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Any financial institution looking to succeed in credit risk management faces continuous pressure to evolve, with shifting customer habits, regulatory changes and cost of living hikes being among the factors making underwriting and monitoring ever challenging.
Over the past few years, we’ve seen an emergence of products like Buy Now Pay Later (BNPL), significant shifts in income patterns and unprecedented macroeconomic events capable of putting any lender under stress.
The increasing complexity of customer’s lives means keeping the current processes and models relevant requires more and more effort. In some cases, it means lost business as a result of having to reject customers but it also often means increasing portfolio risk.
A key way to remedy this is to take a closer look at the data financial institutions use to manage those challenges - and then optimise them.
Typically, the primary source of information related to credit risk comes directly from a credit bureau or an equivalent organisation specialised in gathering information and applying some metrics on top of that.
These organisations are essential for any functioning credit market but they come with certain gaps and limitations. The tradeoff for having a broad data set is that it is slowly evolving both in terms of how up-to-date it is but also how well adjusted it is to changing environments.
Thanks to the growing adoption of open banking, this growing gap can now be more viably addressed through the use of enriched financial data - specifically transactional data. This is because financial transactions have the advantage of being instantly - or near-instantly- available, reflecting customer habits and providing an endless source of insights.
But how can that be applied to risk mitigation?
Equipped with one of the most powerful enrichment engines, Bud’s AI platform provides highly accurate categorisation, merchant mapping, detection of recurrence and more valuable signals designed to supercharge credit risk monitoring.
Drive, our customer data platform, takes this to the next level by generating customer characteristics and insights that combine enriched transactions with dedicated algorithms and external data points, providing a unique view of each customer across your customer base.
By democratising access to data through natural conversation queries, financial institutions can empower their teams with access to instantly available, high-impact insights. We surface this using dedicated dashboards and supplement it with both data and a context-aware generative AI chatbot. This means absolutely no technical skills or data knowledge is required to get the information needed.
Because of Bud’s extensive experience in supporting both lending organisations and retail banks, we have built a vast portfolio of risk and lending insights that are all instantly available in easy-to-use dashboards which allow for cross-filtering and free data exploration.
However, presenting the data is only the beginning. Drive’s true contribution to risk mitigation comes from its ability to actively monitor changing patterns to provide proactive alerts if selected cohorts of customers - or even your entire customer base - exhibit certain warning signs.Action Hub, an integral component of Drive, can then automatically trigger a warning call to any other system - or directly surface it within the dashboard to ensure no relevant changes go unnoticed.
At Bud, we’re building a set of AI models that are able to both recommend metrics and customer behaviours providing an extra input and helping to identify the right data to track. We are also automating how these processes are performed, meaning our tool can recommend segments of interest in line with changing risk profiles.
As we work on the portfolio-level data, we still retain full visibility of customer’s profiles, we can overlay a single person view alongside an overall or segment position at any time. This enables tactical risk management and provides the ultimate flexibility in both decision-making and monitoring processes.
Ultimately, Drive is built to support broad data sets and while our key capabilities are harvesting insights from transactional data, traditional credit bureau data can still be easily integrated. In fact, we often use key metrics (like credit scores) as one of our dashboard’s key indicators so our partners are equipped with a holistic approach to their customer base and are supported in taking the next best action.
Intended to be an add-on to any existing risk management processes, we consider Drive as a way of accelerating processes, bringing previously unavailable (or otherwise expensive) insights into everyday work and discovering hidden patterns. All of this combined ensures risk management is a much more seamless and easier task, with both time-sensitive and more granular data surfaced to all audiences.
And because Drive is an out-of-the-box solution that doesn’t require complex integration, it will immediately contribute to a better risk management process — regardless of whether your transaction data is sourced via open banking or comes directly from your organisation.
With quality data foundation based on transactions, Drive is broadly applicable to almost every area of customer banking - but risk is one of the places with the most immediate impact.
So if you’re looking to capitalise on opportunity with an AI-powered competitive edge, Bud’s here to help.
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