Industry
Banking
Banking on purpose-led ecosystems
Solution
Highlights
- The data-rich banking industry is subject to strict regulations. Also, secure data archiving is a significant liability for banking institutions.
- The rising number of fintech unicorns, offering easy access to finance for a larger population, combined with advanced technologies, helped generate terabytes of data, and analyze consumer behavior.
- However, traditional banks need to overcome a few key challenges to tap into the benefits of leveraging data—as a revenue generator.
- As new regulations contemplate promoting a shared data infrastructure in the banking and finance industry, banks can build on the advantage to create winning solutions.
In this article
A data-rich industry
Big data: How this asset can be a liability
The volume of data generated and held by companies has grown tremendously, over the last few years. With advancements in big data, analytics, and AI, the value of this data has also increased exponentially. As the banking industry is data rich, it is subjected to strict regulations and penal controls. To hold and archive this data securely is a significant liability for banking institutions.
Terabytes of data
Rising challenge of fintech unicorns
Many fintech unicorns (data-driven financial services) have emerged in the last decade. The technological innovations that they have introduced enable cheap and easy access to finance for a larger population. Lenient regulations, advanced technology, wider internet coverage, and smarter mobiles facilitated the growth of these fintech companies.
Today, the digital banking space is buzzing with advanced technology driven by social media, mobile computing, analytics (big data), cloud computing, and so on. Neobanks, payment apps, and Bigtech have emerged as incumbent components along with traditional banks in the financial ecosystem. Terabytes of real-time data are now available to offer deep insights into consumer behavior, predict customer preferences, and drive hyper personalization in banks.
Data Monetization
Key challenges to driving new revenue streams with data
Barring a few large banks, the banking industry has limited capabilities for data analytics, depriving the traditional banking sector of monetizing the value of data that they possess. The banks should take advantage of new regulatory directions that promote a shared data ecosystem, to leverage data assets and offer non-banking services, such as:
1) Share insights on customers’ financial behaviors and preferences with customers’ consent
2) Create tailored offers and personalized banking services for their customers in partnership with merchants
3) Offer services like identity and verification (ID&V) confirmation for their customers to third parties (with due customer consent)
The main challenges for traditional banks in this regard appear to be –
- Lack of technical expertise: Rapid growth in data requires better acquisition, organization, integration, and analysis. Currently, traditional banks lack the infrastructure and knowhow.
- Historical regulations mindset: Notwithstanding modernization of regulations in some countries, existing regulations have largely restricted banks from leveraging customer data as a business enabler.
- Disparate data stores: Traditional banks are departmentalized, leading to data storage in silos and a lack of metadata. In this situation, banks hold large amounts of data without meaningful analysis.
- Data stores are hosted inhouse (local storage): Entails significant capital expenditure on infrastructure, maintenance, and backup of on-premises servers.
A New direction
The way forward for regulators and banks
Previously, regulations (pre-2017) did not envisage a wide scale secure internet connectivity and cloud infrastructure. EU (PSD2-2018) and Australia (CDR-2020) have recently introduced new regulations that take a modern view of technical advancements and promote shared data infrastructure in the banking and financial industry. Many other countries are also updating their regulations to allow banking and financial companies to share and utilize data.
In retrospect, banks have a significant advantage of exclusive possession of data. With new modern regulatory indicators, it is time to convert this advantage into winning solutions.
The following steps are required to use data effectively:
- Breaking the silos and unifying data management on cloud with entitlement-based access across internal organization
- Using cloud for data storage, to –
- replace capital expenditure with operational expenditure
- reduce overall cost—although initial migration may appear expensive the long-term ROI is significant—as it frees up IT personnel’s time to manage physical infrastructure
- reduce data backup costs significantly and enable real-time backup availability
- deploy AI-supported analytics tools within the organizational technology ecosystem
- Build data analytics capabilities by –
- upskilling existing staff or hiring new staff with data analytical skills
- engaging with vendors for the right skills in analytics and insights
- Enrich internal data with external data sources to create viable research products. The external data sources can be –
- Open-source third-party data, for example, population statistics, demographic and economic data collected by the government
- Private sources like social media players (Google, Apple, Facebook, Amazon, and the like) or local telecom companies which also offer rich data sets, such as geographic location data generated by telecom companies, or user browsing patterns.
At face value, the data held and continually generated by banks, appears to be of little value in its raw state. However, if it is structured, formatted, and analyzed, it can offer significant tangible and intangible value. Today, as banks face major headwinds on traditional margins, monetizing data will alleviate some of the challenges.
