Data is the cornerstone of investment decision-making, and investment management landscape firms have achieved varying degrees of success in utilizing the vast amount of data available today.
Competitive pressures are arising regarding revenues, operating costs, winning new clients, and retaining existing clients. At the same time, companies must adapt to the ever-changing regulatory environment and comply with new streams of regulation.
Data, technology, and improved trade execution could all be utilized by businesses to increase investment returns, spur innovation, and provide better investor experiences.
In this blog, we’ll explore how Investment Banks and AMCs can best leverage the Snowflake Data Cloud with its unique data sharing, governance, and scalability capabilities to address these challenges.
Combating Financial Fraud Incidents with Snowflake
Financial services firms are experiencing increased reputational, financial, and regulatory risks for failing to detect fraud or achieve Know Your Customer (KYC) and Anti-Money Laundering (AML) compliance. Organizations must also cope with increased technology spending in addition to fines levied by regulators for non-compliance and reputational damage.
This is due to a fragmented ecosystem of data silos, a lack of real-time fraud detection capabilities, and manual or delayed customer analytics, which results in many false positives.
The data-sharing features of Snowflake enable enterprises to integrate their data without creating any data silos or building new technology capabilities. Snowflake Marketplace offers data from leading industry providers such as Axiom, S&P Global, and FactSet.
Snowflake provides Data Clean Room capabilities and features such as dynamic data masking and end-to-end encryption for data in transit and at rest. Data Clean Rooms provide data exchange, double-blind joins, and limited searches, resulting in several firms exchanging and matching consumer data without disclosing any underlying information.
Snowflake Enhances Compliance Reporting Processes
As Investment Banks become cross-regional, the regulatory requirements become complex and stringent in nature. A fragmented and manual approach will not be effective for a multi-segment business having worldwide operations.
This often results in failure to incorporate crucial data for regulatory disclosures and increases the likelihood of reporting mistakes due to siloed data.
Snowflake enables organizations to instantaneously scale to meet SLAs with timely delivery of regulatory obligations like SEC Filings, MiFID II, Dodd-Frank, FRTB, or Basel III—all with a single copy of data enabled by data sharing capabilities across various internal departments.
Snowflake’s object tagging feature helps firms to classify PII and define data governance policies based on the tags associated with the object and track the usage of sensitive information.
Once that data is tagged, an access history log is available as required for regulatory compliance. Snowflake complies with regulatory requirements while securely sharing data with role-based access controls, tri-secret security with improved encryption, and integration with third-party tokenization providers.
Transforming Asset Servicing with Snowflake
Many asset servicing firms still rely on legacy, time-intensive manual processes and fragmented data silos to run their operations. As assets under management (AUM) rise, asset managers, regulators, and institutional investors demand transparency with timely reporting.
Faced with these challenges, asset servicers have acquired numerous technologies over time to meet their risk management, fund analytics, and settlement needs, leading to data fragmentation and inheriting complex data flows.
Snowflake’s data sharing enables AMCs to join internal data with third-party market data, as well as data that sits across applications and data warehouses.
By having all their data in a single, globally available, governed platform, AMCs can build a strategic security master database and also support their workflows efficiently.
Daily Net Asset Value (NAV) computation, portfolio performance analysis, and reporting can become efficient and reduces time to market, with Snowflake’s multi-cluster concurrency architecture that separates data from computing.
Boost Efficiency of Quantitative Trading and Research
Asset managers and hedge funds need to drive greater efficiencies in portfolio construction, trade implementation, and risk mitigation.
Data movements lead to high costs of ETL and rising data management TCO. The inability to access and onboard new datasets prolong the data pipeline’s creation and time to market.
Data access via Snowflake Marketplace or private share enables business teams and data scientists to leverage new and differentiated data, including market, identity, geospatial, ESG, cryptocurrency data, etc.
Data co-location enables teams to access, join, query, and analyze internal and external vendor data with minimal to no ETL. This vastly improves the data freshness and lowers the overall Total Cost of Ownership (TCO).
Additionally, various Snowflake connectors enable direct integration with transaction applications, simplifying the data ingestion into Snowflake.
Snowflake’s Kafka Connector automatically ingests data directly from a Kafka topic in real-time, Snowpipe is an entirely serverless process, and Snowflake manages the operation entirely, scaling out the compute as needed.
Also, Snowflake is cloud-native, which frees up organizations from ongoing maintenance obligations and offers elastic near-infinite resources—all without worrying about the IT infrastructure. This enables AMCs to deploy compute-intensive artificial intelligence (AI) and machine learning (ML) tools with Snowpark, which can swiftly implement new approaches to research.
Know all About your Customers with Snowflake
Consumers have become more diverse demographically, and expect faster and more personalized services. AMCs need to leverage their data and technology to deliver differentiated customer experience. However, many banks are limited by siloed and inadequate technology architectures resulting in a poor customer experience, missed opportunities with delayed customer analytics, and compliance risk.
Snowflake Financial Services Data Cloud centralizes data from various sources and enables data enrichment with data from third-party sources, including demographics, identity, macroeconomic, and alternative data.
This helps to create holistic consumer profiles and predictive analytics that inform personalization, marketing segmentation, product suitability, and better market penetration.
As the financial industry increasingly becomes more data-driven, the demand for futuristic, cloud-based solutions will continue to grow. If your organization’s prevailing solution is unable to keep pace, perhaps it’s time to restrategize.
Snowflake’s zero-management infrastructure and multi-cluster shared architecture simplify data management, freeing up additional capacity for analytics. Snowflake’s offerings like data sharing, Snowpark, and its unique architecture will eliminate data silos, lower TCO, asset-light infra setup, and enterprise-grade governance controls, making data work for your business.
Interested in leveraging new Snowflake features? As the Snowflake 2022 Partner of the Year, phData has the experience and expertise to help your organization get the most out of your Snowflake investment.
Contact phData today for any questions, advice, best practices, or data strategy services.