Steps to Realizing Robust Regulatory Data Management at Financial Firms

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Amid today’s rapidly evolving financial markets, banks must deploy cutting-edge data management practices to ensure efficient and accurate compliance filing, while unearthing in-depth insights into all exposures. Many firms are yet to capitalize on the opportunities this approach presents, running the risk of non-compliance and increased regulatory scrutiny.

Last year saw an unprecedented number of developments that added yet more pressure on the risk and compliance teams in banks.

New regulations, rapidly growing volumes of data, and the fallout from COVID-19 characterized the year. For local firms in markets like Japan, reliance on manual processes further exacerbated these challenges.

To meet the demands of today’s new paradigm, banks must incorporate data sustainability into their regulatory reporting procedures, as highlighted by panelists at a recent webinar hosted by the International Bankers Association of Japan. But what constitutes data sustainability, and how does it enhance the regulatory reporting process?

regulatory data management

“Data sustainability is about taking a look at the current architecture that banks have in place, and implementing best practices from source to regulatory filing,” explained Harry Chopra, Chief Client Officer at AxiomSL. “It’s about how well banks have designed their current systems, and improving what’s already in play.”

Regulatory Data Management: The Business Case

Upcoming capital and liquidity requirements further underscore the need for data sustainability and sound regulatory data management. The arrival of the Basel Committee on Banking Supervision’s (BCBS) Basel IIIi and “Basel IV”ii accords in January 2023 will not only call for more granular reporting of financial data, it will also demand more data sets from banks. Currently, firms must use either a Standardized Approach to Credit Riskiii, where they use an external credit ratings agency to quantify their required capital, or an Internal Ratings-Based Approachiv where banks carry out this task internally. Both must be reported under the new rulesv.

Similarly, BCBS’s Net Stable Finding Ratio (NSFR)vi, designed to promote the long-term liquidity resilience of banks by ensuring that the amount of stable funding available is equal to the amount required, will also demand yet more data filing. NSFR has yet to be implemented in several jurisdictions globally, including Japan and the US. Late last year, the Federal Reserve made the somewhat surprising announcement that it would go live with the NSFR from July 1, 2021vii —giving American banks just eight months to prepare.

“Data sustainability is also about making sure that banks understand possible future requirements, and position themselves accordingly,” added Chopra.

Many local banks in Japan have yet to make the switch to fully automating the filing process. This is widely understood to be the case in other Asian markets.

For firms seeking to improve their current filing processes, below are four steps to realizing robust regulatory data management within financial firms.

1. Define Critical Data Elements

With every bank owning various sets of exposures—be that commercial credit, fund settlement or derivative exposures, among others—a good place to start is to focus on the individual assets that reside within these. Take consumer credit exposures, for instance; these include car loans, home loans, student loans and many other such facilities. Each loan bears the same or similar characteristics, such as loan type, purpose, counterparty and collateral.

“What we’ve found from many of the implementations we’ve delivered around the world is that defining critical data elements by asset class makes the job so much easier,” enthused Chopra.

2. Apply Data Governance Principles

To ensure the rigor of each critical data element, governance principles can be applied. In 2013, the BCBS rolled out 14 such principles—otherwise referred to as BCBS 239viii —covering four areas: governance and infrastructure, risk data aggregation, risk reporting, and supervisory actions. AxiomSL’s Data Sustainability Concept aligns with BCBS 239. When applied to any asset class, the following nine principles ensure data integrity:

  • Completeness
  • Timeliness
  • Accuracy
  • Precision
  • Conformity
  • Congruence
  • Collection
  • Cohesion
  • Lineage

“Principles make intuitive sense, but the challenge is always with execution and application,” cautioned Sergey Volkov, Partner at PwC. Data sustainability and regulatory data management, he added, must become habitual if banks are to use data effectively for tasks such as regulatory reporting.

3. Implement a Set of Shared Business Rules

To translate the data into meaningful insights, a shared set of business rules is needed. Using Boolean Logicix and the Boolean operators “OR”, “AND” and “NOT”, banks can aggregate several assets into a single report, or simply account for just one asset. This is done by selecting multiple exposures: for instance, home loans OR car loans; student loans AND personal loans AND car loans; or by selecting individual assets like a personal line of credit, and excluding all other assets (NOT). This enables banks to identify their entire exposures, those of a single asset, or a collection of assets.

“Having a shared business rule allows banks to enrich data, pre-process it, and aggregate a set of figures. This enables an organization to say, ‘our exposure to commercial loans is this much’,” explained Chopra.

4. Ensure Data Lineage

A core challenge banks have faced since the onset of regulatory reporting is keeping track of what has changed during the reconciliation process and by whom. A further feature of data sustainability is lineage, where data is both connected and traceable from source to filing: any manual amendments made within the reporting process should be visible and attributable. Ryuichi Nagano, Partner at PwC, warned that without such auditability, banks may face unwanted regulatory scrutiny.

While reporting is typically labor-intensive for banks, regulators are increasingly streamlining the filing process.

“Regulators in the Asia Pacific are not just asking for more data, they’re moving away from form-gathering to the collection of more granular information,” outlined Abraham Teo, Asia Pacific Regulatory Reporting Product Leader at AxiomSL. “This is exactly what banks need—not interpretation.”

Combined, data sustainability and streamlined filing processes will elevate regulatory reporting and risk management to new heights, webinar attendees concluded, ensuring that banks are both compliant and well-informed of all exposures.

To learn more about how your firm can realize the potential of sustainable data and rigorous regulatory data management, please contact us.

The above article is based on a recent webinar hosted by the International Bankers Association of Japan, titled ‘Data Sustainability in Regulatory Reporting’, which was held on 12 January 2021. The discussion was moderated by Harry Chopra, Chief Client Officer at AxiomSL, with panelists Ken Utsunomiya, Joint Global Head of Operations at Mizuho Securities; Sergey Volkov, Partner, PwC APAC and LIBOR Leader at PwC Consulting; Abraham Teo, Head of Product Management, APAC at AxiomSL; and Ryuichi Nagano, Financial Service Assurance at PwC Japan.








AxiomSLのチーフクライアントオフィサーHarry Chopraによれば、「データの持続可能性とは、まず金融機関における既存の構成を把握し、データソーシングから報告提出までのプロセス全体でベストプラクティスを実装することです。その際に重要となるのは、現行システムがどれだけ上手く機能しているか評価し、その上で長所を伸ばすことです」。


データの持続可能性アプローチと、信頼性の高い規制データ管理の必要性に拍車をかけているのが、自己資本・流動性に関する将来的な要件です。2023年1月にはバーゼルIIIx /IVxi 規制が導入されるなど、きめ細かな財務データの報告だけでなく、より多くのデータセットも要求されるようになります。その一例が必要資本額の算定です。現状では、外部機関の信用格付けによる「信用リスクに係る標準的手法xii 」と、金融機関独自の「内部格付手法xiii 」から選べますが、新規制では両方の算定結果が求められますxiv

別の要素は、バーゼルの安定調達比率(NSFR)xv 規制です。NSFR規制は金融機関の長期的な流動性回復力を保つことを目的としており、利用可能な安定調達額を必要額水準に保つことを定めています。NSFRは日本や米国を含む一部の法域では未施行ですが、米国では2021年7月1日から導入されることが連邦準備制度理事会から発表されています。今回の発表は意表を突いたもので、米国内の金融機関にとって準備期間はわずか8か月しかない計算になります。xvi




1. 最重要データ要素を定義する



2. データガバナンスの原則を適用する

最重要データ要素の定義で曖昧さを排除するためには、データガバナンスの原則が役立ちます。具体的には、バーゼル委員会が2013年に発表した14の原則(通称「BCBS 239xvii 」)を指します。この中では、ガバナンス/インフラ、リスクデータの集約、リスク報告、監督措置の4つの領域がカバーされています。AxiomSLが掲げるデータ持続可能性のコンセプトも、同じBCBS239に準拠しています。アセットクラスの分野では、データの整合性に関する次の9つの原則が当てはまります。

• 完全性
• 適時性
• 正確性
• 精度
• 準拠
• 統合/適合
• 収集
• 結束
• データリネージ

PwCのパートナーであるSergey Volkov氏は、「これらの原則は直感的に理解できますが、厄介なのは実際に適用することです」と警告しています。同氏によれば、規制報告などのプロセスでデータを効果的に使用するためには、データの持続可能性アプローチと規制データ管理を習慣化する必要があります。

3. 一連の共通ビジネスルールを実装する

データを実用的な情報に変えるには、一連の共通ビジネスルールが欠かせません。ブール論理xviii と「OR」、「AND」、「NOT」のブール演算子を使用すれば、複数の資産を単一レポートに集約することも、1件の資産に絞り込むこともできます。たとえば、「住宅ローン OR 自動車ローン」や、「学生ローン AND 個人ローン AND 自動車ローン」のように複数のエクスポージャーを選択したり、個人の信用枠を選択してそれ以外を除外(NOT)したりできます。この仕組みにより、エクスポージャー全体だけでなく、単一資産や一部資産のエクスポージャーも識別できます。


4. データリネージを徹底する


金融機関にとって規制報告は一般に人海戦術的な側面がありますが、報告の提出プロセス自体はますます合理化されています。AxiomSLでアジア太平洋地域の規制報告プロダクトを統括するAbraham Teoは、「アジア太平洋地域の規制当局は、より多くのデータを求めていますが、その細かさも重視しています。解釈の余地を残さない報告の提出こそ、金融機関に必要なのです」と述べています。



本稿は、国際銀行協会が2021年1月12日に開催したオンラインセミナー、「規制報告におけるデータの持続可能性」に基づいています。オンラインセミナーの司会者はHarry Chopra(AxiomSLチーフクライアントオフィサー)が努め、宇都宮研氏(みずほ証券グローバルマーケッツ部門マネージングディレクター)、Sergey Volkov氏(PwCコンサルティングパートナー兼PwC APAC・LIBORリーダー)、
Abraham Teo(AxiomSL APAC製品管理責任者)、そして永野隆一氏(PwCあらた監査法人パートナー)にパネリストとしてご参加いただきました。

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