In financial services, trust in your data is everything. But without knowing where your data has come from and how it has changed over time, the accuracy and integrity of your data becomes uncertain. This can damage customer relationships, make compliance efforts harder and ultimately inhibit your growth as a business.
That’s where automated data lineage tools come in.
Data lineage is the process of tracking data through its lifecycle, from creation to end destination. It provides a record of where data originates, how it moves through your organisation and how it gets transformed along the way.
Think of it as a roadmap, showing the route your data has taken through your organisation and all the stops it has made along the way. With automated data lineage tools, organizations can gain real-time visibility into their data flows, enabling faster, more confident decision-making, increased operational efficiency, and stronger data governance.
Below are five real-world scenarios in which automated data lineage capabilities would be indispensable for financial advisory firms and wealth managers:
Challenge #01: Demonstrating regulatory compliance
Scenario: a regulator reaches out to a firm and requests to see how risk profiles were assessed for a group of clients within a specific period. Without data lineage capabilities, the firm is left scrambling through hundreds of documents to piece together a clear picture for each of their clients. This a slow, error-prone process that could jeopardise their regulatory compliance efforts and put the firm at risk of fines and reputational damage.
Solution: with access to an automated data lineage tool, the firm can easily trace back each individual elements that made up their clients’ risk profile. They can access the calculation models and risk engines used, see the data that informed these models and where all that data originated. As a result, the firm can provide the regulator with full, transparent audit trail for the risk profiles created for their clients. Fines from the regulator are avoided, client trust is preserved and their business reputation is protected.
Challenge #02: Fixing inaccurate client reports
Scenario: a wealth management firm overstates a client’s portfolio value by including outdated bond prices. The error isn’t caught until the client complains. Without any data lineage capabilities, the firm spends days looking through their systems and spreadsheets trying to locate the issue. But it’s too late, the damage is done and the client’s trust is lost.
Solution: with the ability to trace the client’s portfolio figures back to their source, the firm can identify how these numbers ended up in the final report. They are able to quickly find out that outdated pricing data was used for the clients report due to a misaligned data feed. With the root cause of the error quickly identified, the wealth management firm is able to resolve the data feeds issue and improve their processes to prevent the issue happening again. As a result, they can be confident that that accurate reports will be delivered to clients in the future.
Challenge #03: Reconciling inconsistent client data
Scenario: A financial advisory firm finds that multiple clients have conflicting risk profiles in their customer relationship management (CRM) software and their financial planning tool. Without clear visibility into where each piece of data originates, the firm’s advisors are unsure which system reflects the most accurate and up-to-date information. This lack of clarity slows down their financial planning and introduces compliance risks which could undermine client trust.
Solution: with a data management platform that has automated data lineage capabilities, the financial advisory firm would have full transparency into where their data comes from and how it moves through the organization. This would quickly reveal that the CRM is pulling information from an outdated onboarding database, while the financial planning tool is using data directly from an active and regularly updated client portal. With this insight, the firm can confidently prioritize the planning tool’s data as the source of truth and correct the CRM accordingly. This supports improved client experiences as they benefit from more accurate, up-to-date profiles which inform their financial planning conversations.
Challenge #04: Streamlining the integration of multiple systems
Scenario: after acquiring a smaller advisory firm, the acquiring company faces challenges integrating the firm’s client data and systems into their own without causing issues around reporting and billing or interrupting their advisers’ workflows.
Solution: by having access to a data lineage tool, both firms are able to map how client, holdings, and account data flows through their respective systems. This then helps them identify which data pipelines may overlap or conflict, allowing them to simulate integration scenarios safely before merging environments. This means their actual integration is done cleanly – minimizing service disruption, reducing data duplication, and accelerating time-to-value from the acquisition.
Challenge #05: Building trust in AI analysis and decisions
Scenario: a financial advisory firm finds that an internal AI tool is suggesting portfolio changes based on what it understand as changing client circumstances. However, their advisors will frequently disregard these recommendations because they feel that they don’t reflect what they know about their clients. Since AI tool’s processes are opaque and there’s no way to validate its accuracy or relevance, the firm finds it hard to advocate for use of the tool.
Solution: if the financial advisory firm had access to a strong data lineage tool they could provide full visibility into how data flows through their internal AI tool. Advisors can then trace the AI tool’s recommendations back to specific, trustworthy data inputs, such as updated financial plans and real-time client account feeds. This transparency makes it easy to verify that the tool is working with current, relevant client data. As a result, advisors are far more likely to trust and act on the tool’s suggestions. This leads to faster, more confident decision-making and improves client experiences.
The smarter way to manage your data
At Raw Knowledge, we simplify the complexity of tracking your data’s journey with our automated data lineage capabilities. Our Managed Smart Data platform provides clear visibility into how and why your data has changed over time – along with easy access to historical dataset versions – so you can stay focused on delivering exceptional service to your clients.
Spend less time chasing data and more time delivering exceptional outcomes for your clients with smarter data management.
