Financial Services

As enterprises have scaled and developed new lines of business (or acquired other businesses), there are 2 categories of issues that have arisen:
‍
1. Customers have different experiences based on the unit of the enterprise they are dealing with eg. retail banking client seeking a life product at the same bank.
2. Customers receive different treatment depending on which business area of the business they are dealing with eg. new policy creation experience varies from claims support experience.

With Pygio Assemby, we are able to map a customer’s entire life-cycle with your institution, ensuring that they receive the best treatment possible given the data the institution already knows about this customer.

Ensure onboarding, upselling, support, cross selling, renewals, activations and fulfilment is handled with care and that your customers receive white-glove experience, at scale.

In retail as well as corporate and investment banking, detecting fraud, money laundering, or unauthorized trading activities quickly is critical. Pygio Assembly, powered by Snowflake’s platform, enables real-time anomaly detection by streaming and analyzing transactional data at scale. With machine learning models running on the fresh data, the bank can flag suspicious activities (e.g. anomalous payment patterns or unusual trading behaviors) as they occur.

Snowflake’s native support for AI/ML (through Snowpark and integrations) allows deploying fraud detection models directly where the data lives, minimizing latency. This modern AI-driven approach goes beyond static rule-based systems – over time, ML models can learn evolving fraud patterns.

In the investment banking and asset management business, we facilitate advanced analytics and AI to drive better investment decisions and trading strategies, on the Snowflake platform. By pooling massive datasets – market prices, economic data, client trading behavior, research reports – and analyzing them in Snowflake, the bank’s quants and data scientists can develop predictive models for market trends or asset valuations.

Because Snowflake can handle structured and even unstructured data, analysts might incorporate news feeds or social media sentiment into investment models (easily connect with external data sources through Snowflake Marketplace). Additionally, high-speed analytics on the data cloud means risk calculations and options pricing can be run more frequently and in greater detail. In short, Snowflake provides the scalable computing canvas for CIB to apply cutting-edge AI techniques – from classic machine learning to deep learning – to gain an informational edge in markets and investment banking activities, ultimately delivering better outcomes for clients and the bank.

Our analytics and data platform capabilities aim to empower your financial institutions to replace countless spreadsheets and manual processes in finance teams. Banks can perform balance sheet modeling, profitability analysis, and scenario planning at scale in the cloud.

For example, instead of running static Excel models, finance analysts can leverage Snowflake (with connected tools) to model multiple scenarios (interest rate changes, economic stress tests, etc.) on demand. This includes credit portfolio optimization – using historical and external data to forecast credit risk and adjust loan pricing or provisions proactively. By speeding up financial forecasting and giving executives interactive scenario dashboards, the bank can respond quickly to market changes with data-backed strategy adjustments. Snowflake’s integrations with third-party analytics tools also allow CIB to incorporate advanced risk models or macroeconomic data easily into their planning process, yielding deeper insights for strategic decision-making.

Banks face heavy regulatory reporting obligations (e.g. Basel capital reports, liquidity coverage, IFRS financial reports). A Snowflake-centered data strategy can automate and accelerate regulatory reporting by consolidating all required data in one governed platform. Snowflake’s computing power enables generating complex compliance reports in minutes rather than days.

This means reports for capital adequacy, large exposures, or stress tests can be produced on-demand with up-to-date data, ensuring both speed and accuracy. Automation reduces manual workloads and the risk of human error, while built-in data governance and audit trails in Snowflake help meet compliance and transparency standards. In short, banks can transform regulatory reporting from a painful, labor-intensive process into a streamlined, near-real-time capability – freeing staff to focus on analysis over data wrangling.

By leveraging Snowflake as a live data hub, banks can deliver real-time reporting and BI dashboards to executives and front-line managers. For example, a CIB executive dashboard could pull together live metrics on deal pipeline, trading P&L, loan book growth, and risk limits from Snowflake, updating continuously as new data flows in.

This is a leap from traditional static monthly reports to interactive dashboards available on demand. Using Snowflake’s native reporting tools or standard BI tools, the bank can build rich, self-service dashboards that visualize data instantly. Business users gain the ability to slice and drill into data without waiting for IT – an agility boost that fosters a truly data-driven culture. Real-time insights (e.g. intraday revenue by desk, or instant flash reports of operational incidents) enable faster response to issues and opportunities. In essence, Snowflake-powered reporting turns management information into a live feed, enhancing decision-making at all levels.