In today’s digital age, the banking, financial services and insurance (BFSI) sector are grappling with increasingly complex challenges related to fraud, risk management and mitigation. As cyberthreats and financial crimes continue to evolve, traditional methods of fraud detection and risk assessment have become less effective. To stay ahead of these challenges, organizations are increasingly relying on data products to enrich their data and enhance their fraud reduction and risk management strategies.

The Data Revolution in BFSI

Data is the lifeblood of the BFSI sector. It fuels decision-making, helps identify market trends, and plays a crucial role in mitigating risks and preventing fraud. However, the sheer volume and complexity of data generated within the sector can be overwhelming. And this is where data products come into play.

What Are Data Products? 

While data products are getting a lot of buzz in the industry, there are many interpretations of what a data product is. So, let’s set the record straight. 

Data products make data tangible for everyone across the organization. They provide ready-to-consume sets of high-quality, reliable, and accessible data that people throughout the business can easily use to solve business challenges. The best data products are organized based on business entities and governed by domain. They consist of comprehensive, clean, curated and continuously updated data sets that are aligned with key business entities, making them consumable by both humans and machines across the entire enterprise. 

Examples of domains and key business entities that represent the core components of BFSI operations. Data products aim to provide high-quality, reliable and accessible data related to these entities, enabling businesses to effectively address various challenges and make informed decisions across the entire enterprise.

Domain: Banking

Key Business Entities: 

• Customers: Individual account holders, businesses, and organizations.
• Accounts: Savings accounts, checking accounts, certificates of deposit (CDs), and more.
• Transactions: Deposits, withdrawals, fund transfers, and payments.
• Loans: Mortgage loans, personal loans, auto loans, and business loans.
• Credit: Credit scores, credit reports, and credit card accounts.

Domain: Insurance

Key Business Entities: 

• Policyholders: Individuals or organizations holding insurance policies.
• Policies: Insurance policies covering various risks, such as life insurance, health insurance, property insurance and auto insurance.
• Claims: Insurance claims filed for reimbursement in case of covered events.
• Premiums: Payments made by policyholders to maintain their insurance coverage.
• Underwriting: Assessing risks and determining policy pricing.

Domain: Investment and Asset Management

Key Business Entities:

• Investors: Individuals, institutions, and funds investing in financial markets.
• Securities: Stocks, bonds, mutual funds, and exchange-traded funds (ETFs).
• Portfolios: Diversified collections of securities managed for investors.
• Market Data: Real-time and historical market information, including stock prices, indices, and economic indicators.
• Asset Allocation: Strategy for distributing investments across different asset classes.

Artificial intelligence (AI) plays a key role in enhancing and optimizing data products by automating the data cleaning, integration and analysis processes. It enables complex computations and predictions that can drive more accurate insights from vast amounts of data. Furthermore, it facilitates the development of machine learning models that can be embedded within these data products to enhance data quality, accuracy and relevance, providing BFSI organizations with a competitive edge in fraud detection and risk management.

Data Products are Engineered for Enrichment

The goal of a data product is to deliver the best version of your data. But many times, the best sources to enrich the data exist outside of the organization—e.g., credit bureaus, government databases (identity verification, tax records, criminal records, and property ownership), third-party fraud databases and cybersecurity threat intelligence. These external data sources, when effectively integrated and analyzed, provide BFSI organizations with a broader and more comprehensive view of their customers, operations and the external factors that influence their business. Leveraging these diverse data sources is instrumental in reducing fraud, improving risk management and enhancing mitigation strategies in the BFSI sector.

That’s why savvy organizations utilize data products that include robust data enrichment capabilities already built in. By linking internal and external data using unique IDs, data products allow businesses to match their data with trusted sources that best align with business needs. This way, businesses can choose and add new, relevant columns based on selected external sources and attributes.

Enriched Data in Action: Real-World Examples

Data products with built-in enrichment capabilities are already making a significant impact in the BFSI sector. Below are a few examples:

Fraud Detection: An enriched customer profile can help identify anomalies in customer behavior, such as unusual spending patterns or suspicious account activity. This information can be used to flag potential fraudulent transactions in real-time, preventing losses and protecting customers.

Risk Management: By integrating data from credit bureaus, government databases, and other sources, data products can create a comprehensive risk assessment of potential borrowers or clients. This information can help financial institutions make more informed decisions about lending and underwriting, reducing their exposure to risk.

Mitigation Strategies: Enriched data can also be used to develop targeted mitigation strategies for specific risks. For example, an insurance company might use data to identify customers who are more likely to file a claim for certain types of damage. This information can be used to proactively reach out to these customers and offer preventive measures.

The potential of data products in the BFSI sector is profound and far-reaching. Powered by AI and robust data enrichment capabilities, these tools are revolutionizing how organizations tackle fraud, manage risk, and develop mitigation strategies. By tapping into a broader spectrum of internal and external data, businesses can gain a more comprehensive understanding of their customers and market trends. This enhanced visibility and insight not only help in detecting fraud but also in making informed decisions to manage and mitigate risk. As we continue to navigate the complexities of the digital age, data products will undoubtedly be at the forefront, guiding BFSI organizations toward smarter, safer and more efficient operations.