Financial Crime Modelling & Analytics Manager
London / £55000 - £75000
INFO
£55000 - £75000
LOCATION
London
Permanent
Financial Crime Modelling & Analytics Manager
London
£55,000 - £75,000 + car, bonus, benefits
A second line of defence role with own and development modelling and analytics capabilities for a large international bank's financial crime division.
THE COMPANY
A leading name across the retail and corporate banking space, this company are changing the way anti-financial crime is monitored. With a high calibre modelling and data analytics team across first and second line of defence, this role allows you to own your business area and make an impact. The company are people-first, leveraging their employees strengths and providing a high level of flexible working and investment in them in return.
THE ROLE
- Develop and maintain advanced models and analytics for financial crime, including AML, Sanctions, List Management
- Support the compliance function with strong data management skills coupled with excellent domain knowledge
- Translate regulatory changes and policies into actionable rules and threshold tuning
- Analyse and mitigate potential risks across the bank
YOUR SKILLS & EXPERIENCE
- Advanced SQL skills for data manipulation, transformation of raw data files, and scripting
- Python or R experience would be advantageous
- Strong financial crime knowledge across various typologies (AML, Sanctions, Transaction Monitoring, Anti-Bribery & Corruption
- Proven experience identifying and managing risk, putting in place necessary controls and processes
BENEFITS
£55,000 - £75,000 depending on experience
Car allowance
Bonus
Healthcare
Generous pension scheme
Retailer discounts
HOW TO APPLY
Please register your interest by sending your CV to Rosalind Madge via the Apply link on this page
CONTACT
Rosalind Madge
Client Relationship Manager
SIMILAR
JOB RESULTS
How Fraud Analytics Can Keep Your Money Safe
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How Fraud Analytics Can Keep Your Money Safe
We’ve previously written about how data analytics can help save your business money, but what about protecting the funds and resources your company already has?
It is widely reported that cyberattacks are rising as are incidences of fraud. Indeed, a 2020 PwC study found that 47 per cent of businesses had at least one incidence of fraud in the past two years, with an average of six instances per company. The losses from these incidents for the 5,000+ businesses surveyed amounted to $42 billion – approximately $8.4 million per company.
As consumer costs rise and businesses find their budgets stretched more than ever, losing any funds through fraud has become all the more damaging. Because of this, leaders need to pull out every stop to prevent it. Here’s how fraud analytics can help.
What is Fraud Analytics?
Companies have been using anomaly detection and rules-based methods to combat fraud for decades. While these methods are effective, they have their limitations.
This is because rules-based tools only detect abnormalities based on explicit, pre-written rules, whereas advanced analytics uses a company’s existing data to spot patterns, learn trends, and eventually detect outliers on its own through the use of artificial intelligence, machine learning, and predictive analytics.
These advanced analytics tools can be used to automate and speed up some of the labour-intensive work, which reduces operational costs and leaves others free to concentrate on the arguably more powerful, preventative activity.
One sector that’s been heavily leveraging fraud analytics is finance. Traditionally, such organisations have relied heavily on manual, human intervention in the regulatory reporting process. However, with large swathes of data moving in and out of systems, the capabilities for humans to keep up are simply untenable.
How is Fraud Analytics Useful?
Financial data can be scrutinised in numerous ways to identify anomalies in patterns of consumer and/or employee behaviour that might indicate financial wrongdoing–both internal and external.
For example:
- Ledger entries can be scrutinised for potential fraud or errors, using data analytics to identify suspicious entries.
- Expenses in areas such as travel are often where unscrupulous employees could fudge numbers. This could be tackled by monitoring department spending over time to understand the average range for each division, and setting up an alert triggered if the department deviates from that range.
- Contractor payments are common areas for fraudulent behaviour. Vendors may submit the same invoice multiple times, either by accident or to follow up on unpaid bills. You may pay the same invoice twice if you don’t have a system for tracking and flagging duplicates.
Financial data analytics can also be applied to a range of companywide performance indicators, such as monitoring company goals and objectives, building dynamic profit and loss statements, or streamlining budgeting and forecasting.
By evaluating historical data alongside forward-looking financial statements, analytic techniques can help to form an evolving forecast, which gives finance teams a greater understanding of the current and future financial health of the business. And, unlike the static reports used for accounting, data analytics offers dynamic analysis, allowing the user to ‘ask’ the data questions.
Humans Versus Machines
Despite strides in technological development, human intervention remains paramount in data analytics practices. While analytics techniques offer a fool-proof way of identifying issues, humans are needed to provide vital context, investigate suspicious activity and give it business relevance.
There will always be a high number of anomalies from the data analytics process, but very few will transpire to be errors and even fewer fraudulent transactions. Data professionals with an understanding of the business can use their judgment and intuition to weed out irrelevant information, explain most anomalies that appear, and further investigate those that warrant extra attention.
Interested in using your skills to help businesses to remain secure against fraud? The world of fraud data analytics is a fast-paced industry full of opportunities across countless sectors – check out our roles today.
How Advanced Analytics and Customer Engagement Create Insight for Your Business | Harnham US Recruitment post
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Have you ever wondered why your favorite store stopped carrying an item you liked to purchase? Or how you discovered a new item to fit the bill for what you were searching for? Consider counterintuitive holidays where the stores are packed, but the checkout lanes are light with few cashiers. On the flip side, there may be opportunities in stores that have ensured they have plenty of product in stock, have extra staff to help, and through it all have managed to make the experience seamless.This last imagining is what happens when you bring Advanced Analytics into your business to gather insights and create customer engagement for people who will return again and again to your store and to buy your product. This isn’t just for brick-and-mortar stores, this includes digital and e-commerce businesses as well. But the big question here is, how did they know to hire extra staff, make sure there was enough product on hand, and not only retained former customers, but made new customers? The motto ‘know your customers’ holds true, even in, and especially in, today’s world of social media marketing, e-commerce shops, review opportunities, and more. Enter Advanced Analytics. The next step up from the Analytics of Business Intelligence to offer you and your business a birds-eye view of what your customers want, how they want it, and how you can ensure their experience keeps them returning, and opening doors to new customers as well. TRADITIONAL BUSINESS INTELLIGENCE (BI) VS ADVANCED ANALYTICS Business Intelligence gives historical performance Data. What have customers bought or thought in the past. This information has been used to inform how to improve processes now, for the next sale, call, or booking. Advanced Analytics, however, offers not only a system in which to capture historical Data, but can work with more complicated systems, and handle the massive amounts of Data businesses capture every day. Think of Advanced Analytics as the change agent who comes in to solve the more complicated issues. While it may still gather the same information, it will use the information to determine why something is working, and if something isn’t working, what is the root cause of the problem. If customers are returning again and again, what is bringing them back, and how can they repeat it and improve it for the future. Below are three types of analytics each with its own specialty to help you make more informed decisions to move your business forward. 4 BUSINESS OPERATIONS ADVANCED ANALYTICS SHINESGaining clear insights about your business involves more than just the experiences of your customers. The driving force behind happy customers are the operations of your business. From the supply chain to marketing to Human Resources, every department plays a role in the Customer Experience. So, what better way to use Advanced Analytics than to ensure the root of your business is running well which will be key to ensuring that smooth customer experience. · SUPPLY CHAIN ANALYTICS – Market demand is at an all-time high and supply is…well, it’s stuck a bit. But regardless of what’s being moved, where, and how, the remote workforce, globalization, and necessary manufacturing plants to handle the loads are making things more complicated than ever before. Advanced Analytics can help businesses plan for what will be in demand not only using past performance indicators, but also predictive modelling scenarios to try to meet the pain points of supply and logistics.· OPERATIONAL ANALYTICS – Changing market demands, adaptable processes, and flexibility in how operations are executed are all signs Advanced Analytics ha a place at the very heart of your organization. In this scenario, bits of seemingly unconnected Data come together to help imagine process alignment with market demand, and craft better insights for business.· RISK ANALYSIS – Cloud-based tools available to help identify management of massive amounts of Data with predictive insights using Advanced Analytics.· HUMAN RESOURCE ANALYTICS – To find and retain top talent, it’s important to ensure your business knows what they need, why they need it, and who can meet their requirements. Advanced Analytics can offer HR the chance to predict and evaluate how a prospective employee may do in your organization. Ready to take the next step in getting a birds-eye view of your business? Consider Advanced Analytics. Imagine knowing not only the historical Data which has kept your business moving forward, but using the near real-time Data streams from omnichannel sources to help you plan for the future of your business with future-predictive insights. If you’re interested in Digital Analytics roles, a career in Advanced Analytics, Machine Learning or Robotics just to name a few, Harnham may have a role for you. Contact one of our expert consultants to learn more. For our West Coast Team, contact us at (415) 614 – 4999 or send an email to sanfraninfo@harnham.com. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.
Is Product Analytics the new Digital Analytics? | Harnham Recruitment post
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Following on from our exploration of what Digital Analytics is, and the exploration specifically of hiring Digital Insights Analysts in the North of England and Midlands, we wanted to take a look at Product Analytics, and how it differs from the standard Digital Analyst role.To help investigate the importance of Product Analytics in the current market, we have interviewed Nicky Tran, a Product Analyst at Virgin Media (Manchester).What Is A Product Analyst?In simple terms, a Product Analyst ‘’looks at the different products a company has, and then you are identifying which areas of the product can be improved or which areas can be optimised.” While Digital Analytics can inform the product lifecycle, the interesting aspect to this role is, that unlike a traditional Web Analyst role, it is more of a hybrid role. Nicky emphasised that it is ‘’an upcoming sector within the analytics community’’, providing an overlap between Digital Analytics, Customer Analytics and Data Science.The key skills and tools for this role are advanced SQL, Google Analytics, and AB testing. So how does this skillset differ from a traditional Web Analyst? Nicky suggests that while the core requirements are that of a Web Analyst, with a web role you would essentially just be using Google Analytics Data. However, as a Product Analyst, you would be using advanced SQL to access other data bases, and pull data from models, and therefore, “you are combining two sets of data to get a more insightful look”.Why Is Product Analytics Important, And Why Are They Now Becoming More Prominent On The Market?Similar to Digital Analytics roles, it is clear that with the impending digital transformation, companies are becoming increasingly data-led, especially with regards to their digital platforms (and products).As a result of the pandemic, the digital space is so much more important than ever before. Therefore, to stay competitive, and to really understand the products from the consumer perspective, companies have to provide the most personalised customer experiences to acquire and retain their consumers. As Nicky mentions, ‘It is definitely worth making an ‘inventory’ to see how to promote what you have – it is about personalising the customer journey’.What are employers looking for in a Product Analytics candidate?Product Analytics are great due to their hybridity. In the current market, where there are numerous jobs, and few candidates, a Product Analyst (technically strong in three areas) is a highly sought-after rarity.Businesses are becoming increasingly invested in Product Analytics and having a Product team that works alongside the Digital team can be beneficial; especially when companies need to stay competitive.What are Candidates looking for? Understanding the differences between a Digital Analyst, and a Product Analyst is key to understanding what a candidate is looking for. Nicky suggested that this Product Analyst role enabled her to be the ‘bridge’ between areas.So how does the future of a Product Analyst differ to that of the route of a Digital Analyst? For Nicky, this is one of the most important factors to being a Digital Analyst, as she has the option to go down the Data Science route in the future should she wish. The more technical skills she has as a Product Analyst means she is building up experience across different areas of Data & Analytics, giving her a slightly different career path, should she want to go down a more technical route.Why Choose A Product Analyst Role?“If you come from a technical background – maths, physics, computer science – and are interested in how the numbers are crunching, it is worth going into Product Analytics, as it needs a logical mathematics brain, to be able to convert it into a way which is useful to stakeholders.”From speaking to Nicky, it is clear that Product Analytics is an up-and-coming role that people don’t know enough about it. Therefore, if you are curious about Product Analytics, or any of the different roles the market has to offer at the moment, as an employer looking for help hiring, or a candidate actively or passively looking for work, Harnham can help. Take a look at our latest Product Analytics jobs, or get in touch for more information on how we can support your hiring needs.
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