Intricacies of data accuracy in Wealth Management

The responsibility of ensuring data fidelity for wealth managers keeps me up at night. Our key performance indicators (KPIs) pivot around data accuracy, completeness, and timeliness. We constantly strive to streamline processes that allow wealth managers to effortlessly access their portfolio data from multiple banks, automatically integrating information into our platform.

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One of our primary objectives is to facilitate the effortless retrieval of portfolio data from multiple banks. This involves intricate technological integrations and sophisticated processes. Bank documentation has to be thoroughly analysed in order to perfectly transform provided data feed and fit it info one Unified Format that will allow to consolidate all information.

This might be extremely involving process taking into account the scale of different files (SWIFT, CSV, JSON, TXT, XML), formats and data transfer methods (REST API, SFTP, EBICS,...) but the huge advantages of in-house build data connection and transformation directly with custodian banks make it worth the effort. This approach allows us to have full control over the data process and most important ensures the highest security of data by excluding 3rd party providers.

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Over 120 custodian connections

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Presently, we interface with over 120 custodians, consolidating an impressive number of over 100 000 positions and over 4000 transactions on a daily basis. However, while these feeds from custodian banks are invaluable, they're not infallible. Common mistakes in these data feeds can range from missing transactions to inaccuracies in asset valuation.

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In 2023 alone, our diligent team has identified and rectified thousands of mistakes within custodian data feeds. We employ a multi-faceted approach to identify these errors, leveraging automated checks, machine learning algorithms, and manual validations by our expert team. We base our daily routine on automated data alerts that detects data discrepancies such as:
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• Performance spike detection with ARIMA model
• Incorrect positions/transaction
• Duplicated positions/transaction
• Partially missing data
• Unclassified positions/transactions Incorrect prices
• Incorrect valuation Incorrect Fx
• Rate Incorrect Quotation Factor

It is worth to mention that during the year our team processed 35k of such data quality alerts which is saving thousands of hours of work for our clients.

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Automated reconciliation -  effort that is worth it all

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The reconciliation process acts as the bedrock of our efforts. It involves cross-referencing data from multiple sources, identifying discrepancies, and resolving them. Just this week, we detected a discrepancy in a client's portfolio valuation due to an incorrect quotation factor applied by one of the custodian banks. Rectifying this ensured an accurate representation of the portfolio's performance, potentially saving the client from misleading insights.
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>>> See the report "Time-saving power of automated reconciliation"

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Time-saving power of WealthArc

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Without our unique approach, existing clients typically spend a considerable amount of time on data reconciliation— often several hours a day, checking all portfolios sifting through discrepancies and validating data accuracy manually. Our build-in-house algorithms allow the team to detect only portfolios that require reconciliation making the process flawless and efficient with minimum client interaction.

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Data reconciliation of tomorrow

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The future of data reconciliation at WealthArc is poised for innovation. We envision leveraging advanced AI technologies to further automate reconciliation processes, ensuring near-instantaneous and error-free data reconciliation for wealth managers. Our focus is now on two game-changing approaches:
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• Document AI – soon will revolutionize wealth management by providing sophisticated tools that  streamline and enhance document processing within the financial sector. This technology employs machine learning and natural language processing techniques to automate the extraction, classification, and analysis of vast amounts of financial documents such as statements, contracts, invoices, and more.
  
  By swiftly organizing and comprehending this data, Document AI empowers wealth management professionals to make informed decisions efficiently, reducing manual errors and accelerating the overall process of client onboarding, compliance, risk assessment, and investment analysis. It is definitely great opportunity for advanced data reconciliation that will automatically compare Account Statements with data feed from custodian banks, point out discrepancies and propose the best solution.
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• Chat Powered by AI - within the realm of wealth management presents a transformative solution poised to significantly enhance data quality and client interactions. Leveraging artificial intelligence, these chat systems are designed to engage with clients in real-time, offering personalized assistance, guidance, and support while concurrently gathering valuable financial information.
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  By employing machine learning algorithms, these AI-powered chat systems can swiftly interpret and analyze client queries, extracting pertinent details and subsequently updating databases with accurate and relevant information. This not only ensures a higher level of data accuracy but also facilitates the constant enrichment and refinement of client profiles and investment preferences.
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  Moreover, AI Chat interfaces serve as a seamless channel for clients to obtain immediate assistance, reducing response times and improving overall customer satisfaction while concurrently contributing to the ongoing improvement of data quality within wealth management processes.

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With all respect to all above points there is one most important topic that needs to be taken into consideration when we discuss about innovative AI and data quality solutions. Ensuring data security is paramount in wealth management, especially when implementing new AI features. To alleviate concerns, robust security measures must be implemented to safeguard sensitive financial information. Encryption protocols, multi-factor authentication, and stringent access controls should be rigorously enforced to protect client data from unauthorized access or breaches.

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Additionally, compliance with industry regulations such as GDPR, CCPA, or specific financial sector standards must be a top priority. Transparent communication about the implemented security measures, including regular audits and assessments, will instil trust and confidence among clients. Assuring them that the AI features undergo rigorous testing for vulnerabilities and privacy considerations will further reinforce the commitment to data security. Collaborating with cybersecurity experts and investing in cutting-edge technologies specifically designed for threat detection and prevention will demonstrate a proactive stance towards safeguarding client data, mitigating fears associated with the integration of new AI functionalities in wealth management practices.

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Relentless innovation in Data for Wealth Management

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It has to be clear to everybody working with asset management: data reconciliation stands as a pivotal pillar in ensuring the integrity of wealth management portfolios. At WealthArc, our unwavering commitment to data accuracy, coupled with relentless innovation, continues to redefine the landscape of data reconciliation in the realm of wealth management putting as a top priority data governance and security.

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WealthArc team: Who we are, what we do

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As Head of Data at WealthArc, my journey within the financial technology realm has been one driven by a passion for precision and accuracy. With background in Computational Engineering, I was thrilled to join WealthArc where we connect outstanding data quality with high complexity of data model consolidation coming from custodian banks. My role revolves around steering a team dedicated to ensuring data integrity and reliability within our platform. WealthArc, a leading wealth management solution provider, relies on our team's expertise to guarantee that wealth managers have seamless access to accurate portfolio data.

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Our team comprises skilled individuals with diverse backgrounds, numbering 6 experts. Each team member brings a unique blend of expertise, be it in financial analysis, algorithmic design, or software development, enabling us to address multifaceted challenges in the wealth management space. We have gathered experience in biggest banks like HSBC or CITI and data-leading companies  such as Nielsen. The collective proficiency and interdisciplinary background amalgamates seamlessly to orchestrate a robust data infrastructure at WealthArc. This unique set of skills allow respectively small team to handle hundreds of data connections and maintain highest data quality. What’s the secret? – we are able to automate over 99% of our work and letting us to focus only on the most difficult cases