Rapid Bordereaux Extraction: using technology to improve BDX processing - Blog - artificial.

Rapid Bordereaux Extraction: using technology to improve BDX processing

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The limitations of bordereaux

Insurance bordereaux (BDX) reports are used as a way of sharing data between parties in the distribution network from customer to carrier. The broker is normally responsible for collecting the data and then creating the bordereaux.

Issues can arise immediately in the bordereaux lifecycle: data is collected in different ways using various software applications. From there, the information is stored and reported in formats that are not generally standardised across the value chain.

When separate coverholders create bordereaux files for one carrier, the same data can end up presented in many different formats. There may be inconsistencies in how the data points themselves–date formats, addresses–are formatted, and even the various ordering of columns in tables can cause challenges and require time consuming manual intervention. These often occur as a result of the customer's particular choice of software.

The carrier therefore expects to receive the 'same' data from their sources, but in inconsistent formatting. In order to consume this data into their systems, the carrier requires some level of standardisation, validation and translation.

In situations where the received data is incomplete, these issues can be tracked and allocated to relevant parties to resolve. Direct and real time feedback to the coverholder in relation to the quality and completeness of the data they have provided can be of tremendous help.

Risk aggregation-related bordereaux files are considered the most complex, because they are commonly used to feed data into complex software models in which the data must be in a specific format. The source data is often provided in the incorrect format, meaning more complex derivation and augmentation is required.

How can technology make bordereaux processing better?

Software created to improve bordereaux processing has so far been focussed on enabling the standardisation of incoming files using predefined mapping or rules engines. The aim of this technology is usually to input the data into another system, rather than to digitise the full end-to-end management of a carrier's delegated business.

Whilst this is a step in the right direction, it still has several limitations: this approach needs humans to set up new rules or mappings each time a new format is provided. There are often different formats for each coverholder, sometimes even differing between classes of business. And each time new coverholders are onboarded, new mappings need to be created. Coverholders can even change format whenever they like, further adding to the confusion.

But it doesn't have to be this way forever. Bordereaux processing software is improving and, with technology like artificial's Rapid Bordereaux Extraction tool, insurers and their clients can improve the way they receive, process and monitor their reports.

1. Machine learning engines

Advances in the application of machine learning enable the engines to support more than a rules-based approach. In this scenario, the engine can be configured to extract a target set of columns as required, but rather than needing guidance to find the relevant data points it will locate them itself.

2. Easy configuration

Another way of improving BDX processing is by empowering software users to define and amend their own rules and validations. Some validation and management fundamentals should be mandated to support proper digitisation and standardisation but many day-to-day elements could be amended with minimal risk. 

3. Transactional data for minimal disruption

Structuring and storing the data at a transactional (declaration) level within the management tool is key to better reporting. Historically, each file is considered as one transaction where all components must be valid to progress. This means small discrepancies in single records can block the entire process, but by working at a policy/declaration level any valid data can be automatically processed and exceptions instead dealt with on a case-by-case basis.

4. Better reporting insights

A transactional level of data also gives insurers full insight into the current and recent performance of their delegated portfolio. Insights can be expanded, looking beyond financial performance to a more general coverholder performance. Is data being submitted in a timely manner and to the required standards? Are the coverholders operating within the remit that has been defined in the coverholder agreement? These questions can be answered thanks to detailed, up-to-date reporting.

What's next for bordereaux?

The insurance market is changing and innovations are being driven by multiple parties. In previous years, the London Market Target Operating Model (LM TOM) was a key part of the modernisation proposal at Lloyd's; this morphed into Blueprint One and more recently Blueprint Two.

Market practitioners collaborated on proposed API standards some years ago but these appear to have been superseded by the aspirations of Future at Lloyd’s. LMADARE are also looking to provide an alternative route to building a solution that is defined by and works for the market.

At some point, digital data and integration standards will become a reality. Carriers and coverholders alike will then have the means to integrate, but that doesn't mean a frictionless experience. Existing technology ecosystems will be restrictive, and investment will be required to take advantage of the new standards. For some participants, business as usual may be the only option until they are forced to change.

Adoption may also be enforced by the carriers. Bordereaux requirements and standards are now more regularly defined as part of contractual terms. The costs associated with doing business 'the old fashioned way' have become prohibitive, and it is in the carriers' interests to mandate usage of new standards, once they become available.

On the other hand, coverholders are powerful because of their relationships with the end customers. There is no business without them, so if carriers wish to continue their partnerships with clients that aren’t able to change their software, technology is now advanced enough to support this way of working in a vastly more efficient manner.

Ultimately, once one insurer proves that digital bordereaux processing is the way forward and can demonstrate the profitability of such an approach, others will have to follow.

The benefits of better bordereaux processing

Using a digital solution with workflow, automation and machine learning-driven data extraction at its foundations will lead to several benefits for carriers and subsequently their customers:

  • Significant reduction in manual effort required to onboard new facilities or coverholders

  • Exceptions routed automatically to the relevant party

  • Real-time data insights, once received from the coverholder

  • End-to-end management process, with direct access for coverholders via portal or API

  • Data readily available via API for use in other applications and in the creation of reporting

If you would like to know more about how Artificial technology can help your bordereaux processing, get in touch.

Anna Burge
Tim Bates
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