Apr 21, 2021

Broadridge: AI’s relevancy will depend on partner ecosystems

AI
Broadridge
ML
partnerecosystems
William Girling
3 min
As AI becomes a necessary tool for staying relevant in today’s market, Neha Singh at Broadridge tells us why establishing partner ecosystems will be vital
As AI becomes a necessary tool for staying relevant in today’s market, Neha Singh at Broadridge tells us why establishing partner ecosystems will be v...

Individual companies’ relative maturity in terms of artificial intelligence (AI) capability is fast becoming an important differentiator. Furthermore, for Neha Singh (NS), Vice President of Innovation and Growth at Broadridge, that gap is widening:

“We have ‘leaders’ in the space with multiple use cases, growing AI adoption, and a greater proportion of spend on AI. They have invested in access to clean data and a modern tech stack and are seeing outsized benefits, increased revenues, and reduced costs vs ‘non-leaders'.”

Therefore, with a desperate need to update and remodel their systems, those companies falling behind need a way to regain their advantage.  

Singh is convinced that developing an ecosystem of external partners will be essential for this objective. In a Q&A session with FinTech Magazine (FM), we find out more about the burgeoning automation revolution.

FM: The utility of AI for FSIs has been demonstrated by COVID-19. What do you expect from the next five years of development?

NS: We expect to see a significant acceleration in AI investment as firms realise strategic benefits, including increased revenues, decreased costs, faster and better decision-making, and effective risk management. 

According to our recent Next-Gen Technology Adoption survey, over the next two years, firms plan to increase their overall IT budgets for next-gen technologies from 12% to 16% on average. Firms will focus on ensuring access to clean data and a modern tech stack to accelerate AI benefits, especially as they move to the cloud.

As they mature in their use of AI, firms will move towards a hybrid approach: business unit or product-driven AI use cases (i.e. decentralised) that are supported by a ‘centre of excellence.’ This will enable organisations to ensure AI delivers commercial value while leveraging AI expertise in a scalable manner.

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FM: With human workers displaced from the more rote aspects of their work by automation, how will they be redistributed?

NS: This shift will create a virtuous cycle that increases productivity and role satisfaction, and enables greater scale in operations. It is critical to manage this transition with empathy and clearly communicate how it can help employees in their day-to-day roles. When Broadridge implemented its digital workforce, we empowered our associates to identify opportunities to automate repetitive and high-volume work, to enable them to do more.

In an interconnected and heavily regulated industry such as financial services, human oversight and the ability for people to make decisions about when to halt digital labour in certain situations will remain key to the governance process.

FM: Please tell me about Broadridge’s 'Centre of Excellence'. Why was it created, what goals have been set and how are you achieving them?

NS: Our AI Centre of Excellence (COE) is composed of data scientists and technologists that use AI/ML techniques to create new products and enhance existing offerings. As a global fintech leader, Broadridge is in a unique position to help clients extract valuable insights from data assets on the company’s platforms and transform the way they do business. 

The COE ensures access to AI talent, instils best practice, and forms a close partnership with business leaders to drive new proofs-of-concept (POCs). This allows us to translate high-level ideas for leveraging AI into tangible impact for clients, quickly and at scale. The COE has helped incubate numerous POCs, many of which are included in our products and services.

FM: How is Broadridge using AI to boost its products and services?

NS: We’re embedding AI into our products and services, allowing clients to realise value in a cost-effective manner. One example is our new corporate bond trading platform, LTX®, which uses AI (LTX AISM) to help broker-dealers automate fixed income trading and maximise liquidity for asset managers. 

Broadridge is also providing banks and wealth management firms with new predictive analytics solutions that can transform their business. By harnessing data in collaboration with our partner Fligoo, we’re able to predict the needs of each client and create a personalised experience that drives client satisfaction and asset growth.

Pictured: Neha Singh, Vice President of Innovation and Growth, Broadridge

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May 10, 2021

Open Finance: The future of data sharing

openfinance
datasharing
Cybersecurity
Technology
William Girling
7 min
Commentators from TrueLayer, Nutter, and Zilliqa Capital help us understand the value of data sharing and why Open Finance could be its future
Commentators from TrueLayer, Nutter, and Zilliqa Capital help us understand the value of data sharing and why Open Finance could be its future...

Data: What is it good for?

Although most of us probably don’t consider it as such, data could be regarded as one of the most recyclable commodities on Earth. Every day, consumers produce it, companies collect it, extract the value, transform it into actionable insights, and then create new products and services for the market. From here the cycle continues, and the results it’s produced for financial service institutions (FSIs) so far have been favourable.

Data sharing can be best understood as a consent-based agreement by which privacy is waived in a limited capacity for commercial purposes. Customers gain products that have higher relevance to their lives while FSIs reap enhanced marketing and development opportunities. In Deloitte’s article ‘The next generation of data sharing in financial services’, the overall FSI benefits of data sharing are summarised into three categories:

  1. Inbound data-sharing (acquiring data from third parties) = enriched decision-making.
  2. Outbound data-sharing (sharing owned data with third parties) = enabling companies to draw on capabilities otherwise undeveloped within their own organisation.
  3. Collaborative data-sharing (inbound and outbound sharing of similar forms of data) = allowing companies to create richer, larger and more comprehensive datasets than siloed efforts could achieve. This is particularly important as forming ‘data lakes’ becomes more popular.

And yet, despite the mutual beneficiality of data sharing, there still exist several potential drawbacks and aversions to overcome. For customers, there is a persistent reluctance to share sensitive data - Statista found that approximately 44.3% of US fintech app users experienced some degree of discomfort, whether related to account balances, loan history or investment information. Worse, a Harris Poll survey conducted on behalf of IBM found that only 20% of respondents “completely trust” organisations to properly maintain their data. With incidents of compromised security involving major companies like Capital One and Microsoft still making headlines, this is, perhaps, not unsurprising.

Benefits of sharing data

For institutions: better decision-making, access to third-party capabilities, greater scale of data

For regulators: support for innovation and competition, enables effective system oversight

For customers: access to higher quality and more efficient products

Drawbacks of sharing data

For institutions: competition hindered by lack of secrecy, could breach privacy regulations, could potentially alienate customers by appearing ‘omniscient’

For regulators: possible breach of customer privacy

For customers: personal data could be mishandled or misused

(Above from World Economic Forum) 

Data sharing is also not without risks for FSIs themselves; creating such a forthcoming environment could erode competitivity by handing too much information to rivals, complex and evolving privacy regulations like GDPR and PSD2 could be breached by unforeseen tech developments, or companies could simply alienate clients by appearing too omniscient for comfort. 

Among VC firms and investors data sharing is an important decision-making component, particularly during early-stage investment. Michael Conn, Chairman, CEO, and Co-Chief Investment Officer at Zilliqa Capital, explains, “It is important that the target investment team be open and willing to share the data reflecting their performance to date, the market opportunity and any other metrics that would help demonstrate why they are a better investment than another in the same space.” However, at the same time, Conn clarifies that the value of data today can sometimes be overemphasized; for Zilliqa Capital, the quality of a potential investment’s team is often more of a determining factor. “The fact is that most, if not all businesses, will at some point be forced to pivot away from their initial plans - see Amazon. It is just not possible for data analytics, at least as of now, to prove itself superior to gut instinct when evaluating the quality of an investment target’s team.”

If not fully utilisable as a resource for decision-making, then, what’s needed is a re-evaluation of data sharing, both in terms of its place within modern finance and the methods by which its present shortcomings can be overcome. Open Finance and API (application programming interface) technology could represent such an opportunity. 

Open Finance’s value proposition

“Open Finance is all about empowering customers,” explains Jack Wilson, Head of Policy and Regulatory Affairs at TrueLayer. “It gives customers the ability and the right to re-use their financial data in new and innovative ways. It does this by giving a role to third-party providers, who securely retrieve data and put it to work for the customer.” These actors can do so in a variety of ways, such as:

  • Consolidating multiple held accounts into a unified view
  • Facilitating electronic data transmission that eliminates the need for physical documents when applying for financial products 
  • Using account data as a form of identity verification

These capabilities are utilised in one of Open Finance’s most widely discussed aspects: Open Banking. Defined by McKinsey & Co as “a collaborative model in which banking data is shared through APIs between two or more unaffiliated parties to deliver enhanced capabilities to the marketplace,” Open Banking allows for a more direct consumer-bank relationship. The APIs themselves can be of three distinct models: public, partner and internal, each of which has specific functions and benefits. Regarding the latter, these include overall cost reductions, increased operational efficiency, enhanced innovation through collaboration with developer communities, and greater security.

“Consumers are increasingly demanding financial data aggregation services through APIs because it makes personal financial management much easier,” says Thomas J. Curry, Co-Chair of the Banking and Financial Services group at Nutter and former US Comptroller of the Currency. “Banks and fintechs each want to be the primary portal for financial services and they are competing to keep or obtain the customer relationship.” 

Types of API

Public: APIs used by external parties to develop new apps and products. These often facilitate innovative results as a consequence of broader community engagement.

Partner: These APIs create a more integrated connection between business partners, suppliers, etc. They offer better security, lower operating costs, and enable API monetisation opportunities.

Internal: Only used by developers within a single enterprise, internal APIs offer cost reduction, better efficiency and greater security. However, they also lack the potential with regards to integration and innovation.

(Above from McKinsey & Co)

“Open Finance, which broadens out the types of accounts accessed, could offer yet more benefits for both customers and companies,” adds Wilson. He cites the following:

  1. Aggregated savings and investment data, bringing more holistic financial oversight to consumers.
  2. Granting access to data that can bring value-added services, such as financial advice, “robo-advice”, better ID verification, and KYC.
  3. Empowering third parties to carry out fund transfers between customer accounts (savings, ISAs, investments, etc) and initiate account switching.

Security: The elephant in the room

Carried out in its most ideal form, then, Open Finance’s benefits for both customers and companies makes it an attractive proposition. However, there remains what McKinsey calls the topic’s “elephant in the room”, security. Data sharing in any capacity should be a central concern, with each dataset’s value accorded an appropriate level of protection, and customers need to understand how and why some data is used. “[I]nformed consent requires understanding the implications of sharing before approving —no small feat when the reflexive clicking of ‘I Agree’ on an unread set of terms and conditions is standard,” said McKinsey in ‘Data sharing and open banking’. Curry believes that cybersecurity and the protection of data form the major concerns for fintechs and banks regarding APIs’ functionality. “[In the US] Section 1033 of the Dodd Frank Act makes it clear that consumers have a right to their financial information. Some progress has been made in developing voluntary standards for APIs but regulatory clarity is needed. The Biden CFPB (Consumer Financial Protection Bureau) will likely develop a more concrete regulatory framework for APIs.”

Therefore, it seems clear that, in addition to general clarity regarding data sharing policies, what customers really need are examples that demonstrate why APIs are beneficial and what Open Finance can do for them.

A recent collaboration between TrueLayer and UK digital bank Monzo provided one such demonstration. With customers using Open Finance as a payment method for online gambling, Monzo needed a solution to protect its at-risk customers by blocking transactions to certain gaming sites. TrueLayer was brought on board to implement an enhanced API capable of notifying the bank whenever a customer with gambling restrictions on their account attempted to pay via Open Finance. TS Anil, Monzo’s CEO, praised the API and stated that it was “simple to build, proven to work, and will help protect hundreds of thousands of people.” The finance industry’s accumulation of such examples will be pivotal in convincing consumers that data sharing can be responsible and useful for safeguarding them.

Data sharing through Open Finance is ultimately a path towards greater convenience, better products and services, and significantly cheaper operations for FSIs. Making sure that customers are aware of these benefits, concludes Wilson, will be the aim of the game. “At the very least, dealing with physical paperwork and documentation in financial transactions will become a thing of the past."

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