Ensuring clients have a positive user experience and rooting out operational inefficiencies will be critical if private credit managers are to grow their market share. Innovative technologies, including Artificial Intelligence (AI), which are being developed by industry leaders such as Broadridge, will help facilitate this.

A competitive market gets more intense

Despite the challenging macroeconomic conditions, the private credit industry is holding up well, with Assets Under Management (AUM) expected to double to $2.8 trillion by 2028.¹

The post-Covid interest rate increases across North America, Europe and Asia were a boon for private credit funds, especially as many of them are floating rate investments making them more attractive than other asset classes. Although rates are now beginning to fall [see table below], this is benefiting those private credit funds offering fixed rates.

Despite this, the market is becoming more competitive.

Not only are there a record number of private credit funds raising money,² but investors are becoming incredibly selective about where they deploy their cash. Along with generating decent returns, investors want their managers to provide them with a positive user experience, with seamless onboarding, ongoing digital reporting, client-friendly communication channels, etc.

Just as clients’ needs are getting more complex, the cost of doing business is skyrocketing (i.e. because of inflation, growing regulations, etc), and this is forcing firms to identify operational savings.

To meet the growing demands of clients while simultaneously keeping spending under control, private credit firms are increasingly turning to disruptive technologies, such as AI, for help.

Private credit looks to embrace AI

The financial services industry – including private credit - is making tangible progress on AI.

In the UK, a 2024 study of banks, insurers, wealth managers and financial sponsors by Lloyds found that 63% of firms are now investing in AI, up from 32% in 2023. ³

According to Broadridge’s 2024 Digital Transformation and Next-Gen Technology Study, 66% of private equity/credit managers are making either ‘moderate’ or ‘large’ investments in AI. On average, private equity/ credit managers plan to ramp up their spending on AI by 16.5% over the following two years. Of this, the study found that private equity/credit firms will increase their investment in Generative AI by 4.2% over the next two years.

But, what exactly is the industry using AI for?

AI makes its real-world debut

AI has many applications in private credit, and the technology is already being trialed across investments, risk management, and client communications.

On the investment side, AI can digitalize documents and extract information from vast pools of data, expediting the research and credit evaluation process. Through AI, firms may even identify correlations or trends, not easily observable to human analysts.

The technology has use cases in risk management too. AI can be trained to spot build-ups of systemic risk, before making recommendations to private credit managers on the pre-emptive measures they ought to be taking to safeguard themselves against credit defaults and market shifts.

Amid the interest rate gyrations and general market volatility, some private credit firms are using AI to track covenants more assiduously, allowing them to detect potential breaches quickly, thereby reducing the risk of borrower default.

At the moment, APAC-based private credit managers seem to be the most proactive users of AI when performing credit assessments and covenant monitoring, at least when benchmarked against their peers in other major markets.

AI is also transforming client communications

As private credit starts attracting more retail clients, managers will have to change the way they report. Whereas previously, managers would send out periodic reports to a select few institutional investors, now they will need to distribute hyper-personalized updates to large numbers of retail customers.

Some firms are also thinking about using AI to provide customers with personalized investment advice based on client profiles and preferences.

Although AI might help managers with disseminating highly bespoke reports and investment recommendations to clients, some believe the technology’s true value lies in the development of next-generation Chatbots. This comes as more firms look to roll out ChatGPT or Co-Pilot powered Chatbots allowing clients to ask their managers questions in real-time about their investments, i.e. portfolio performance, risk exposures, etc.

Although these Chatbots will only be able to answer fairly basic, i.e., non-technical, questions, they will still free up resources for managers, allowing people to focus more on revenue-generating activities.

Broadridge is also doubling down on its own AI capabilities, with a number of AI-enabled products now coming to market.

Notable examples include Sentry Co-Pilot, an AI-powered tool, which has been added to the Sentry Private Credit portfolio management solution. It is designed to enhance data retrieval and query execution. By providing private credit managers with instant access to critical information through pre-calculated datasets, users of Sentry Co-Pilot will be able to handle investor inquiries more efficiently.

Broadridge subsidiary LTX recently rolled out BondGPT that gives users – including private credit firms – succinct answers to bond-related questions, while simultaneously helping them identify corporate bonds on the LTX platform. As a result, this will make the bond selection and portfolio construction processes much more straightforward for fund managers.

Broadridge also offers AI tools like Distribution AI and the Global Demand Model. Distribution AI provides access to proprietary market intelligence and research, aiding asset managers, including those in the private credit sector, in optimizing their distribution, product development, and marketing strategies. The Global Demand Model analyzes current and future demands for asset management products, tracking over $100 trillion in global assets. It uses AI models alongside expert insights to predict asset flows and demand trends. These tools help asset managers, such as private credit managers, identify market opportunities and strategize effectively.

Keeping on top of the risks

As with any new technology, AI is not without its risks, and this is something private credit firms need to keep close tabs on.

Although AI is impressive, it is not completely error-proof. If the technology is fed bad data, the output will be equally bad. The technology also has a nasty habit of hallucinating, i.e. fabricating responses, which means managers must ensure that any AI-generated analytics are thoroughly fact-checked and sanitized before being used internally or distributed onwards to customers. Broadridge is addressing these issues by implementing comprehensive data validation and AI monitoring systems to ensure the accuracy and reliability of their AI-driven solutions. Trust, security and transparency are at the heart of Broadridge AI initiatives.

Furthermore, data used to power AI engines needs to be safeguarded to the nth degree, to prevent any leakages or cyber-breaches. Failure to do so could lead to safety issues or reputational risk.

The complexity of implementing AI solutions should not be underestimated either. Part of that complexity is ensuring AI models are adequately trained and outputs staged or validated. Aggregating and organizing the necessary data to feed into AI systems is a rigorous process and will take time to implement. Compounding matters further is that some firms are guilty of not adequately training people on how to use AI properly, which in itself is hampering productivity gains.

The number of potential use cases and proofs of concepts (POCs) for AI is massive, but firms risk falling into a paralysis trap, whereby they have so many ideas and possible applications that they get overwhelmed. This can result in managers making poor or undisciplined investments in AI.

Longer-term, private credit managers need to be careful that their employees do not forget critical skills by becoming too reliant on AI, particularly if the technology is being used to perform tasks like drafting PowerPoints or providing comprehensive summaries of large documents.

Adherence to AI best practices is non-negotiable

In addition, Broadridge was one of the first companies to sign up for the EU’s AI Pact, a voluntary initiative for companies to start incorporating the principles of the EU’s AI Act into their businesses ahead of the regulation’s actual implementation.

AI is making waves in private credit circles, supporting better investment decision-making, risk management and client communications. As a technology, it is having a transformational effect on private credit’s operating model and organizational structure. However, AI is not risk-free, so firms should exercise caution when using the technology.

1 Preqin – December 13, 2023 – Number of private debt funds in market reaches new record – Preqin reports

2 Preqin – December 13, 2023 – Number of private debt funds in market reaches new record – Preqin reports

3 IBS Intelligence – October 3, 2024 – AI investment doubles among UK financial institutions in just one year