Internal tech expertise: top 3 concerns for CROs

With the right investment, banks can ensure agility and competitiveness, and more easily navigate shifting business demands. A recent survey by Quantifi underscores concerns voiced by Chief Risk Officers and Heads of Risk Systems at tier-2 banks regarding their in-house technology expertise.
20 Jun, 2024

Faced with fintech advancements and cybersecurity challenges, banks are forced to strengthen their tech capacities. Banks acknowledge that a strong in-house tech proficiency is necessary for establishing innovative solutions, streamline operations, and strengthen the security of financial data. With the right investment, banks can ensure agility and competitiveness, and more easily navigate shifting business demands.

A recent survey by Quantifi underscores concerns voiced by Chief Risk Officers and Heads of Risk Systems at tier-2 banks regarding their in-house technology expertise. The survey revealed three standout concerns across all global regions: reliance on outdated technology, ineffective use and aggregation of data, and the inability to identify specific technologies to help banks achieve strategic goals.

The cost of legacy solutions

Banks often rely on legacy systems that, though once reliable, now pose problems amid rapid technological advancements. Holding onto and trying to maintain outdated solutions can put banks at a disadvantage.

The lagging legacy

Outdated systems often lack the speed and processing capabilities of modern platforms. While modern solutions leverage cloud computing and distributed databases for real-time transaction handling, legacy solutions frequently employ batch processing. This difference can slow down decision-making, especially critical in fast-paced environments such as algo trading. Failing to analyse data promptly may lead to missed opportunities and delayed responses to market shifts, ultimately affecting profitability and competitiveness.

Breaking down silos

Legacy solutions typically operate in silos, making integration with new technologies or other IT infrastructures difficult. This fragmentation hampers comprehensive risk management, increases cost, and operational risk. Consequently, data aggregation and analysis become challenging, leading to incomplete or delayed risk assessments and potential unforeseen risks for the bank.

Counting the cost

The financial burden of maintaining outdated technology often surpasses the cost of adopting new solutions. Legacy systems require specialised expertise, which is increasingly rare, thereby inflating maintenance and support expenses. Furthermore, the inefficiency of older technologies results in elevated operational costs. The cost of upkeep can deplete resources that could otherwise be allocated to strategic initiatives, thereby sustaining a cycle of technological obsolescence.

Security risks

Relying on outdated technology significantly heightens the risk of security vulnerabilities. Regulatory authorities, including the European Central Bank and the U.S. Office of the Comptroller of the Currency, impose stringent requirements for data protection and cybersecurity to mitigate such risks.

From data chaos to clarity

Many banks face significant challenges due to ineffective data utilisation and aggregation. In a landscape where data-driven decision-making is crucial, some banks struggle to harness the full potential of their data The problem is exacerbated by the vast volume of data. Without robust data management and analytics capabilities, extracting actionable insights becomes a difficult task.

Advanced data warehousing architectures are crucial for consolidating vast amounts of structured and unstructured data. They provide a cohesive platform that enhances data accessibility, integration, and analysis. This robust infrastructure supports risk management, regulatory compliance, and strategic planning, driving efficiency and innovation within the bank.

Implementing these architectures requires robust ETL processes to ensure data consistency and reliability. The utilisation of machine learning and AI help identify patterns and anomalies, providing predictive insights. Furthermore, APIs facilitate seamless data exchange between systems, enriching the data pool and enhancing risk model accuracy.

Regulatory requirements shape data warehousing solutions, necessitating compliance with standards like Basel III, GDPR, and Dodd-Frank. Firms must implement stringent data governance, security measures, robust data lineage, and audit trails to ensure data accuracy and transparency. Real-time reporting capabilities are also essential for meeting regulatory demands and providing timely risk disclosures.

Aligning innovation with strategy

Banks often face the task of selecting the right technologies that align with their strategic goals. The advancement of emerging technologies like generative AI, data science, and blockchain adds layers of complexity to this landscape. It is important for Heads of Risk System’s and CRO’s to grasp how these technologies can streamline operations and improve risk mitigation.. Nevertheless, integrating these cutting-edge tools into established infrastructures poses a significant challenge for many banks.

Harmonising technology investments and overarching business objectives can be difficult, either due to a lack of expertise or a disparity between a bank’s technology and business planning teams. Without a well-defined roadmap, investments run the risk of falling short of anticipated impact.

Assessing and choosing appropriate technology providers and solutions is complex. Banks must rigorously vet third-party offerings to match their strategic goals, compliance needs, and risk tolerance. Regulatory adherence is crucial, given the strict standards on data privacy, security, and transparency. Inadequate vendor evaluations can lead to subpar investments or partnerships, failing short of expectations and regulatory repercussions.

Banks face several challenges when it comes to harnessing technology to drive strategic goals. Overcoming these hurdles demands a blend of technological foresight, strategic insight, and thorough due diligence to ensure investments support business goals and regulatory requirements. By tackling these obstacles, banks can benefit from the transformative power of emerging technologies, securing a competitive advantage in today’s digital financial arena.

Technology built for the way you work

Are your legacy systems difficult to maintain, difficult to integrate and require huge effort in managing your data? Quantifi provides new levels of flexibility and efficiency with a single integrated view across trading, risk, and operations. Eliminate complexity and reduce costs with a solution built on a cloud-centric, data science-enabled technology stack.

Trusted by 5 of the 6 largest investment banks, Quantifi’s enterprise risk solution is a real-time platform that supports cross-asset trading, front-to-back operations, position and risk management (market, credit, counterparty, and liquidity risk), limit management, and regulatory reporting. An integrated analytics library generates results matching top-tier banks for even the most complex derivatives. Quantifi’s cloud-centric data science-enabled solution optimises operations for greater flexibility, scalability, and agility.

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