Recruitment Readiness: Fund and Asset Managers Expanding their Footprint with Intelligent Data

There is no shortage of articles published relating to AI and Big Data and much of that is predicated on the idea that AI will replace the jobs of many professionals (recruiters seem to have a target on their back here too).  It does seem a fully viable and end to end AI solution is far away.  Fund and asset managers are however looking to ways that intelligent use of Data and Analytics can add value to the business, empowering firms to better deploy their resources.

Applications of data and decision science has been a feature of many fund and asset managers for building quantitative investment and risk models and the scope of its application is now changing beyond these departments.  A growing number of firms have sought to invest in their data teams, working to enhance the capability of distribution teams by applying data science and advanced analytics to their distribution models.  This has seen organizations shift to a more targeted engagement model for working with clients and coordinating sales visits.  This has freed up much of the sales force to engage with higher priority and often more profitable opportunities.

Implementing Data

After seeing real results from implementing data driven changes, demand for data skilled talent is growing along with its adoption.  To roll out any such changes, companies need to review and enhance their Data Architecture, Data Governance and Data Quality Management processes.  The last 12 months has seen considerable growth in opportunities and wages for Data Architects, Data Scientists, Data Engineers, Data Governance Managers as well as project services candidates with strong data migration and management backgrounds.

Beyond the distribution teams, data is being used to make enhancements to middle and back office operations, allowing some of our clients to reduce costs through the increased process automation, better administration efficiency and automated systems for monitoring of crime and trade surveillance.  Accessing data and information has elevated in importance, as many legacy products do not provide the required capability to do advanced modelling.

Migration to new systems such as BlackRock’s Aladdin platform or SimCorp Dimension has been a feature over the last 12 months, with a number of other firms looking to make the transition over the next due to the better access to data and information. For a clearer indication on how we see the market salaries for Data skills, Data Science, Business Analysts, please contact

Market salaries

Overall, the market is offering rates for candidates with certain skills in systems or product knowledge.  Programs such as the CHESS Replacement program have attracted many Project Services BA’s and PM’s with knowledge of the equities trade life cycle.  Systems migrations to Aladdin or Dimension have provided attractive rates for BA’s and PM’s with legacy or incumbent platform knowledge.

Beyond this area we are also seeing investment going into Data Product Creation, with firms looking to make the most of incoming data or historical data.  Organizations with large amounts of unpublished data such as Stock Exchanges are rolling out data platforms known as a “Data Sandbox” allowing organizations to capture value in big data, and providing the opportunities for other organizations to run proprietary data into platforms to gather further insights.

All things considered, Fund and Asset Managers are ready to embark on the next stage of their journeys, with Data Driven changes enabling firms to realise efficiencies, savings and growing revenue, demand for data driven talent with knowledge of the buy side industry still valuable, however, relevant market knowledge may not be as mandatory to some other areas of the business such as sales, marketing and distribution.

For more information on current market and trends, please reach out to or follow Shane on LinkedIn at

3 strategies Investment and Funds Management firms should adopt in 2020:

As an Australian Investment or Funds Management firm, you will know that the market is tough, competition is rife and commissions are getting squeezed. So how do you differentiate yourselves against your competition?

As one of the leading Fintech recruitment firms in Australia, we have seen what our clients have and have not been doing, relative to their competitors. So let us break down the 3 strategies we think you should adopt for 2020.


What Technologies are you currently using and are they fit for purpose in this vastly changing technology landscape? What Systems and tech stacks are you looking at? What is the market demand and supply for such skills and technologies and also what are the costs for on-prem vs SaaS or DaaS solutions for investment managers?

We are seeing a huge demand for Data Analytics professionals with Tableau, PowerBI or Alteryx to get raw data and provide insights across various demographics and market shifts.

Market demand is vastly growing for Machine Learning/AI and Data Science tools across the investment management industry. These skills are brought in-house to help portfolio managers and traders make better and more educated decisions through the use of text mining and social media scraping to validate and substantiate findings and insights.

There is also an increased demand within our buy-side clients for Data and Quant Programmers/Analyst Programmers who are experienced with R, Python and Matlab but who also have an accounting or an applied finance degree.

In terms of systems, are you still running Excel/VBA Spreadsheets? There are many diverse platforms on the market which can help you scale through the use of investment systems. These could be Charles River, Blackrock Aladdin, MarkitEDM / Cadis, Thinkfolio, SimCorp Dimension and are you utilising it for Front, Middle or Back Office functionality or all 3? Some of these systems can be quite costly and selecting the best one for your company, 5-10yrs from now rather than at this present time, is vastly important and I’ll summarise why;

In the financial services sector, Australia has slowly moved away from heavy sell-side activity and there is less happening locally with investment banks compared to 10 years ago. I remember being inundated with technology jobs for major global banks such as Credit Suisse, Deutsche Bank and Merrill Lynch, but less so since 2012.

If anything, many of the large global investment banks are streamlining their Australian operations and moving them to regional hubs such as Singapore or Hong Kong or back to head office in Europe or the States. Australia is increasingly becoming more tailored towards our traditional buy-side safe havens being Superannuation, Wealth, Annuities, Funds, Investments and Custodian businesses.

This brings about an increase in large technology transformations, M&A and divestment activity which we are working on for our clients and which will continue. Thus, to be positioned well for such programs for your potential clients, ensure you have systems fit for purpose long term.

2.You need to adopt a core SAR Strategy

I’m not talking about your Stop and Reverse Trading strategies, actually something vastly different. I am referring to:

Selection – what are all the Omnichannels available for you to engage with possible candidates to join your organisation? How have you selected your go-to-market strategy for this? Which recruitment firms are you partnering with? What channels are you missing out on?
Attraction – Do you have a reputable brand in the market? Is there a positive word of mouth out in the market surrounding your brand? Are you using the right recruitment firms who a) understand your market and b) are well placed to attract the right candidates into your recruitment funnel to open up meaningful discussions? Then once you have the candidates, how are you going to attract them to your organisation rather than a competitors during the interview process?
Retain – Now you have a great hire in place, what are you doing to keep them happy and challenged within your organisation? What new technologies are you adopting? What makes them want to stay in your firm rather than popping their heads up to see what else is out there?

3.Do what is right for your company

Yes it is important to have a handle on what systems your competitors are using but make sure you are selecting the right systems, technology and hiring the right personnel which are fit for your business and not just because your competitors are doing so. If you do that you will be following the path which the industry takes and not setting the course for the industry’s future.

As a niche Fintech recruitment firm, we have been helping numerous Funds, Asset and Investment firms across Australia with all levels of tech hires. We can help you select and attract top talent and look at avenues or retaining those hires.

If you’d like to find out more reach out to us, we are more than willing to assist where we can at

I hope this has been useful.

Sean Turner – Founder and Director, Kapital Consulting

Recruitment . Made . Simple

Recruitment Ready: A snapshot of the forces driving demand for data talent

Technology is becoming a mandatory feature of regulation and changes, that is to say that data is empowering organizations to make better decisions, and at the same time it is being regulated and protected. While the use of Data is said to be one of the key drivers of an organisation’s success, using data incorrectly is not only expensive in opportunity costs, but also in potential fines for regulators when breaches are discovered.  It is mandatory that firms meet regulatory requirements and respond to changes. The effective use of data can empower an organisation to properly monitor, detect and respond to potential risk.  We’ve seen this impacting the wider technology recruitment market.

There has never been a better time for organisations to deploy technology and data to solve regulatory challenges.  Intelligent use of data is being deployed in many ways across organisations to garner results, with artificial intelligence, machine learning and data science a critical feature of many organizations decision process.  Data driven solutions are having a profound impact on how an organisation monitor activity, detect breaches and manage potential crime and regulatory risk to avoid loss and costly fines.  Not only can data assist in avoiding such costs, it can also make processes more efficient to better prioritise innovation and prioritise more transparency.  

Data Scientists are an integral piece to insurers, consulting firms and banks, with roles of actuaries, data analysts, pricing analysts and risk analyst changing.  As data savvy talent are providing more and more value to the organization where they ply their trade, it is understandable that the cost of attracting such talent is increasing.  For example, the cost of demanding the best Data Scientists to gleam new insights for a business is not only in the form of salary, it comes also in the form of benefits provided by the firm.  

The real cost comes in organisations having appropriate strategies to ensure that the data is captured, structured and shared appropriately.  A data transformation can require substantial investment in new systems, processes and implementation.  Changes to Data Governance, Data Pipelines, Data Quality and Master Data Management necessitate data focused Architects, Project Managers, Engineers and Business Analysts.  

Regulatory changes such as the General Data Protection Regulation (GDPR), codifying guidelines on data and its protection is a European Union initiative however the globalisation of the economy means that it is being adopted by any organisation who may interact with EU citizens.  Similarly, global accounting standards such as IFRS17, specific to insurers is being adopted by major firms globally, impacting insurance contracts and their underlying revenue, with a deadline set for early 2021.  

The impact of global initiatives and changes increases short-term (1 -3 years) demand of the Technology Staff with strong understanding of Data and experience in regulatory change, such as GDPR or IFRS17.  There is a further premium for those with such experience as well as strong business stakeholder skills to engage with business, compliance and marketing functions.  Currently, many of these SME’s are employed by the Top 4 consulting firms.  The positions below represent some of the placements we are seeing here at Kapital (for further information on salaries, bonuses and day rates for the below, please contact

Head of Data

Data Analytics Lead

Data Scientist

Data Architect

Data Engineer

Salary ranges can vary vastly due to the dependent on the specialised knowledge and skills of candidates.  Those with strong technology skills and the ability to engage with business functions effectively are proving to be the most in demand due to the additional value they provide.  Business acumen, influence and emotional intelligence to navigate complex change associated with such projects as data transformation and or regulation changers is a mandatory feature to the success of any change.  The consequence of this is that the overall cost is often greater for organisations seeking talent with such attributes.  Retention of such talent will also be a key feature of any organisation in the current market.  

As the use of data is such a powerful magnifier for all organisations, data talent, unlike many of the other areas of technology before are industry agnostic.  The result of this is that banks, consulting firms, insurers and fund managers are competing with the likes of Google or Atlassian to bring on the best talent.  The demand for data skills will likely continue to grow, so how organisations work with their best data talent to provide value to them will be a key feature.  

For more information on current market and trends, please reach out to or follow Shane on LinkedIn at

How Artificial Intelligence (AI) and Machine Learning (ML) is affecting the recruitment industry

Hey guys,

In this newsletter we’re going to discuss the ways Artificial Intelligence (AI) and Machine Learning (ML) are affecting the recruitment industry as well as how they affect client-side talent acquisition teams. Although AI and ML have brought lots of positive changes, it’s always a good idea to examine the possible downsides too. Examining both sides of the argument is the best way to prepare for the changes AI and ML could bring.

How Artificial Intelligence (AI) and Machine Learning (ML) are changing the recruitment industry

Both AI and ML are excellent for automating processes. There’s no denying that recruitment can feel a little time-consuming, especially when we’re in the earlier phases of sifting out unsuitable candidates. When AI and ML work to automate correctly, they give recruitment teams extra time to spend on the more important aspects of the hiring process.

Now, although all this automation is excellent in terms of efficiency, there are a few shortfalls. In order for AI and ML to automate successfully, they need to mimic the behaviours of those who would usually eliminate unsuitable candidates during the early phases of recruitment. AI and ML are technologies which have algorithms who’s sole purpose is to “learn” behavioural patterns, predict outcomes and relies heavily on the person imputing the data to ascertain what is good and reliable for its use. That person is likely to focus on what has worked well for the company in the past and if the company is trying to change their hiring process and aim to unearth niche talent pools of candidates with innovative, entrepreneurial ideas and new ways of thinking, then how would this work? As these platforms are based on historical search patterns and learned behaviour, once those behaviours are in place for the AI software to use, they’re hard to alter even when a company needs to change its approach to hiring.

AI and ML could potentially exclude highly-qualified candidates

Let’s say the behaviours inputted into autobots that exclude candidates and don’t look beyond basic flaws for human explanations. One example of this is excluding candidates with gaps in their CV’s. Unfortunately, this could result in the exclusion of highly-qualified, career rich and excellent candidates who’ve taken career breaks for secondments or parents returning to the workplace who have years of experience behind them.

The autobots filtering candidates are only as good as the person programming behaviour criteria

It’s always worth remembering that the autobots that filter candidates during a recruitment process are dependent on human programming. As such, if the person inputting behaviours isn’t overly familiar with the industry they’re representing, they could accidentally encourage inappropriate candidates through the recruitment process.

For example, in the tech world there are significant differences between a Python, Javascript front end developer, a Python Automation Programmer and a Software Engineer with basic Python. If the human providing the autobots with search patterns and behaviours doesn’t recognise this, AI and ML then becomes burdensome in the recruitment processes rather than efficient.

One of our best hires to date was a 24 year old with a long standing financial services client  of ours in Sydney. His profile was a mix of Cisco Networking, .Net Development, Text Mining, Social Scraping and some Python within DevOps. I can almost guarantee that he would not have shown up through the use of AI and ML for a Data Analysis SME (Subject Matter Expert) within a trading environment and this is where the inquisitiveness of the human mind over a machine prompted our team to meet him and 3 years later he is still one of their best hires.  

However, we can use AI and ML, we just need to use them wisely

At Kapital, we believe that there is a place in recruitment for AI and ML. However, we’re also of the mindset that we need to test software cautiously and provide the right level of human input to ensure it’s successful. This usually means finding software programs that are culturally appropriate and right for each unique recruitment process.

As an IT recruitment agency, we take a forward-thinking approach that uses software and human skills. Our consultants cover multiple technical disciplines for individual clients across industries creating “one touch points” for our clients and HR/Talent Teams, which means you can avoid the costly mistakes that come with poorly implemented AI recruitment processes.

Remember to follow our company page here and you can view our other newsletters here.

Till next time from The Kapital Team – Recruitment Made Simple