On Wednesday 20 September 2023, Michael Lutterodt and George Holman from our Banking & Markets EMEA practice attended the Big Data LDN exhibition. It’s the UK’s leading data, analytics & AI conference and exhibition, hosting leading data, analytics & AI experts to deliver the most effective data-driven strategy.
A week on from the event and having had a chance to digest everything from the day, we asked them to share their thoughts and key takeaways from the day.
Firms may not truly understand their existing tech and data stacks and may not be making the most of their existing vendor products
More through necessity than design, many Financial Services organisations find themselves operating with a complex and often antiquated technology and data ecosystem. Regulatory obligations and budgetary pressures have left many firms having to implement tactical on top of legacy. This can create redundancy and latency issues and make identifying and investing in the right strategic solutions a challenge. Some of the feedback we received from data technology providers is that firms often don’t truly know their own tech and data stacks and won’t be fully utilising the breadth of capabilities that vendor technologies can offer. We would encourage firms to thoroughly document their system and data architecture, log technology assets in a dynamic repository and, when looking at investing in a new capability, to consider if they may already have the answer and simply need to make more of what they already have.
Resilience needs to be front of mind when it comes to data
Operational Resilience has been a hot topic for a number of years. DORA (the Digital Operational Resilience Act) is broadly viewed as the next turn of the regulatory wheel. We wrote about DORA here and it will be crucial for Financial Services firms and market participants to implement mandatory technical measures to protect data and create resilience. This will include maintaining:
- Highly auditable standards of data availability, integrity, authenticity, traceability and confidentiality.
- Dynamism in responding to incidents, threats and vulnerabilities, linking through to impacts, analysing the cause(s) and factoring that into meaningful improvements for prevention.
People are still required
There is a collective feeling that, although AI is the direction of travel, there is also a sense of distrust towards relying on it for complex and critical business processes. It is broadly acknowledged that AI can disrupt traditional organisational structures: people, processes and platforms. However, quite a few of the data leaders we engaged with remained cautious about one of the known unknowns with AI: the error rate. Current estimates put AI’s error rates anywhere between 3% to 25% and this presents risks and issues when operating in such a highly regulated and client-centric industry and environment, such as financial services. When accuracy and integrity are paramount, particularly around key business functions, speed and cost often become less important factors. Firms will, therefore, need to identify and embed the right strategies, levels of resourcing and culture during this potentially transformative period for the industry. This will need to include quality control mechanisms and up-skilling employees to work alongside AI, truly understand and be able to interrogate and remediate AI solutions and associated data, where errors may persist.
Firms should conduct thorough vendor selection processes upfront
When it comes to data products and associated AI technologies, the market is vast, meaning sifting through vendors requires a robust and pragmatic approach. In a market saturated with the same or similar solutions, running a vendor selection process is critical to ensure:
- Alignment: Ensure partners align with financial goals and regulatory compliance.
- Innovation: Choose partners with cutting-edge capabilities for long-term competitiveness.
- Trust: Prioritise vendors with impeccable reputations to maintain customer trust
- Agility: Seek partners who can adapt to market changes swiftly
- Security: Emphasise robust cyber security and data protection measures
- Longevity: Assess a partner’s long-term viability for sustainable partnerships.
Environmental, Social, and Governance (ESG) data is a hot topic
ESG is a hot topic in financial services due to its ability to mitigate investment risks, meet investor demand for ethical investments, align with evolving regulations, offer a competitive advantage, enhance reputation management, address global challenges, and foster innovation within the industry. It’s a multidimensional framework that’s reshaping how financial institutions approach investments, reflecting the growing awareness of environmental, social, and governance factors in our sector.
Other industries are ahead of Financial Services
In the realm of digitalisation, sectors such as e-commerce, technology, energy and utilities, media entertainment and telecoms have undergone more extensive digitisation compared to financial services. In fact, financial services companies now face a daunting challenge when it comes to managing their data and technology ecosystem, given the multitude of providers involved. It’s crucial for them to have a deep understanding of their business model, identity, and revenue generation strategies both now and in the future. Moreover, they must establish a set of guiding principles that ensure the resilience of their business, agnostic of technology providers to ensure future-proofing.
Shifting away from viewing data as a mere byproduct of infrastructure and recognising it as a valuable, tradable asset will prompt the industry to reimagine its position in the market. Lastly and perhaps most importantly, regulatory bodies play a pivotal role in steering the industry toward a more digitally transformed future.
Get in touch
If you would like to discuss anything mentioned in the article or have a question about data in your organisation, please contact us to find out how we might be able to support you.
