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.
Ewan began his recruitment career in 2015, joining Harnham as a member of the Credit Risk team. His understanding of the market and ability to deliver service excellence to his customers has seen him progress to Managing Consultant level where he now runs the Risk Analytics team. Ewan continues to use his expertise to drive Harnham’s Risk Analytics services into new markets.
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.
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. ITProPortal: How computer vision can help vaccine distribution scale securely This insightful article from ITProPortal demonstrates the importance of computer vision in medicine and logistics - particularly in regards to COVID-19 vaccinations. Everyday computer vision makes it possible for the transportation and distribution of vaccines to be carried out safely. Some of the top points from the article were: Computer vision helps secure vaccine supply chains Automated procedures reduce vaccine loss and wasteDigital records can match citizens to test samples and vaccine batch The pandemic has accelerated the digital transformation. The possibilities of smartphone and computer vision are endless, and will be vital in helping maintain the future population health. There is no doubt that this technology will continue to be critical in how we navigate the future. To read more about this topic, click here. Global Government Forum: Europe’s strategy for responsible AI and data will also boost digital transformation Although the pace of digital transformation within European governments has accelerated during the pandemic, there is a long way to go. A new AI Act hopes to accelerate the digitalisation of European governments and bring them into the modern age. The AI Act is one of the core elements of Europe’s broader digital and data strategies, and focuses on sharing storage and government of data. Concerns over cultural attitudes and lack of understanding have previously delayed the digital transformation. But it is hoped this new legal framework will help accelerate the digitalisation of government in a holistic, responsible and sustainable approach. With clear data policies and the promotion of digital skills, this new legislative framework for AI and data may help European governments finally achieve their goal. To find out more about the AI act, read here. The Wire: Why scientists need to be better at visualising data Humans are visual creatures by nature, yet lack of training in data visualisation means scientists are not aware of its importance. As a result, poor data visuals can confuse readers and mislead scientist, reducing the quality and impeding the progress of scientific research. With scientific data becoming increasingly complex, scientists need to understand the importance of effective visualisation. Key notions include: Bar charts are easiest to read but are not effective for visualising continuous dataPie charts are standard practice in some disciplines yet are cognitively challenging to analysis The choice of colour is crucial and can greatly impact understanding of the graph: if colour isn’t necessary, shades of grey are best There is a long way to go with data visualisation. To make visualisations effective, designers and scientists need to work with the brain, rather than against it. To read the full article, see here. SearchBusinessAnalytics: How augmented analytics in healthcare improves patient outcomes This article explores both the benefits and problems of using augmented analytics in healthcare, with emphasis placed on the improvement of patient outcomes. Of course, digital data in healthcare is not new. The current potential of digital transformation is huge. Intelligent use of augmented analytics creates better patient satisfaction and experience. And it doesn’t stop there. Using augmented analytics in clinical trials allow healthcare providers to identify the right populations and track responses. However, without sufficient data literary, companies risk dealing with poor data quality resulting from a lack of diverse participants. Again, this is another example of the importance of data literary throughout organisations. To find out more, click here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at email@example.com.
11. June 2021
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. Computer Weekly: Microsoft outlines five-year plan for accessibility tech 1 in 5 employers have stated that they would be less likely to hire someone if they were disabled. A damning and worrying statistic highlighting the severe disability divide that still exists in the working world. In a bid to help put a stop to this serious lack of inclusion, Microsoft have teamed up with the Department for Work and Pensions (DWP) to train up to 26,000 members of staff and work coaches to help them create a more accessible recruitment and working experiences for those with disabilities. The three key areas of focus for Microsoft include: Educating workers to have a better understanding of accessibility.Showing how applied sciences can be used to create opportunities for all.Dedicating its cause to constructing inclusive office environments, whether on or offline. Brilliantly summed up by Brad Smith, Microsoft President: “Our work begins by guaranteeing that Microsoft’s personal merchandise are accessible by design, in order that as we advance our options and performance, we can assist everybody throughout the spectrum of incapacity be extra productive.” Read more on this fantastic story here. Analytics India Mag: Why Data Engineering is the fastest growing tech job in 2021 As a result of COVID-19, businesses have had to work hard to not only navigate the ‘new normal’ but thrive in it. Remaining relevant and staying one step ahead of the competition has been, and will continue to be, crucial – and for this reason alone, Data Engineering is undoubtedly going to the fastest growing sector this year and perhaps beyond. During this year’s SkillUp event, Sourav Saha, academic dean at Praxis Business School, and Prasad Srinivasa, assistant vice president at Genpact, spoke about the exciting career opportunities in data engineering. In a world driven by data, it is crucial that companies are using the data they have available to drive the success of their business. From being able to forecast future trends to gather consumer sentiment, data, and data engineers, will undoubtedly drive business success. Srinivasa highlights the three key roles he is expecting to emerge and boom over the next 6 – 12 months: Data OrchestrationData Architecture and Governance Data Strategy To read more on what to expect for the future of Data Engineers, click here. Silicon Republic: How to ensure your Life Science career thrives after COVID Life Sciences became the saviour of the COVID-19 pandemic. Those within the sector worked tirelessly to create and deliver vaccines around the world, giving us all the hope we needed to get to the end of this crisis. However, once we finally see the back of the COVID-19 pandemic, many Life Science specialists beg the question – what next? How do we continue to thrive in our careers and any future prospects post-pandemic? This insightful article from Silicon Republic highlights five key steps to ensure specialists can be prepared to take the next steps in their working journey once the dust has settled. 1. Take control and be proactive Before you do anything else, take proactive steps to look at the opportunities your current employer might be able to present you. Don’t be afraid to put yourself forward. 2. Look for innovation As the whole world adapts to the new normal, it’s more than likely your company is going to innovate to stay one step ahead of the competition. Explore where this innovation is likely to happen and put ideas forward to spearhead change. 3. Upskill across the board From those harder skills, such as technical knowledge, to softer skills, such as communication and empathy, will all need to be revisited and boosted as we come out of the pandemic. Make sure you take your learning into your own hands and show initiative. 4. Reflect on your career options If you’re ready to make the move away from where you are, make sure you’ve got a clear idea of what it is you want next before taking the leap. Tailor your CV, brush up on your knowledge and don’t be afraid to engage with a recruiter if you need guidance. 5. Learn how to present well in remote interviews Computer to computer isn’t the same as face-to-face. Get up to speed with online etiquette and make the best first impression. Read the full article here. TechBullion: 3 sectors revolutionised by AI The pandemic has accelerated many businesses uptake and implementation of AI. But which sectors have we seen reap the most reward from this fantastic technology? TechBullion explores. Insurance: Insurance firms have seen AI boost customer satisfaction like never before. Whether that’s through faster processing of claims, a reduction in fraud or improving loss prevention, AI has been making the sector smoother and more efficient. Entertainment: The likes of Netflix and Spotify have taken AI and used it to transforms how they service consumers. With many users wanting a service that provides a seamless, efficient, and relevant experience, entertainment platforms have been able to create software that can learn personal preferences and offer timely suggestions based on users evolving needs and wants. Education: The use of AI within education has become vast. From making every day learning easier through AI-based games that can be tailored to all learning types and needs to the personalisation of students’ curriculum depending on the results of past tests – the abilities are endless. To read more on this, visit TechBullion here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at firstname.lastname@example.org.
30. April 2021
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics. BBC: International Women’s Day: Illustrating the COVID-19 pandemic This incredible article from the BBC reflects on the volatility of the past year and the aftershocks all of us have suffered as a direct response to the COVID-19 pandemic. One huge issue faced by many is the sheer volume of information we are given daily around the pandemic, and how overwhelming it has become for many of us to take in. Author, Dhruti Shah, speaks to three female pioneers in the fields of science, health and technology who have been using their artistic talents to help us understand and battle coronavirus in a simple, digestible and visual way. For example: “Avesta Rastan, 25, is a visual science communicator currently living in California. At the start of the pandemic, she realised there weren't many infographics revealing how Covid-19 directly affected the human body. So, the artist, who is of Iranian and Canadian heritage, and is a member of the Association of Medical Illustrators, saw a unique opportunity to use her skills and her training in pathological illustration (the drawing of disease) to help the wider public." "I saw lots of illustrations and 3D models of the virus itself and its protein, but I didn't really see what it did to us," she explained.” To read more on this, click here. Open Access Government: How to tackle the gender gap in artificial intelligence There’s no denying that Data & Analytics is an incredibly male-dominated industry, especially across areas such as Machine Learning and AI. Reports show that 26 per cent of the Data and AI industry is made up by women, with the findings going on to say that the lack of representation in senior roles is a real ‘turn off’ for any women considering entering the industry. In this article by Open Access Government, five key areas are highlighted that must be implemented if we are to challenge and change the stereotypes in the industry currently and encourage a more equal workforce.These include: Fix the STEM gap to reduce bias in development: “With women representing a percentage of only 20-25 per cent of the sector, technological developments will be skewed,” Andrea Mandelbaum, President and CEO of Mc-Luhan says.The battle for diversity starts in education: Dr. Angela L. Walker Franklin struggled to find mentors who had the same lived experience as herself, “despite many years of talk of diversifying leadership in higher education.” It’s time to start practicing what we preach from school. Defying gender roles and expectations is key to career success: Liliana Mantilla who works as a Cognitive Delivery Manager at Amelia, an IPsoft Company, describes previous roles in which she felt she “had to work twice as hard as fellow male colleagues.” Men need to get involved in the conversation to help create change. Read more on this here. KDNuggets: 9 skills you need to become a Data Engineer KDNuggets gives some fantastic career advice to the next generation of Data Engineers, of which there is a growing number. As the industry becomes more competitive, there are 9 key areas candidates need to focus on to clinch that dream job. SQL - “Strong SQL skills allow using databases to construct data warehouses, integrating them with other tools, and analysing that data for business purposes.”NoSQL - “Examples of NoSQL include Apache River, BaseX, Ignite, Hazelcast, Coherence, and many more others. You’ll definitely get across them during your data engineer job search, so knowing how to use them would be a huge advantage.”Python - “Data engineers are expected to be fluent in Python to be able to write maintainable, reusable, and complex functions.”Amazon Web Services (AWS) - “If you’re interested in learning AWS, you might want to try online courses or Amazon’s own tutorials"Kafka - “60 percent of the Fortune 100 companies use Kafka for their applications.” For the next four key skills you must know to become a Data Engineer, read the full piece here. AdExchanger: Inside Disney’s plan to automate half its ad business within five years Disney has announced very ambitious plans to automate over half of its ad business over the next five years. As part of this plan, the animation giant has created a programmatic exchange, also known as Disney Real-Time Ad Exchange (DRAX), which will allow any potential buyers to compete for all Disney ad impressions. Lisa Valentino, Disney Ad Sales EVP of client solutions and addressable enablement said: “Automation and data is really the underpinning of the Disney Platform, that is a new way of clients doing business with us.” This need to move to a much more automated way of working comes after Disney’s multitude of partnerships which have manifested over the past few years, including Hulu, the Trade Desk and Google. Valentino continues: “We’re democratizing the client pool and allowing clients to better plan for access to Disney.” Read more on this story here. We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at email@example.com.
12. March 2021
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of data and analytics. KDNuggets: 20 core Data Science concepts for beginners The field of Data Science is one that continuously evolves. For Data Scientists, this means constantly learning and perfecting new skills, keeping up to date with crucial trends and filling knowledge gaps. However, there are a core set of concepts that all Data Scientists will need to understand throughout their career, especially at the start. From Data Wrangling to Data Imputation, Reinforcement Learning to Evaluation Metrics, KDNuggets outlines 20 of the key basics needed. A great article if you’re just starting out and want to grasp the essentials or, if you’re a bit further up the ladder and would appreciate a quick refresh. Read more here. FinExtra: 15 DevOps trends to watch in 2021 As a direct response to the COVID-19 pandemic, there is no doubt that DevOps has come on leaps and bounds in the past year alone. FinExtra hears from a wide range of specialists within the sector, all of whom give their opinion on what 2021 holds for DevOps. A few examples include: Nirav Chotai, Senior DevOps Engineer at Rakuten: “DataOps will definitely boom in 2021, and COVID might play a role in it. Due to COVID and WFH situation, consumption of digital content is skyrocket high which demands a new level of automation for self-scaling and self-healing systems to meet the growth and demand.” DevOps Architect at JFrog: “The "Sec'' part of DevSecOps will become more and more an integral part of the Software Development Lifecycle. A real security "shift left" approach will be the new norm.” CTO at International Technology Ventures: “Chaos Engineering will become an increasingly more important (and common) consideration in the DevOps planning discussions in more organizations.” Read the full article here. Towards Data Science: 3 Simple Questions to Hone Python Skills for Beginners in 2021 Python is one of the most frequently used data languages within Data Science but for a new starter in the industry, it can be incredibly daunting. Leihua Yea, a PHD researcher at the University of California in Machine Learning and Data Science knows all too well how stressful can be to learn. He says: “Once, I struggled to figure out an easy level question on Leetcode and made no progress for hours!” In this piece for Towards Data Science, Yea gives junior Data Scientists three top pieces of advice to help master the basics of Python and level-up their skills. Find out what that advice is here. ITWire: Enhancing customer experiences through better data management From the start of last year, businesses around the globe were pushed into a remote and digital way of working. This shift undoubtedly accelerated the use of the use of digital and data to keep their services as efficient and effective as possible. Derak Cowan of Cohesity, the Information Technology company, talks with ITWire about the importance of the continued use of digital transformation and data post-pandemic, even after restrictions are relaxed and we move away from this overtly virtual world. He says: “Business transformation is more than just a short-term tactic of buying software. If you want your business to thrive in the post-COVID age, it will need to place digital transformation at the heart of its business strategy and identify and overcome the roadblocks.” Read more about long-term digital transformation for your business here. We've loved seeing all the news from Data and Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at firstname.lastname@example.org.
15. January 2021
We were recently LIVE with Jonathan Ward, CEO and Co-Founder of Genome Biologics to discuss how AI, computational platforms and Data and Analytics have changed and accelerated the research and development of drugs in Biotech and Pharmaceuticals. Jonathan is a specialist in cardiovascular disease, one of the biggest killers globally. Annually, Cardiovascular Disease accounts for 17 million deaths, one-third of all deaths worldwide. His main line of work is in exploring and implementing how an integrated computational and biological approach to research and development can accelerate the creation of successful cardiovascular drugs, in a more financially and time efficient way. Genome Biologics was founded to spur the innovation that is often missing in the field of cardiovascular drugs. This unmet demand stems from the combination of expensive trials and high failure rates. However, Genome Biologics came up with a smart system, using both computational and biological systems, which allow the team to better predict failure before it happens. This amazing technology not only help increase success rates but makes the research more financially viable and a lot more attractive to potential investors. How does it all work? The team starts with the computational side. Here they screen large amounts of data which comes from a diverse range of sources, including public repositories, and the main aim of this process is to identify matches between gene expressions in heart disease or heart failure and a drug, or a mixture of drugs, that can change those gene expressions. The result of the gene therapy derives mostly from the integrated biological platform, where the team can validate the drugs used. Using real hearts, the team test the drugs screened by the computational research and see which ones improve the heart function. These drugs then go through the lengthy process of clinical trial which can take anywhere between seven to 15 years to complete. Using the technology for COVID-19 Jonathan and his team were approached early in the pandemic to see if their technology could help find a vaccine for COVID-19. Initially, the team said no due to the understanding that COVID-19 was a respiratory virus only. But as research continued and the virus was found to also affect the heart and other vital organs, Jonathan and his team looked at how they could apply their technology to identify any therapeutics. The team applied the computational system to filter out all the compounds within the coronavirus, looking at how these affected or changed the heart. The team were able to filter 5000+ compounds down to around 500 that were potentials for a repurposing approach to COVID-19. The idea was that they would be then be able to identify a drug, or a combination of drugs, that could boost the immune system and heart function to fight off the disease. In our event, Jonathan noted that, for all the vaccines being trialled and released to market over the past nine months, the computational approach has been favourable across the board from small labs to Pharma and Biotech giants, such as Pfizer. And, as we’ve seen in only the last few days, this approach has been incredibly successful as 90-year-old Margaret Keenan was one of the first people in the UK to vaccinated against COVID-19. Challenges for the industry post-pandemic COVID-19 has forced the Data and Life Science industry to evolve and adapt quickly and efficiently in order to work under pressure and find viable treatments in a much shorter timeframe than usual. The past nine months has most certainly provided learnings that the industry can take with them into any future work but, of course, the field constantly evolves, and this ever-changing nature will undoubtedly create hurdles to overcome. Genome Biologics explained that handling and managing data will be the biggest challenge for Biotech companies moving forward, simply because of the sheer scale and amount being produced. The volume of data, while important, is overshadowed by the need for high-quality data. As Jonathan points out, “If you put in junk, you get junk out” and so, the focus will very much be on getting hold of and using good data from reputable sources to ensure research and drug creation can be done efficiently and effectively. The future of data As we move forward, especially post COVID-19, there will be a lot more computational data analysis being used in the interpretation of medical information and data, which is both very advanced and exciting for the industry. However, this does mean that certain roles within the industry may become redundant, most likely pathologists. Pathologists are a large cost for many companies, as well as the hardest employees to source, making this element of research a very arduous and expensive problem. With the large uptake of computational systems, companies will be looking at creating a much cheaper and highly automated system. Not only will this reduce costs and time, but it will also greatly reduce the risks of human error in misinterpreting data. The further implementation of computational data in drug testing, means that there is a good chance human error could be eradicated from the industry in the next decade which would make a huge impact on the healthcare industry. Of course, there will always be limitations to consider. Here, no matter how good your computational platform is, you will always need the biological platform as the biological element is just as, important, if not more so, as the computational side. And so, humans will need to work together with advancements in technology to create an efficient and integrated system. Pharma, Biotech and drug discovery will never be a robot-only industry. Where should I start if I want to work in drug discovery? With decades of experience in the industry, Jonathan explains how to break into drug research, explaining that you need to have a clear understanding of the vision, mission and types of projects that are undertaken. Jonathan outlined, “Ultimately, it all depends on the kind of companies you want work for. What I can say however is that smaller Biotech companies are perfect for those who want hands-on work. These firms are more dynamic, you are likely to be involved in more projects and thrown into the deep end and ultimately learn a lot more. In big pharma, your experiences may be a little more limited across daily tasks, projects and progression.” There are a few key questions to look at as a professional already in the discipline: What can you contribute to the role that someone else can’t? What do you want to get out of the role? Working in drug discovery, research and a role that challenges a range of core issues in Life Science can be incredibly rewarding, but as Jonathan notes, “Make sure this job change is really what you want before you jump in. Like any role, do you research and get to know the role and company inside out.” Over the past nine months, Harnham has seen an increase in the number of in-demand positions across the Data Analytics and Life Science industry. With our unique understanding of this arena and excellent relationships with some of the best organisations around, whether you are a client or a candidate, we can offer bespoke solutions to suit your needs. If you’re hoping to change career or are looking for the next member of your team, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. To watch this LIVE event in full, please visit: https://www.linkedin.com/video/live/urn:li:ugcPost:6727579805614673920/
10. December 2020
The financial crisis of 2007-2008 changed banking. The world moved from taking mortgage loans in our dogs’ names to introducing strict regulations for banks prohibiting them from giving out loans to “anyone” without assessing Risk properly. In 2010 the Basel Committee on Banking Supervision (BCBS) introduced BASEL III, a regulatory framework that builds on BASEL I, and BASEL II. This framework changed how banks and financial institutions asses risk. It introduced an Advanced Internal Rate Based Approach (Commonly known as the AIRB approach). Now, the committee has introduced new changes and, by 2022, all banks and institutions will have to implement the revised IRB Framework, as well as new revised regulations for the standardised approach, CVA Framework and new frameworks for Operational Risk and Market Risk. So, what does this mean for those working Risk? Change Is Coming Change is inevitable, no matter what you do. If you work in Risk Management and Compliance, change is something you can expect to happen, often. As mentioned above, by 2022 there will be lots of changes. The Basel Committee calls this initiative the “finalised reforms”, or BASEL IV which builds on the current regulatory framework BASEL III. Quickly summarised, the changes limit the reduction in capital that effect banks IRB models. This change is predicted to impact banks in Sweden and Denmark the most, with estimations that capital ratio will fall by 2.5-3%, far higher than the 0.9% expected for the average European bank. So what does all this mean for Swedish and Danish banks? What’s Happening Now? One of the main things that Swedish and Danish banks need to revise for these new regulations, are their internal models. The new regulations introduced a new definition of Probability of Default, measured through a model commonly known as a PD model. Effectively this means that every bank must “re-develop” their internal PD Models in the IRB approach. Consequently, we are already seeing a clear response from the banks in their strategies moving forward. It has already become quite apparent that many banks are looking to make IRB model development their focus for 2019-2020 and 2021. This has resulted in a boom in the hiring space for developers with experience in IRB Modelling and Credit Risk Modelling in general, which in turn has led to high demand in the face of the low supply of these types of candidates. Understandably aware of this, modellers are now looking to negotiate higher salaries. What You Can Do For candidates that hold the right experience, there are good opportunities at hand. If so inclined, they can utilise this chance to finally see if the grass actually is greener on the other side, or not. However, there are a couple of things worth considering before making a move. Firstly, are you actually keen on switching jobs? Your skills are probably equally in demand at your current employer and, if you are having doubts about moving from the get-go, you may well be able to negotiate a rise without pursuing a new opportunity. However, if you are serious about finding something new, this is a great time to do so. The majority of banks have found that these new regulations are creating an unsustainable workload, and are now looking for talent externally to expand their teams. This means that the experienced modeller can pretty much have their pick of the litter. Furthermore, if you are a junior modeller, there are now plenty of opportunities for you to enter a niche area known for being exciting and innovative. So, wherever you are in your career, these regulatory changes are likely to have a large impact and open up new avenues for you to explore. We all know that regulations in banking and finance are now essential, we all agree, even if they can be a little frustrating. However, what people often fail to think of are the opportunities new regulatory requirements create. In the case of BASEL IV, we’re already seeing an increase in demand for strong talent, and a demand for people who are passionate about Risk Management and model development. For businesses, new regulations also provide the chance to not only improve their teams, but to create new models that can be utilised to optimise and automate. A lot of financial institutions are already aware of this and are using these models to gain competitive advantage over their competitors, as well as to stay one hundred percent compliant. If you’re looking to build out you Risk Management team or take on a new Risk opportunity for yourself, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
08. August 2019
In the world of Risk Management, top talent is always in high demand. Despite this, those who specialise in area know that progression can be difficult and, according to our 2019 Salary Survey, is the slowest in the industry. So, how can you differentiate yourself from the competition, and what steps can you take to make yourself the ideal candidate for that promotion or new job you’ve been hunting? Whether you are looking to move somewhere new, or trying to climb the ladder in your current company, here are some ways that you can make sure you stand out. Stay one step ahead in tech Traditionally, the Risk Analytics tech stack has comprised of SAS, SQL and VBA. SAS and SQL remain very much present, but we are also seeing a clear increase in the use of Open Source programming languages, such as R and Python. Unsurprisingly, a lot of Risk Modellers and Analysts are now spending their time in developing their skills in these languages. One might argue that if you know one language, there’s not too much work required to upskill in another when you take on a new role, but this isn’t necessarily true. By being proactive and evolving your skillset in your current position, your CV will have a much bigger impact when it lands on a Hiring Manager’s desk. Over the past few years, we’ve also seen the arrival of Machine Learning and AI in the world of Risk. Whilst many businesses are still slow to embrace these technologies, do not be surprised to see them make a big impact over the next couple of years. Risk Analytics are catching up to the rest of the industry in regards to technology, and having the knowledge and skillsets required in these areas before they take off will only enhance you profile. Business-driven Data In the world of Risk Analytics, it is easy to think that if you have the right programming and analytical skills in the right tools, you’ve all got all you need. You might be off to a really good start, but there’s more to it than that. It about having the balance. Yes, being data-driven and understanding complex model development is crucial to becoming a good performer in this industry but, what truly separates the good from the great, is business acumen. The ability to understand both what your analytics and models do, and how they impact the overall business is now at the top of most Hiring Manager’s lists. A person with good quantitative skills will always see something that can be improved, but they also need to know when to stop and be happy with the result. The key to getting this right lies in their understanding of the business and the ability to answer questions like “If I sit and work on this for 8 more hours, will the real-world difference be worth that amount of time and resource?”. By viewing things through the prism of cost vs reward, and understanding that balance, you can demonstrate that your value to a business goes beyond your analytical skills. React, adapt and attract In this world there are a few things we can take for a certainty; the sky is blue, it will rain on your day off, and there will always be new regulations for financial institutions. Because of the certainty of change, a key thing employers look for in candidates is the ability to react quickly and make changes as soon as they are needed. Fast growing companies such as Klarna, tink and iZettle may seem like fairy-tale success stories, but the real edge they have is their adaptability and agile culture. Whereas some traditional corporations and banks have lengthy and complicated processes required before they adapt to new regulations, these new companies embrace their agility and get things done. The ability to be agile and adaptable is, therefore, something that a lot of businesses are starting to realise is key. Therefore, if you’re looking to get ahead, you should try to evolve these qualities in your working ways. If you are looking for something new, look to prove you are driven and do not fear change. If you can demonstrate that you are able to work with a business-oriented mindset and embrace change, you’ll stand out as a key player in your team. Specialist vs Generalist With the world of Risk Management offering a number of opportunities to become very specialised in very niche areas, it’s worth considering whether this approach is right for you. There are some definite pros, for example, if you are the best developer of PD models for non-retail, you will be highly sought after for roles in this area. Plus, high demand, and a shortage of skillsets means that you will be in a good position to seek a high salary and lots of benefits. However, this does mean that you are likely to only have the opportunity to work in this area for the foreseeable future and, for some, this can become repetitive and not provide enough of a challenge. Additionally, if you were ever were to apply to work in a new area because of this, you would likely find yourself overpriced and needing to take a step down in seniority. The alternative, therefore, is to become more of a generalist, with a broader, but less advanced skillset. Think being able to play every instrument, but only knowing one song. There are definitely some clear benefits with this approach, not least the ability to work on a diverse set of projects, gain an excellent understanding of how Risk Management affects a business on every level, and be able to slot into a number of roles easily. You will also gain a better idea of which areas of Risk that you like, and which parts you dislike. Whilst many analysts begin as generalists before looking to specialise when they get promoted, they often find that their knowledge will not be as deep as their specialist counterparts. Therefore, it is likely they will have to take a step-down or make a sideways move before they can achieve that promotion. There is no right or wrong when it comes to the specialist vs generalist argument. However, for those looking for faster progression early-on, a generalist approach may be better suited despite the fact that you may need to change approach before reaching the most senior levels. Whilst demand will always be high for the best candidates, competition for promotions and senior roles in Risk Analytics remains fierce. Therefore, by proactively thinking about the ways that you work, how effective you are, your business focus, and what your ambitions are, you should be able to get the most out of your career. If you’re looking to get ahead in Risk Analytics, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.
26. June 2019
Instant transfers, real-time payments, virtual banks, and digital currencies - these are just a few of the ways fintech innovation has been booming in the last few years. Around the globe, start-ups, upstarts, and non-bank payment providers have shaken up the banking status quo. New technologies, market conditions, and alternative business models fueled by global investment offer much needed change in payment systems as well as complement others already on the market. Demand for optimised payments experience in terms of speed, convenience, and multi-channel accessibility are the new ways to pay. How to pay- let me count the ways Retail and traditional banking have moved away from slow batched processing as consumer demand drives real-time payment systems. This demand has Consumers in retail banking also benefitting from the development of payment systems that run in real-time rather than via the traditional (and relatively slow) method of batched processing. This demand has in turn furthered innovation in real-time payment infrastructures. Consumers no longer require a bank or credit card to make payments, but can instead use service layers that run on top of existing real-time payment infrastructures. In our mobile world, mobile wallets are often at the forefront of thought for payment systems and with the rise of P2P payment such as Venmo, Square, and Klarna. While generally focused on the peer-to-peer (P2P), mobile capabilities are much smaller in the wholesale and corporate sectors. But, this won’t last for long. Projected smartphone growth offers banks an opportunity to adapt and consider solutions across devices to meet growing demand. An increasing number of non-bank providers are entering the payments world as well. Consider the rise of digital currencies, foreign exchange and remittances, and other P2P models which enable users to buy and sell currencies directly at an agreed rate. Real-time technological innovation reduces currency risk faced by banks and money transfer agencies, while also lowering costs associated with money transfer. Growth in e-commerce makes consumer and retail payments sector the fastest moving in terms of innovation and adoption of new payment capabilities. Renewed confidence in the financial services sector has led to a substantial rise in available jobs, particularly among risk management teams. Yet, professionals to fill these roles remain in short supply. Roll out the red carpet- these are the roles in high demand Against the U.S., Japan, and globally, the U.K. faces a skills shortage in risk functions. According to a report by Accenture, over 75 percent of organisations say a shortage of core risk management talent impedes their effectiveness. Just over 70 percent are facing a shortage in new and emerging technologies. With an eye to the future, many organisations, capital markets, and U.K. banking plan to strengthen their understanding of emerging technology risk and their data management capabilities. Roles in highest demand are those in counterparty credit risk, particularly within pricing. While more recently, graduates with quantitative backgrounds found roles in risk methodology, real-time payment structures and the role of e-commerce has created more opportunity for those who candidates who understand pricing models. Those at the first line of defence in regard to assurance, internal audit, IT controls, and cyber security fall within the scope of operational risk functions are also in demand. The role of Brexit programmes will drive risk change hires in 2018. As negotiations become clearer, other organisations are expected to follow an investment bank in Canary Wharf which has made credit risk function hires a top priority. Top challenges in risk management function Increased demand from regulators, increased velocity, volume of data, legacy technologies, and variety are the top challenges faced by U.K. banking and capital markets. To meet their needs, these organisations are focused on creating teams which blend core competencies, a deep understand of new digital capabilities, and commercial acumen. Quantitative risk professionals with experience in counterparty and market risk analysis are in high demand as well as those with a pricing model focus. Demand for regulatory and portfolio level market risk managers have also seen an uptick in demand. In order to overcome shortages, businesses are considering internal candidate pools and moving strong candidates between asset classes. Despite shortages of professionals with key skill sets within risk, employers have remained cautious. Quantitative risk roles are a notable exception, where skills shortages are most acute. We have an opportunity for a Senior Credit Risk Manager within New Product Leadership to help build a leading Financial Service’s recently purchased Consumer Finance Portfolio. Shape the entire strategy, oversee all Scorecard and Model Development, and build your own team. Interested? For additional opportunities check out our current vacancies. Contact our UK Team at 0208 408 6070 or email email@example.com to learn more.
11. January 2018
By 1 January 2018, the International Accounting Standards Board will have introduced IFRS 9 as a mandatory measurement model for financial assets. Due to this, I thought I would break down what this means for business and how it will impact recruitment trends over the next one to two years. What is IFRS 9? IFRS 9 is an International Financial Reporting Standard which is responsible for the accounting of financial instruments. It includes requirements for recognition and measurement, impairment, derecognition and general hedge accounting. Since July 2009, IFRS 9 has been implemented in various stages whereby the IASB has been adding to the standard as each stage has been completed. What were the downfalls of IAS 39? IAS 39 was first implemented by the IASB in 1984 and its predominant aim was to ensure there were rules for the reporting of the financial instruments ensuring that companies would then present them in a way which was consistent, but also transparent. However, following a G20 summit in 2009 after the financial crisis of 2008, it was decided that IAS 39 needed to be changed due to the fact there were too many exceptions and inconsistencies and the project to replace it went ahead imminently. IAS 39 was often considered to be very backward looking, meaning that it failed to give a true and fair view the financial position of a business. Perhaps more crucially was its inability to respond fast enough to the recognition of credit losses, which was evident in the financial crisis of 2008. IFRS 9 at a glance The main difference between IAS 39 and IFRS 9 is that instead of loan provisioning using an incurred loss model, they will be using an expected loss model. Despite the Financial Account Standards Board (USA) using a single measurement model, the IASB decided that a three-stage model would be more appropriate. Stage 1 will include financial instruments which have had no noticeable increase in Credit Risk since their initial recognition or that have low credit risk. Stage 2 will include financial instruments which have had a noticeable increase in Credit Risk since recognition, however, does not have evidence which suggests that they have been impaired. Stage 3 will include any financial instruments which have had a noticeable increase in Credit Risk since recognition and have evidence that they are impaired. In the table below I have compared IFRS 9 in its three stages to how things would look if IAS 39 used the same technique. Will IFRS 9 eliminate the possibility of a repeat of 2008? In my opinion, the simple answer is no. Evidence, without a doubt, suggests that under excess financial pressure, banks should be able to withstand it without any major implications. However, despite this, I am not convinced that any reporting standard put in place would be able to prevent another crash. Nonetheless, it is important that all financial institutions become compliant by the impending 1 January 2018 deadline, meaning financial reporting managers who can work on the implementation of IFRS 9 are now in high demand. Due to the significant impact of this change, we know that those candidates with strong ACA, CIMA and ACCA backgrounds, who can efficiently manage key programmes, will shape how well the implementation of IFRS 9 takes place for a company over the next two years. Are you such a candidate and what is your experience of the changes that are taking place? Will these new Standards be robust enough to protect institutions and the public? As a business, are you ready or on track to have these Standards fully implemented in time for the 2018 deadline? If, from a recruitment perspective you need more advice or insight surrounding how we can help you get your company IFRS 9 ready, get in touch with me - T: (020) 8408 6070 E: firstname.lastname@example.org
11. May 2016
KPMG, the global accountant and consultant has announced the formation of KPMG Capital, which will invest in big data and data analytics companies in Europe and beyond. Headquarterd in London, KPMG Capital says it will primarily invest in big data and analytics businesses through strategic acquisitions and technology partnerships. A growing fund The initial value of the fund is believed to be worth $100 million (£66 million), and when required the KPMG Capital fund will be topped up with cash from its parent company. Click here for the article on the web.
11. November 2013