Wealth management firm simplifies audit preparation and gains data estate visibility

优点

• Slashing time and effort to document their data estate and data movement through automation
• Saving days or weeks in regulatory audit response
• Anticipating data quality issues earlier to cut research time by half for customer and partner inquiries
• Improving data landscape visibility, understanding and governance to ensure data is AI-ready
• Maximizing the return on investment in erwin by Quest

故事

Since 1991, clients have put their trust in St. James’s Place, one of the largest advice-led wealth management firms in the UK. Having grown to nearly a million clients and £179 billion in funds under management, SJP has enjoyed three decades of organic growth. As they have grown, so has their data estate, spanning a wide variety of technologies, with a great deal of data moving among systems from many different vendors.

With no easy way to see into and explain their data landscape, SJP needed better support for regulatory requirements and to be prepared for auditing. They additionally wanted a toolkit to automatically document change in their landscape. Their goal was not only to quickly identify where data came from and address any problems at the source, but also to see the potential upstream and downstream effects of pending change.

The importance of data governance in finance

Our products are constructs of data,” says Ian Peters, Divisional Director of Group Data Management at SJP. “We are not a paper-based business at all. The way we manage the business, all of our financial information, products and services exist within our systems and applications as constructs of data.”

Data governance is an important concept for SJP, driven by its requirement to hold high-quality, well-managed data is for its operations. It has also been driven by the delivery of a mobile application for SJP investors and the arrival of recent hires bringing new, external perspectives on artificial intelligence (AI). Peters joined the Central Data Office and is creating a new data governance framework to bring control and direction across the organization.

"If your data isn't right,” says Peters, “AI will deliver sub-optimal results. That’s why one of our goals is to make our data AI-ready. The other is to manage the data that AI produces. It's not only about the data that AI consumes, but also about the data that it produces and the predictions from an AI model that drive decision making.”

SJP wanted to make sure they could understand the why and where of conclusions generated by AI, and how to use the conclusions in operations. They saw data lineage and data quality as integral to that understanding and looked for the right tool to arrive at it.

They didn’t have to look far.

Using erwin Data Intelligence for data lineage

Already underway within SJP was its Strategic Client Reporting project using erwin Data Intelligence as a data dictionary. The goal of the project was to identify and document the source of all data going into the reports that the company sent out to clients.

On the surface, the project requirement was relatively simple: to trace the one-hop lineage back to the system that was collating data from multiple sources. But it became obvious that erwin Data Intelligence could do a lot more and that SJP could get a lot more from their investment in the product.

“We weren't using the automation features in erwin Data Intelligence for scanning metadata,” says Peters. “We hadn't taken a close look at the other tasks the tool could accomplish for us. Take the business glossary, for example. Given any business term, what do we mean when we use it? How does the term relate to our data? And, what is our source for the data that corresponds to that term?”

SJP looked at the Strategic Client Reporting project and saw an implementation of erwin Data Intelligence around a very specific project and outcome. But the project took advantage of only a fraction of the total capability of the software, so Peters and his team sought ways to extract more return on their investment.

Documenting Consumer Duty reporting with erwin

erwin by Quest’s Value Attainment Program includes a method for exploring how customers are currently using erwin solutions and discovering ways to get more out of them. While embarking on the program with the erwin sales and services team, SJP also appointed a head of data intelligence to promote erwin throughout the organization. The effort led to applying erwin Data Intelligence to SJP’s requirement to report on Consumer Duty.

“Consumer Duty is a regulatory requirement imposed on financial services companies to avoid bringing harm to clients,” says Peters. “It calls for reporting that cuts a wide swath through our entire business, covering data domains such as clients, partners, finance and investments. We now use erwin to document our reporting, which in turn will enable auditing all the way back to the source of the data.”

With erwin, SJP defines business terms and picks out the data elements that go into them. For any term or element, they will be able to follow the lineage back to the point in the organization where the data originates. Based on that information, they can then build rules to ensure quality at every point along the data path, from source to report.

“Pulling data from so many different domains for Consumer Duty also allows us to change our conversation with the data stewards,” Peters explains. “As we build out our data governance effort, instead of going vertically and starting from scratch within each domain, we can go horizontally. We can say to the stewards, ‘We’ve already incorporated fifty of your data elements as part of the Consumer Duty work. Now we’ll incorporate the last few and you’ll be done.’ This horizontal approach is our way of extending the use of erwin Data Intelligence and advancing data governance more quickly to all the data elements in the business.”

How automation tames a heterogeneous data landscape

SJP manages their data on a variety of platforms and applications. Their complement of tools for ETL and reporting includes Matillion, Mulesoft, Talend, Power BI, Tableau, Python, Snowflake, Tableau and SQL Server Integration Services (SSIS).

Given that heterogeneous mix, it’s important for SJP to automate the harvesting and management of their metadata. They use erwin Standard Data Connectors to auto-ingest or automate the harvesting of metadata from data-at-rest platforms. They also use erwin Smart Data Connectors to capture data in motion and data transformations between platforms.

The savings in manual labor alone are huge. “We would truly struggle if we didn't have the connectors to accurately document the structure of our databases in erwin,” says Peters. “We've done loads of scanning with erwin Standard Data Connectors, and the documentation output from them is brilliant. We value them because, even if you're documenting a single system in isolation, the connectors do it for you. The main benefit is that erwin Data Connectors allow us to do something that, were it not for automation, we wouldn't even consider doing. erwin saves us trying to work it out manually. It’s really as simple as that.”

The business value of anticipating audits and data quality problems

The result will be deep insight into SJP’s heterogeneous data estate. They will have what they need for impact analysis to quickly assess pending change. They will be able to get to the root cause of data quality problems much faster than they ever could. They consider it a huge advantage to be able to see what’s happening in the data before it goes outside to their clients.

“We spend a lot of time researching and responding to queries from partners and clients,” Peters notes. “Anticipating data quality problems instead of reacting to them will cut that time. It's difficult to put a figure on it, but it’s conceivable to reduce costs in that area alone by about half.”

And, in anticipation of audits, SJP has created an object in erwin called the Key Risk Indicator. From an erwin report, they can drill into the object to see the source of all the data behind it, including how the data has been coded. 

“The real business value of erwin is that we now have an important safeguard when our data needs to be audited and checked,” says Peters. “That will enable us to save days or weeks in responding to a request for, say, a Consumer Duty audit. That's a huge benefit for us. Our biggest realization is that erwin Data Intelligence is more than a reference library. It's not just a one-and-done, sit-on-the-shelf software package to install. It's a living, breathing capability that will allow us to manage our data estate much more effectively in the future. Our evolution with this product is ongoing.”