredit’s affordability suite, Nationwide will be enabled to validate an applicant’s income and affordability when considering personal loan applications. This affordability check is intended to simplify responsible lending decisions as it regards over-indebtedness rather than just assessing a customer’s credit history. Ian Laing, chief risk officer at Nationwide, said: “In reviewing suppliers of credit and affordability data, we have consistently found Callcredit’s approach to be collaborative and client-focused, with the result that we get incremental value from using their data.” Kaye Rickards, business development manager at Callcredit, said: “Credit checks and robust affordability assessments are a crucial part of the application process. “As consumers continue to feel the squeeze on their disposable income it is reassuring that Nationwide are actively seeking the means to ensure they continue to lend responsibly.” Click here for the article on the web.

by Conor Larkin

02. December 2013

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