News & Analysis

Rethinking New Data Challenges for Financial Companies

Coming into 2020, the data landscape for financial institutions was already subject to significant transformative forces, notably around increased expectations on data privacy, continued internal pressures to reduce costs and additional customer demands for new services and digital offerings. COVID-19 has now ushered in unprecedented disruption, impacting not just customer and employee health and safety but also business continuity and the financial system as a whole.

In times of crisis, particularly of this scale, it is a challenge to plan beyond the next few weeks, let alone months. However existing data challenges will not disappear in the meantime – in fact, COVID-19 only re-emphasizes the need to address them in the most diligent and forward-looking manner possible, said Joseph Forooghian, Principal consultant, CAPCO Global business and technology consultancy, in a recent whitepaper shared with CXOToday.

As the pandemic brings into sharp focus new challenges for financial institutions, Forooghian believes, the proliferation of digital channels will continue, if not accelerate – and data organizations will play a critical role in helping the industry respond to this market dynamic in an effective and efficient way.

At the beginning of the year CAPCO identified 12 key data trends in 2020 impacting near-term regulatory and cost challenges as well as strategic, revenue-generating objectives. Inevitably COVID-19 will have significant implications for those ‘data differentiators’.

Modelling Risk in the Midst of Pandemic

The global recession that looks set to follow the pandemic will have a significant impact on financial institutions’ clients. Banks, for instance, will need to reassess how they model credit risk by looking at the network impacts of shocks through their client base. Risk modeling will need to look wider than credit, market and liquidity risk and focus on operational risk, the whitepaper mentioned.

According to Forooghian, analytics will play an important role in looking at how credit shocks will impact on their complex network of clients and the solvency of those clients. Banks will need to focus on identifying early signs of problems and taking pre-emptive actions to help their customers with credit and liquidity issues

“More modeling, and more data within these models, will demand an increased focus on better understanding the provenance and quality of data used in such models, and on effective model governance and appropriate model validation,” he said.

Business Resilience and the Digital Twin

Key to both continued operations and the management of operational risk is a clear understanding of organizational dependencies around infrastructure, employees and third-party vendors. Being able to comprehensively map an organisations’ people, process, data and technology will be critical to navigating through the challenges that COVID-19 has brought to light.

In this context, Forooghian emphasizes the need to understand an organization’s ‘Digital Twin’, which sets out its operating models in a manner which is navigable and can be queried. This allows a clearer understanding of the ‘what-if ‘ramifications of different scenarios. “We foresee organisations needing to stress test their operations much as they currently stress test their capital,” he says.

Keep Analytics going in an Agile fashion

Whether providing digital offerings to their clients or managing complex cost environments in resource-heavy processes such as KYC, organizations’ analytics pipelines need to be developed with robust data management as the foundation. Firms should continue to focus on building data ‘assets’ that can be reused, the whitepaper said.

COVID-19 presents a specific challenge to analytics teams as regards access to data in a digital workforce. The only way to resolve this is via enterprise analytics platforms, and here data organizations should continue to take ownership and push for their development and enhancement.

Vulnerable Customers

Institutions can identify where customers may need financial support or are suffering from poor mental health by analyzing spending patterns from transaction data. COVID_19 has meant significant financial uncertainly for customers, and the importance of support or intervention is greater than ever.

“Banks are increasingly looking to understand customer appetite for proactive, data-driven support. We expect the UK Financial Conduct Authority and Information Commissioner’s Office to provide guidelines on how banks can ethically provide such services, which should rapidly gain traction in the wake of the pandemic,” it said.

Customer Identity and KYC

Challenges around confirming customer identity will be exacerbated during the pandemic. As Forooghian said, banks can carry out Anti-Money Laundering checks using smart phone selfies as well as scanned documents sent by email, firms will need to accommodate new data sources.

According to him, “To address identity-related challenges, there will need to be  clear segregation of an individual customer’s identity, relationship and transactions, with organizations gravitating towards more sophisticated analytics solutions – such as entity resolution and network analytics – to manage a single repository of customers in a secure and ethical fashion.

With KYC, now one of the fastest growing costs within organizations, more sophisticated, risk-based data analytics approaches need to be taken to build more robust client profiles and take a more pragmatic risk-based approach to KYC.”

Data Quality Cost Reductions

Financial institutions will be under pressure to rapidly identify cost-cutting opportunities. Key to achieving this is a proactive understanding of, a firm’s reliance on costly, manual mitigating controls and any duplication of data quality checks across their data flow. Additionally, understanding how poor data quality impacts firms’ digital channels and offerings will be the key to effective automation.

Forooghian believes that gaining this insight presents opportunities to ensure the data is correctly controlled at source via automated means, thus eliminating the need for costly manual controls downstream.

“Through a resultant increase in data quality, firms will be able to undertake more accurate risk reporting and by extension achieve a better understanding of their available capital during the pandemic,” he summed up.

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Sohini Bagchi
Sohini Bagchi is Editor at Trivone Digital, a published author and a storyteller. She can be reached at sohini.bagchi@trivone.com