Strategies for creating value from data

In our recent white paper, Letting Go of Legacy, we discussed several new directions for financial organisations in a post-pandemic future, and I shared some of our findings in my July blog. High on our list of concerns was capitalising on the proliferation of financial data, using advanced technologies such as AI and big data management. ING's Stephane Malrait commented that ?we can definitely see the acceleration of data usage and rapid changes that are needed in larger organisations to create value from data?, while these organisations believe that data holds a lot of answers.

S&P's Matthew Aslett explained that effective data usage requires cultural and organisational change - such as reducing or removing data silos, investing in employees? data literacy, and democratising data. Firms must ?ensure that staff across the whole organisation have the skills, tools and access they require to read, analyse, understand, and communicate with data?, and are working within an organisational culture where everyone is encouraged to share their ideas.

Meanwhile in a British Computer Society article Jay Boisseau and Lucas Wilson said that ?all enterprises generate massive amounts of data from diverse sources?., and argued that data management plays an essential role, because firms need to convert structured and unstructured data from different systems and silos into collections of useful, consistent data from which applications and algorithms can extract understanding and value.

A recent Siemens report similarly pointed out that companies often face a mountain of unstructured data, tangled data streams, and scattered data sources. But this data is valuable: we found that unstructured and alternative data sets are central to financial firms? data management strategies. And they will need specialised tools to manipulate their unstructured data - from call centre transcripts to reinsurance contracts - whether doing so themselves or buying from third parties who have built a business structuring unstructured data, then selling that as a service to others.

According to Will Robinson of CMIS, bringing huge disparate datasets together and ensuring they are of the right quality and consistency builds the solid data foundations ?for all of the more advanced technology that sits on top?. Firms can then dig deep into their consolidated data to identify the hidden trends that make a difference in operations, whether using robotic process automation (RPA) or AI, data analytics or machine learning.

For example, RPA technology can drive down operational costs by automating transaction-heavy, manually intensive tasks, handling repetitive, time-consuming work such as invoice processing and regulatory reporting. From the audit perspective, we use automation to improve a 100-year-old paper-based manual processes, the confirmation process. This has allowed financial institutions to have an 88 per cent faster response time to requests, reducing staff time and manual errors.

AI is employed in areas ranging from automated credit scoring to insurance underwriting and in increasingly specialised applications, such as curbing abusive messages attached to money transfers. And addressing one of Confirmation's key concerns, machine learning techniques are helping to highlight potentially fraudulent activity. EY designed an algorithm that can ?correctly uncover fraudulent journal entries?, while PwC has cocreated a ?revolutionary bot? that applies judgment 'to detect anomalies in the general ledger?.

These value creation initiatives - organisational and cultural change, data management, and the application of advanced technologies - must form part of an overall data strategy that addresses a firm's business needs. As I indicated in my conclusion to our white paper, financial organisations rarely want to spend time and resources developing their own data management and analytics tools. Instead, they look to build partnerships with third parties who specialise in the technologies that will help them achieve their strategic goals.

If you want to discuss any of the findings in our report, please contact me. Alternatively, we held a webinar alongside UK Finance where we explored the specific challenges and opportunities banks face when adopting technology, where they are prioritising and how they are implementing technology transformation. You can find the recording of the webinar here.

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