The Know-How Equation for Accelerating Customer-Centric Investment Banking

2nd June 2021: The unprecedented public health, economic, and societal impacts of the Coronavirus pandemic have intensified the challenges facing the investment banking industry – falling equity prices, reduced liquidity, new regulations, shareholder demands, market democratisation, increased client sophistication, remote working, and rapid technology advances.  These forces have combined to accelerate the need for greater efficiency, collaboration and customer-centricity.

Investment banks, like all other financial service providers, hold an information advantage – but all too often they fail to properly leverage this advantage, and turn it into commercially-valuable intellectual property (IP).  Advances in technology – data science, artificial intelligence, machine learning – provide an opportunity to unlock the value of this customer IP to optimise:

  • Sales
  • Onboarding (KYC and AML)
  • Trading
  • Operational efficiency and cost reduction
  • Risk Management, regulatory compliance and customer monitoring

Leverage internal data (or ‘Know-How’ as we like to call it) in combination with external structured and unstructured data, and the opportunity to optimise performance and add value through differentiated intelligence and insight gets really interesting.


If you’re in sales in an investment bank, then just like traders, you work in a high pressure environment.  You know that clients will only deal with you if you demonstrate technical knowledge, context and reliability.  We may be living in the self-service era, but in the investment banking world, clients still value high-quality advice and insight.

In a 2019 report by PWC on the future of investment banking sales, they comment that banks and sales people providing information, insight and advice “will generate better value from it”, and that “ideas and insight positively influence flow sales”.

The advantage gap between sales people that do and do not deliver data-driven insight and advice has only grown during the pandemic.  Stronger understanding of trends, market activity and client needs in a challenging revenue pool can help banks win and retain client relationships, unlock previously untapped opportunities, and grow market share.

Investment banks must seek to optimise their sales function by taking their know-how (customer and market experience and expertise) and harness data science to offer a smarter, more refined service.  Helping their salespeople do what they do best, but do it at scale – marshalling, comprehending and interrogating vast quantities of structured and unstructured data to build a complete view of the customer.  In doing so they will be able to offer a differentiated service:

  • Improved segmentation and targeting
  • Customer-centric rather than product-centric engagements
  • Tailored needs-based customer strategies
  • Moving customers smoothly to onboarding

In 2019 PWC speculated that refining investment banking sales strategy will be a key focus area over the next couple of years.  This statement is even truer in 2021 than it was then.


In a typical investment banking organisation, the sales person engages the client, wins the business and initiates an onboarding request. A dedicated onboarding team then takes over to process the request and gather all relevant KYC and AML documentation i.e. credit and legal information (CCJs, directorships etc.), identification checks, financial history and so on.  Finally, the client trading account is set up, credit lines established and the traders take over.

This is a pretty disjointed process.  Unfortunately, client onboarding is too often viewed as a routine process, rather than an opportunity to build relationships.  The different front, middle and back office teams involved are not motivated to collaborate, and even if they try to they are hampered by fragmented processes that prevent a seamless onboarding service.   The result being vast amounts of manual work, long turn-around times and frustrated customers.

The problem starts with lack of data, or more accurately the lack of a centralised view of the client.  In 2019 PWC research suggested that 84% of banks expected to have significantly advanced data and analytics capabilities by 2025.  Nowhere is this investment more urgently required than onboarding.

By combining the internal know-how of the entire bank (front, middle and back) and harnessing data science to automate external customer identification and data collection processes (KYC and AML activities, credit and risk actions), then layering the two together and applying an AI-powered rules engine to flag issues immediately, investment banks can drive increasingly agile onboarding processes, and in turn greatly improve all facets of the client onboarding experience.


PWC observed that a decade after de-risking, investment banking must be centred on clients and service.  Again, this is certainly true in 2021.  In an increasingly challenging and competitive capital markets environment, investment banks must place greater emphasis on client relationships if they are too survive and thrive.

Just like sales people, traders must put client relationships at the heart of all activities, and leverage advanced knowledge and know-how of each client’s specific needs to bring the full capabilities of the bank to bear.

By combining everything a trader, and the wider bank, knows about its customers and markets, and leveraging an advanced data science engine that ingests millions of structured and unstructured data points to layer on top of that know-how, traders can quickly access impactful insights and risk intelligence needed for next-generation trading – aligning constantly with customer needs for differentiated decision-making and outcomes.

Operational efficiency

In 2021, the challenges investment banks face are significant.  They are operating in a competitive environment of rising cost pressures, where rapid action and response is imperative.  They can no longer wait to modernise their technology stack, to support advanced efficiencies of the front, middle and back functions of their businesses, if they are to increase revenue, whilst optimising the balance sheet and reducing cost.

Beyond customer centricity and differentiation, SaaS banking intelligence platforms are also pivotal in helping investment banks optimise operations and rein in costs.  By capturing an investment bank’s collective expertise and know-how (breaking down silos associated with legacy technologies and practices), and applying advances in technology and data science, banks can achieved vastly improved efficiency, efficacy and consistency, at scale, which can drive down research costs, activate faster data-driven decision-making, allow the automation of manual processes, improved collaboration and so on.


Regulators continue to refine existing regulations implemented in the wake of the pandemic, and reinforce the core investment banking pillars of governance and risk management.  A dynamic regulatory environment, coupled with market forces shifting constantly as a result of the pandemic, requires greater transparency, effective management and use of quality data, automated processes, and a systemic approach to monitoring through the client lifecycle.  So how to do this whilst at the same time delivering growth?

Give the compliance team a sophisticated decision engine to enable incoming data to have rules applied and tasks created, then distribute these tasks to appropriate front, middle and back office staff, monitoring their completion and evidencing the whole process. The automation aspect of this is fundamental, because it brings efficiency, consistency and control to the areas it transforms. It puts risk at the heart of the business, and at the same time allows compliance analysts to focus on work that requires their skills and experience.

Application of work flow automation, data science, and applied technologies can also be utilised to better address risk measurement and reporting, digitised monitoring and risk early warning and mitigation.

Investment banks must be agile and adaptable to face current and future disruption

Accelerating customer-centric investment banking requires leveraging artificial intelligence, data science and advanced automation tools to underpin your business know-how.

What if you could capture your Know-How – the domain knowledge and experience that sits in the brains of your people – and quickly and cost effectively put this to work for you in a system that’s finding opportunities and risks for you 24/7, wherever and whenever they appear?

Well, that’s Artesian Connect.

Artesian Connect automates key aspects of your business process by applying configurable rules to premium data sources, powered by the Artesian Insight Engine.

  • You know your business. We know technology. Together, it’s a powerful combination
  • A platform uniquely tailored to your business and your goals
  • Configured by your subject experts, leveraged by your front-line teams
  • Efficiency, efficacy and consistency

Get in touch with us to find out how your competitors are already experiencing next-generation sales, onboarding, trading, customer monitoring, ongoing assessment of portfolio risk, and how we discover your Know-How Equation and design and deliver an Artesian Connect platform that’s as unique as your business.